National Conference on Geospatial Technologies in Agriculture 20-21 February, 2020
Book of Abstracts
Organized by
Association for Management of Agricultural Research and Agripreneurship (AMARA) In collaboration with ICAR-National Academy of Agricultural Research Management (NAARM) Citation P D Sreekanth and M Balakrishnan (Eds), 2020. Book of Abstracts, National Conference on Geospatial Technologies in Agriculture, 20-21 February, 2020. ICAR-National Academy of Agricultural Research Management, Hyderabad. Pp:215.
ISBN: 978-81-943090-6-2
Editors P D Sreekanth M Balakrishnan
Year of Publication: 2020
Cover page design: Mr. P Namdev
Published by Association for Management of Agricultural Research and Agripreneurship (AMARA) ICAR-NAARM Campus Rajendranager, Hyderabad-500 030
Printed at : Balaji Scam Pvt. Ltd. Nampally, Hyderabad – 500001, Telangana, INDIA. Tel: 23303424/25, 9848032644 e-mail: [email protected]
Disclaimer The abstracts included in this Book of Abstracts remain the work of the authors/ co-authors and minimally edited to maintain uniformity in style of presentation. MESSAGE In our Country, agriculture supports more than 60% of the population. Around 51% of India’s geographical area is under cultivation. Major shares of its GDP comes from agriculture sector. Government recently launched some major schemes like crop insurance, per drop more crop, Rashtriya Krishi Vikas Yojna to enhance the productivity of the crops. Initiatives like organic farming and increase in the production of pulses are also been taken. Geographical Information System (GIS) plays a vital role to use the latest technologies useful for the decision makers can visualize all the farmlands with their allied information and current situation on one click. The tasks like yield estimation and crop damage assessment done by traditional means take month or two and a whole lot of manpower to complete the work. By using Geospatial technologies, the same task can be completed within half or even in lesser time frame with minimum number of resources and high accuracy. Balancing the inputs and outputs on a crop farm is essential to its success and cost- effectiveness. The capability of GIS to study and envisage agricultural environments and workflows has proved to be favourable to those involved in the farming industry. While natural inputs in farming cannot be measured but, can be better understood and managed with Geospatial applications such as crop yield estimates, soil amendment analysis, erosion identification and remediation. The National Conference on Geospatial Technologies in Agriculture (NCGTA-2020) is to focus the attention of national policy makers, academicians in agricultural sector and industry-leaders throughout India on the vast opportunities in the area of Geospatial Applications and develop strategies for harnessing the same in a sustainable manner. The conference will provide a forum for establishment of liaison and intellectual co-operation between key stakeholders for development of sustainable practices in appropriate use of agriculture sector.
i In this context, the NCGTA-2020 to be held at NAARM, Hyderabad is being organized by Association for Management of Agricultural Research and Agripreneurship (AMARA) in collaboration with NAARM during 20 -21st February, 2020, with its theme will enrich the knowledge for the conservation of agricultural resources. I am sure that this conference will bring new ideas and information and latest developments for the benefit of the researchers and farming community.
I wish all success for the conference
(Ch. Srinivasa Rao), Director, NAARM & President, AMARA
ii MESSAGE Today Geographical Information System (GIS) in agriculture helps farmers to achieve increased production and reduced costs by enabling better management of land resources. The risk of marginalization and vulnerability of small and marginal farmers, who constitute about 85% of farmers globally, also gets reduced. Agriculture using Geospatial Technologies enable the farmers to map and project current and future fluctuations in precipitation, temperature, crop output etc. Agricultural mapping is day by day becoming crucial for monitoring and management of soil and irrigation of farmlands. It is facilitating agricultural development and rural development. Accurate mapping of geographic and geologic features of farmlands is enabling scientists and farmers to create more effective and efficient farming techniques. As farmers are able to take more corrective actions in the form of better utilization of fertilizers, treating pest and weed infestations, protecting the natural resources etc., we are bestowed with more and higher quality food production
In the light of the global focus on GIS technology applications in agriculture, it is very timely and appropriate that Association for Management of Agricultural Research and Agripreneurship (AMARA) and ICAR-NAARM organizing a National Conference on Geospatial Technologies in Agriculture (NCGTA-2020) during 20 -21 February, 2020.
I hope the conference would provide a platform to deliberate on the issues confronting the agricultural biodiversity and evolve innovative approaches for their conservation and utilization.
I wish the National conference grand success
(S.K. Soam) Joint Director, NAARM & Vice President, AMARA
iii
iv Preface
The agricultural sector is the mainstay of the rural Indian economy around which socio-economic privileges and deprivations revolve, and any change in its structure is likely to have a corresponding impact on the existing pattern of social equality. No strategy of economic reform can succeed without sustained and broad-based agricultural development, which is critical for raising living standards, alleviating poverty, assuring food security, generating a buoyant market for expansion of industry and services and making a substantial contribution to the national economic growth. Sustainable agricultural production depends on the judicious use of natural resources (soil, water, livestock, plant genetic, fisheries, forest, climate, rainfall, and topography) in an acceptable technology management under the prevailing socio-economic infrastructure. Geospatial Technology plays an important role in the rapid economic growth and social transformation in developing countries. The future growth in agriculture must come from new technologies which are not only cost-effective but also in conformity with natural climatic regime of the country; technologies relevant to rain-fed areas specifically; continued genetic improvements for better seeds and yields; data improvements for better research, better results, and sustainable planning; bridging the gap between knowledge and practice; and judicious land use resource surveys, efficient management practices and sustainable use of natural resources. The National Conference on Geospatial Technologies in Agriculture (NCGTA-2020) is being organized to provide a central issue in agricultural development is the necessity to increase productivity, employment, and income of poor segments of the agricultural population, and by applying GIS in agriculture, this situation can be addressed. GIS tools and online web resources are helping farmers to conduct crop forecasting and manage their agriculture production by utilizing multispectral imagery collected by satellites. The ability of GIS to analyse and visualize agricultural environments and workflows has proven to be very beneficial to those involved in the farming industry.
v GIS has the capability to analyse soil data and determine which crops should be planted where and how to maintain soil nutrition so that the plants are best benefitted. We are delighted to bring this conference book of abstracts, this souvenir covers the plenary lectures, lead papers and invited lectures in different sessions. A total of 110 abstracts received for presentation are accommodated under different sessions, keeping in view the overall theme of the conference. The NCGTA-2020 organizing committee is thankful to all the contributors who have shared their findings, knowledge and ideas through this publication for the benefit of the farmers and the scientific community. We take this opportunity to place on record our profuse indebtedness to ICAR, and NAARM their sponsorship and all the help and cooperation extended for bringing out this publication.
Editors
vi Contents
Sl.No. Title Page No. 1. Mapping and spatial analysis for plant genetic resources management 1-2 M. Elangovan 2. Geo-spatial technologies as a tool to generate quality agromet advisories for managing climate related crop production risks in 3-4 Telangana G. Sreenivas, B. BalajiNaik and R. Sudhakar 3. Health assessment of citrus orchards in central India using remote sensing Based vegetation indices 5-7 P. Vijaya Lakshmi, Jugal Kishore Mani, Ashish Srivastava, K. Srinivas and A. O. Varghese 4. Estimating land surface temperature from satellite data B. Sailaja, S. Gayathri, D. Subrahmanyam, P. 7-8 Raghuveer Rao, S.R.Voleti and R. Nagarjuna Kumar 5. Spatial estimation of methane emission using remote sensing and DNDC model in major rice growing areas of Tamil Nadu 9-10 N.S. Sudarmanian, S. Pazhanivelan, and Ragunath Kaliaperumal 6. Groundnut area mapping using Sentinel-2 and Sentinel-1(VH and VV polarization) satellite data 11-12 P. Siva Sneha Jyothi, S. Rama Subramoniam, A. Karthik Kumar, K. Padma Kumari and K.Ganesha Raj
vii 7. Assessment of grasshopper damage on maize using high resolution satellite data 13-14 M. Prabhakar, G. Srasvan Kumar, U. Sai Sravan and M. Thirupathi 8. Integrating time-series SAR data and crop growth model in rice area mapping and yield estimation for crop insurances 15-16 S. Pazhanivelan, N.S. Sudarmanian and M. Venaktesan 9. Reservoir modeling using geo-spatial technology for fisheries management 17-18 V. Radhakrishnan Nair, P. Pravin, M. Baiju, K.V. Kumar and N.H. Rao 10 Remote sensing and global position system studies in coastal zone management – A new perspective 19-20 Narshivudu Daggula, M. Shiva Kumar, M.T. Lakshmipathi, A.T. RamachandraNaik, H.S. Praveen Josh and R. Mahesh Kumar 11. Integration of GIS and multicriteria decision analysis for aquaculture development in East Sikkim 20-21 Parvaiz Ahmad Ganie , Deepjyoti Baruah, Kishor Kunal, Ravindra Posti, Amit Saxena, Prem Kumar and Debajit Sarma 12. Digital elevation model extraction for springshed management: a study in middle Himalaya of Uttarakhand 22-23 Utkarsh Kumar, Sher Singh, J.K. Bisht and A. Pattanayak 13. Identification of ground water recharge potential zone of Mann river basin using GIS and remote sensing 23-24 Kishor Gharde, Nikunj Mal, G.U. Satpute, Y. Bisen and M.B. Nagdeve
viii 14. Flood mapping of agricultural area using remote sensing technology – Optical and SAR Images 25-26 Aruna Balla, Prashant Bagade, M. Bhaskar, and Nalin Rawal 15. Uses of geospatial technologies in Inland fisheries sector of India 26-28 Basanta Kumar Das and Sanjeev Kumar Sahu 16. Application of GIS for planning water management strategies to enhance farmers income 29-30 R. Rejani, K.V. Rao, D. Kalyana Srinivas, K. Sammi Reddy, G.R. Chary, K.A. Gopinath and M. Osman 17. Determining hot spots of female agriculture workers in eastern India using geospatial tools 30-32 Anil Kumar 18. Spatial and temporal variability analysis of soil moisture in jute growing areas of West Bengal using 0.5° × 0.5° gridded data 33-35 D. Barman, Tania Bhowmick, R. Saha and Sikhasri Das 19. Monitoring crop lands using satellite imagery and machine learning Murali Krishna Gumma, Prasad S 35-37 Thenkabail, Pardhasaradhi Teluguntla, Bhavani Pinjarla, Kimeera Tummala, Pranay Panjala and Anthony Whitbread 20. Application of machine learning technique for identification of salt-affected soils using 37-38 remote sensing Alka Rani and Nirmal Kumar
ix 21. Advisory services for balanced use of fertilizer using web based spatial decision support system 39-40 Tarun Kumar, Anupma Kumari, Nidhi Kumari, D.C. Jhariya, M. S. Kundu and Brajeshshahi 22. Vegetation health monitoring using drone (Unmanned Aerial Vehicle) derived Multispectral 41-42 R. Kumaraperumal, S. Pazhanivelan, Ragunath Kaliaperumal, G.R. Mugilan, S. Manikandan and S. Venkatesan 23. Climate change and spatial variability in land use pattern of Kashmir valley using geo-spatial technology: A case study of district Ganderbal 42-43 F.A. Lone, Nayar A. Kirmani, Ikhlaq A. Mir and Abid. M. Baba 24. Geospatial web portal and cloud computing: Effective tool to empower stakeholders in agricultural domain 44-46 Rajesh Solomon Paul, Saurabh Upadhayaya, Pradeep Sharma and Aditi Pandey 25. Habitat risk assessment due to climate change along the coast of Odisha using InVest model G. Gopinath, M. Iyyappan, S.K. Dash, S. 46-48 Sujith Kumar, G. Vivek, R. Karthikaa and Tune Usha 26. Impact and damage assessment for tropical cyclone using Sentinel- 1A SAR data and geospatial techniques 48-49 M. Iyyappan, S.K. Dash, G. Gopinath, R. Karthikaa1, G. Vivek and Tune Usha 27. Emerging Geoportal technologies for innovative geospatial applications towards geosmart agricultural planning 50-51 G.P. Obi Reddy, Nirmal Kumar, S. Chattaraj,R. Srivastava and P. Chandran
x 28. Time series Satellite data for identification and mapping of degraded lands 52-53 Nirmal Kumar, G.P. Obi Reddy 29. Assessment and management of coastal multi- hazard vulnerability along Andhra Pradesh Coast using Remote sensing and GIS 54-55 Technique R. S. Mahendra, P C Mohanty, E. Pattabhi Rama Rao and P A Fransis 30. Thermal stress on coral bleaching and their spectral characteristics around Andaman Island 55-56 P.C. Mohanty, R.S. Mahendra, Sahu, B.K. and E. Pattbhi Ramarao 31. A high sense of urgency for Participatory Geospatial Information and Decision Support Systems (PGI DSS) in Sustainable Natural 57-58 Resources Management using Google Earth Engine Mohammed Hussain 32. Application of geospatial technologies and integrated approaches for doubling farmer’s income in sugarcane based farming system in 59-61 Uttar Pradesh-Policy options L.S. Gangwar, A.D. Pathak and Brahm Prakash 33. Soil nutrients and jute fibre quality mapping using geo-spatial technology: A case study of Karimpur-I block of Nadia district of West 62-63 Bengal B. Saha, Koushik Manna, and Saptarshi Sarkar 34. Uses of geospatial technology in seed spices cultivation 63-64 G. Lal, A.K. Verma, M.K. Vishal and M.D. Meena
xi 35. Developing a framework for computing GHG emission rates for Peri-Urban agriculture in Hyderabad 65-66 Manoj P. Samuel, A. Suresh and P.D. Sreekanth 36. Ecological niche modelling for the potential habitat distribution patterns of the critically 67-68 endangered tree species Madhucainsignis P.E. Rajasekharan and K. Souravi 37. Digital communication for agricultural research management 68-70 M. Elangovan 38. Land evaluation of Bharatnur-3 micro- watershed in north eastern dry zone of Karnataka for sustainable land use planning 71-72 Mahesh kumar, K. Basavaraj, B.M. Chittapur and N.L. Rajesh 39. Genetic analysis of rice genotypes under aerobic conditions 72-73 B. Srinivas, D. Padmaja, T. Kiran Babu, Y. Chandramohan and S. Thippeswamy 40. Geospatial technologies for precise nutrient management in oil palm (Elaeisguineensisjacq.) plantations 74-76 K. Manorama, K. Suresh, R.K. Mathur, B.N. Rao and K. Ramachandrudu 41. Comparative study on nutritional values of fodder produced by using vermiwash and water with hydroponic technique 76-77 M.N. Ambore, A.S. Hembade and P.H. Nandedkar 42. Variability assessment in SOC stocks influenced by land use and cropping systems using geographic information systems 77-79 techniques in Chittoor district of A.P Madaka Madhan Mohan, T.N.V.K.V. Prasad, K.V. Naga Madhuri and P. Ratna Prasad
xii 43. Acreage estimation of kharif rice crop using Sentinel-1 SAR Data Nandepu.V.V.S.S.Teja Subbarao, Jugal 80-82 Kishore Mani, Ashish Shrivastava, K. Srinivas and A.O.Varghese 44. Delineation of potential production zones of soybean using cropgro-soybean model and GIS as tool in Telangana State 82-84 N. Mahesh, G. Sreenivas, P. Leela Rani, Akhilesh Gupta, P.D. Sreekanth, K. Surekha 45. Spatial characterization of long-term agricultural drought in Myanmar using google earth engine 84-85 Bhavani Pinjarla, Murali K. Gumma, P.S. Roy and Anthony M. Whitbread 46. Assessment of vegetation loss during the cyclonic storm fani in Puri and Khordha districts of Odisha using remote sensing and 86-87 GIS N. Sahoo, R. Dalai, A. Rout, D. M. Das and B. C. Sahoo 47. Maize area estimation using multi-temporal features extracted from Sentinel 1A SAR data 87-88 M. Venkatesan, S. Pazhanivelan and N.S. Sudarmanian 48. Mapping banana growing area in Tamil Nadu using SAR data 89-90 A. Karthikkumar, R. Jagadeeshwaran and M. Venkatesan 49. Cotton area estimation using parameterized classification of Sentinel 1A SAR data S. Pazhanivelan, M. Venkatesan, 90-91 S. Thirumeninathan, G. Srinivasan and A. Karthikkumar
xiii 50. Evaluation of sugarcane crop area distribution under sugar mills in Villupuram and Cuddalore 92-93 Kumaraperumal Ramalingam, S. Pazhanivelan and S. Nithya Remote sensing in weed management 51. 94-95 N. Varsha and Lavanya 52. Smart agriculture based on internet of things (IoT): Friendly Fields 96-97 M. Shanmukhi, P. Mukesh and K. Harinath 53. Use of GIS for potential production estimation in selected beels of Assam Manisha Bhor, Sanjeev Kumar Sahu, B.K. 97-98 Bhattacharya, Simanku Borah, Taniya Kayal and Basant Kumar Das 54. Applications of microwave remote sensing in agricultural crop identification 98-99 V. Srilatha and P. Sowmya 55. Site specific nutrient management as a tool for yield maximization and cost reduction to double the farmers income 100-102 M. Shankaraiah, P. Surendra Babu, M. Chandidni Patnaik and Soniya Purma 56. Temporal image analysis to observe creation of a 'beel' through a geomorphological development in the 102-103 course of river Hooghly Sanjeev Kumar Sahu, ManishaBhor and Basanta Kumar Das 57. GIS tools for combating climate change through precision and sustainable agriculture S. Rakesh, S. Kundu, G. Somashekar, 103-105 G. Ranjith Kumar, R. Manasa and Ch. Srinivasa Rao
xiv 58. Identification of groundwater recharge potential zones in Hyderabad using remote sensing and GIS 106-107 V. Anuragh, D. Doneshwari, K. Veerendra Gopi and T. Srinivasa Rao 59. Dynamics of Evapotranspiration in an Irrigation Command Area using SEBAL Model for Planning of Water Resources 108-109 K. Krupavathi, M. Raghu Babu, A.Mani, P.R.K.Prasad and L. Edukondalu 60. Assessment of soil erosion risk and watershed prioritisation in the upper 110-111 Subarnarekha basin using SWAT model Chinmaya Panda, D. M. Das and B. C. Sahoo 61. Soil fertility mapping of Brahmanakotkur watershed in Kurnool district of Andhra Pradesh 112-113 S. Satish, K.V. Ramana, M.V.S. Naidu, G. Prabhakara Reddy and P. Sudhakar 62. DSS for estimating water requirements of grape and pomegranate crops R. Nagarjuna Kumar, V. S. Rathore, K. 113-115 Srinivas Reddy, M. S. Nathawat, C.A. Rama Rao, K. Sammi Reddy , G. Ravindra Chary and B. Sailaja 63. Effect of stage wise irrigation schedule on yield and quality of thompson seedless grown on dogridge rootstock 116-117 D. Vijaya, Jagdev Sharma, A.K. Upadhyay and Ram Reddy Prakash Patil 64. Assessing the supplementary irrigation for improving productivity of cole crops using 117-118 SWAT model J. Padhiary and D. M. Das 65 Applications of Geospatial Technologies in Soil and Water Conservation Engineering- A 119-120 critical review S. S. Salunkhe, B. L. Ayare and H. N. Bhange
xv 66. Use of remote sensing and geographical information system in water resources planning and management -A critical review 120-121 Dara Rooha Blessy, Suvarna Kale and B.L. Ayare 67. Planning and designing of watershed using remote sensing and geographic information system 122-123 Suvarna Sunil Kale, Dara Rooha Blessy and B. L. Ayare 68. Deficit water management practices influence on yield, water use efficiency, and consumptive use of rabi maize (Zea mays L.) 124-125 N. Ramya, N.V. Lakshmi, K. Chandrasekhar and K.L. Narasimha Rao 69. Comparative assessment of water quality parameters in aquaculture grow-out using conventional methods and real time sensors 126-127 Ajay Adarsh Rao Manupati, Tapas Paul, Rajesh Kumar Dash and S.M. Raffi 70. Rainfall runoff analysis by advanced hydrological system and artificial neural network 127-128 Nidhi Kumari, P. Singh, M. S. Kundu and B. Shahi 71. Estimation of runoff from Kunaji micro watershed, western ghats by using soil conservation service curve number method along with remote sensing and geographical 129-130 information system tools K. M. Madhu, S. S. Shirahatti and M. S. Shirahatti 72. Mapping and monitoring of water spread area in PWD tanks of Tamil Nadu using remote sensing data 131-132 M. Venkatesan, S. Pazhanivelan and Ragunathkaliaperumal
xvi 73. Effect of macro and micro nutrients on growth, yield and economics of linseed (Linum usitatissimum) under irrigated 132-133 condition B.M. Wakchaure, P.N. Karanjikar and V.G. Takankhar 74. Hydrological modeling of a sub-basin of Mahanadi river basin using SWAT model 134-135 Munish Kumar and Ramesh Verma 75. Comparing SPI and RDI for Parambikulam Aliyar Project basin of Tamil Nadu using DrinC 135-136 V. Guhan, V. Geethalakshmi, K. Senthilraja, P.J. Prajesh and S.P. Ramanathan 76. Applications of thermal remote sensing in agriculture 137-138 D. Anilkumar 77. Role of remote sensing and GIS in water resources management 138-139 B. Soujanya 78. A diagnosis of water table depth and water quality dynamics in the salt affected paddy fields of Bhadra command, Karnataka 140-141 C.N. Nalina, P.K. Basavaraja, T.S. Vageesh and S.S Prakash 79. Geospatial appraisal of Odisha inland water resources 142 ManishaBhor, Sanjeev Kumar Sahu, and Basanta Kumar Das 80. Geospatial appraisal of Bihar inland water resources 143-144 ManishaBhor, Sanjeev Kumar Sahu, Ganesh Chandra and Basanta Kumar Das 81. Identification of erosion-prone areas and prioritization of micro-watersheds: A 144-145 remote sensing and GIS approach V. T. Shinde and M. Singh
xvii 82. Flood inundation modelling in Cauvery basin using HEC-RAS: A case study of T 146-147 Narsipura discharge site Tippu Kareemulla Sharif 83. Role of big data for smart agriculture in India for doubling farmer income 147-148 G. Majeed and Mouneshwari R Kammar 84. Assessment of water yield and reuse options for enhancing cropping Intensity in sub- basin scale using SWAT and linear 149-150 programing technique J. Soren, D.M. Das, B.C. Sahoo and S.K. Raul 85. Study of comparative performance of Wepp and Usle model for prediction of soil loss using remote sensing and GIS 151-152 N. N. Bandgar, B. L. Ayare and H. N. Bhange 86. Advanced smart irrigation system based on GSM and Bluetooth –A case study 153-154 Jilakarra Venkatesh, Killi Srinivas and K. Padma Kumari 87. An ensemble based clustering approach for metagenomics data Anu Sharma, Dipro Sinha, Anil Rai, D.C. 155-156 Mishra, S.B. Lal and Mohammad Samir Farooqi 88. Expert system approach for digital soil mapping of Coimbatore district of Tamil Nadu 156-157 Kumaraperumal Ramalingam, Ragunath kaliaperumal, S. Pazhanivelan and M. Janappriya 89. Cloud computing, web services and portal in geospatial applications TNIAMP Server 158-159 Ragunath Kaliaperumal, S. Pazhanivelan and Kumaraperumal Ramalingam
xviii 90. Spatio-temporal analysis of vegetation variability as a response to agricultural drought aridity 159-160 P.J. Prajesh, Balaji Kannan, Kumaraperumal Ramalingam and S. Pazhanivelan 91. Crop detection using SAR data Manikandan, M. Venkatesan, B. 161-162 Sabarinathan, G. Srinivasan and S. Pazhanivelan 92. Remote sensing based disaster assessment assessing Gaja cyclone damaged areas using drones and satellite imageries 163-164 S. Pazhanivelan, Kumaraperumal Ramalingam, Ragunath Kaliaperumal, G.R. Mugilan and M. Venkatesan 93. Wireless and mobile GIS for agricultural field work TNIAMP – Mobile App 164-165 G.R. Mugilan, Ragunath Kaliaperumal and S. Manikandan 94. Wireless and mobile GIS for agricultural field work mobile App for geotagging crop cutting experiments 166-167 S. Manikandan, P.J. Prajeshand A. Karthik Kumar 95. Delineation of risk zones for cultivation of rainfed cotton crop using remotely sensed data 167-168 Ragunath Kaliaperumal, Balaji kannan, Kumaraperumal Ramalingam and S. Pazhanivelan 96. Impact of climate change on rainfed maize productivity over Tamil Nadu R. Gowtham, V. Geethalakshmi, M. 168-169 Dhasarathan, K. Senthil Raja, A. Senthil and S. Panneerselvam
xix 97. Land evaluation of soils in semiarid region of Tatrakallu village of Anantapuramu district in Andhra Pradesh 170-171 G.Sashikala, M.V.S Naidu, K.V. Ramana, K.V. Nagamadhuri, A. Pratap Kumar Reddy and P. Sudhakar 98. GIS based analytical hierarchy process of evaluation of land suitability of vegetables and flowers for agricultural sustainability 172-173 around thermal power plant Subhas Adak, Kalyan Adhikari and Koushik Brahmachari 99. Spatial and temporal variability in physico- chemical properties of vineyard soil without 174-176 and with application of fertilizers D.Vijaya and G. Ram Reddy 100. Geospatial techniques for studying spatial distribution and spread of cotton mealybug 176-177 M. Prabhakar, M. Thirupathi, Y.G. Prasad and M. Kalpana 101. Evaluation of spatial variability of soil nutrients for drought mitigation in arid zone of deccan plateau of India using geostatistics and GIS 178-179 R. Srinivasan, Rajendra Hegde, S. Srinivas, B. Kalaiselvi, Amar Suputhra and P. Chandran 102. Plant leaf disease detection using deep learning methods 180-181 Minkesh Gupta, Vikash Magar and U. Srinivasulu Reddy 103. Tomato plant diseases recognition using CNN 181-182 Shailam Kumar and U. Srinivasulu Reddy
xx 104. Spatial variability of soil micronutrients in Semi-arid tropics of Tamil Nadu uplands using geo-statistics 183-184 B. Kalaiselvi, S. Dharumarajan, M. Lalitha, R. Srinivasan and Rajendra Hegde 105. Application of remote sensing and geospatial technology in real time monitoring of crop growth, yield estimation and precision agriculture 185-186 Himanshu Kumar, Magan Singh, Sateesh Kumar Karwariya, Sujay Dutta and Sanjeev Kumar 106. Smart agriculture based on IoT use machine learning 187 P. Mukesh, Ms. Nazia Tabassum and M. Shanmukhi 107. Integrated wireless sensor technologies for agriculture crop monitoring 188-189 Mamidi Kiran Kumar and Perumala Mukesh 108. Crop stress monitoring with drones is a new generation technology for Indian agriculture 189-191 B.B. Nayak Internet of things in agriculture 109. 191-193 Shilpa Karat, Anirudh K.C, Dr. Smitha Baby 110. Modelling rainfall patterns in Karnataka using seasonal ARIMA models 194-195 B.S. Yashavanth, M.P. Sharath Kumar and S.K. Soam 111. Image data analytics for estimating the water coverage area in districts of Telangana using machine learning algorithms 196-197 K. Nagendra Babu, P.D. Sreekanth and S.K. Soam 112. Geo-spatial applications in land resource inventory and land use planning- case study 198-200 Sujala of Karnataka
xxi 113. Identification of suitable location for cultivation of medicinal plants in Telangana using geo-spatial tools 200-202 N. Sivaramane, Ranjit Kumar, P.D. Sreekanth and K.V. Kumar 114. GIS based decision support systems for sustainable development of major fruit cops in India 202-203 Sweety Sharma, B. Raghupathi, Rupan Raghuvanshi, B. Padmaja and S. Rakesh 115. GIS and Agricultural Education for Quality Improvement Rupan Raghuvanshi , B. Raghupathi and 204-206 Sweety Sharma 116. Agricultural drought monitoring using SPI and NDVI in mid hills of Uttarakhand: A study in Mid Himalaya of Uttarakhand, India 206-207 Utkarsh Kumar, Sher Singh, J.K. Bisht and A. Pattanayak 117. Application of Cloud Computing and Web Portals in Agricultural Education 208-209 Seema Kujur, K.Akhila and V.V. Sumanth Kumar 118. Geospatial Technology: A Gateway for Precision and Sustainable Agriculture S. Rakesh, B. Raghupathi, S.B. Khade, R. 209-211 Raghuvanshi, S. Sharma, B. Padmaja and R.P. Divakar 119. Application of Geographical Information System in Management of Agrobiodiversity Resources of AP and Telangana 212-213 M.Balakrishnan, S.K. Soam and P.D. Sreekanth
xxii 120. Consumption of Fertilizer Nutrients in Telangana and its Percentage Variation Over Previous Year Pannala Divakar Reddy, Padmaja B. and 214-215 Shrikant Khade
xxiii
Oral Presentations
National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-001 Mapping and Spatial Analysis for Plant Genetic Resources Management
M. Elangovan Principal Scientist, ICAR-Indian Institute of Millets Research Rajendranagar, Hyderabad 500030, Telangana E-mail: [email protected]
Spatial analysis of gene bank collection and characterization data is very important to know the diversity of genetic resources available in the geographic locations. DIVA-GIS 7.5.0 is used to map the location where sorghum germplasm was collected. Analytical maps of sorghum collection were done in grid form for use in developing plans and strategies for future collection and gap analysis. These grid maps include diversity of sorghum germplasm in a specific region indicating the number of numbers of distinct landraces collected and richness of sorghum germplasm in a specific region indicating the number of collections in a specific region. Mapping and spatial analysis of sorghum genetic resources collection at ICAR-Indian Institute of Millets Research (IIMR) was carried out to know the diversity of sorghum in India. During 2000-2018, a total of 1791 acc. of sorghum germplasm are collected/augmented comprising 14 different sorghum growing states in the country. The accessions are collected along with the passport information viz., local name of the accession, village, mandal, state, farmers name, latitude, longitude, altitude, ethnic group, importance of the accession etc., A total of 270 popular
1 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______landraces are collected. Maximum number of accessions are collected from Andhra Pradesh (340 acc.) followed by Madhya Pradesh (245 acc.), Maharashtra (209 acc.), Tamil Nadu (174 acc.) etc., The altitude of collected ranged as 1-1975 m msl. The overlaying of sorghum germplasm collection maps of ICAR-IIMR and ICRISAT also attempted to know the gaps in explored regions. It clearly indicates that ICAR-IIMR’s sorghum explorations were undertaken in the new areas viz., Gujarat (Kutch region), Southern Rajasthan, Southern Uttar Pradesh, Western Madhya Pradesh, most parts of Tamil Nadu. The spatial analysis helps to identify the gaps in germplasm exploration. The maximum diversity of sorghum accessions are collected from central Tamil Nadu, adjoining districts of Karnataka, Maharashtra and Telangana, Araku valley in Andhra Pradesh, Khammam and Adilabad in Telangana, Kutch regions in Gujarat, Malwa regions in Madhya Pradesh, Southern Rajasthan and Bundelkhand regions in Uttar Pradesh and Madhya Pradesh. Maximum local landrace diversity was observed in adjoining districts of Karnataka, Maharashtra and Telangana; Bundelkhand regions in Uttar Pradesh and Madhya Pradesh; and Malwa regions and Central Madhya Pradesh. The richness of accessions (37-45 acc.) was observed in Khammam district in Telangana which is already by identified as a hotspot for sorghum diversity by the other researchers. In some regions the sorghum explorations were repeated after 25-30 years to know the loss of sorghum genetic diversity in the region.
Keywords: Sorghum, Germplasm, Spatial Mapping, Exploration, Gap Analysis
2 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-002 Geo-Spatial Technologies as a Tool to Generate Quality Agromet Advisories for Managing Climate related Crop Production Risksin Telangana
G. Sreenivas*, B. BalajiNaik and R. Sudhakar Agro Climate Research Centre, Agricultural Research Institute Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad *E-mail: [email protected]
Every plant process related with growth, development and yield of a crop and each of in on-season and off-season farm operations in turn all depends on weather. Among the various weather elements, temperatures, radiation and rainfall play major role in deciding the crop growth and yield levels. Precipitation is one of the important weather factors being responsible for soil moisture and therefore has more importance in agriculture, especially under rainfed situation. The State of Telangana is frequently prone to various climate related risks like droughts, excess rainfall leading to floods, heat waves, cold waves etc., The State experiences one or the other extremes during the season affecting the economy of the state. Four rainfed crops (Cotton, maize, soybean and red gram) and one water-intensive crop (rice) are mainly affected owing to these extreme events. Under these circumstances Agro advisories based on medium range forecast given twice a week helping the farming community in minimizing climate risks in
3 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______crop production. The onset and distribution of southwest monsoon rainfall is most crucial for sowing of rainfed crops and their establishment for proper growth, development and yield. Any deviation in the onset and distribution of southwest monsoon rainfall causes huge impact on agriculture and its dependent activities. Generation of quality Agromet advisories in a given Agro climatic zone or at a Mandal level necessitated the detailed analysis of Agro climatic conditions of the zone, like computation of start of sowing season, LGP and mandals frequently prone to drought, cold and heat waves and excess rainfall events etc. and mapping of these weather aberrations using GIS environment helping as a guide for generation of quality Agromet Advisories. Besides Agroclimatic analysis, real time monitoring of Agrometeorological conditions like daily rainfall, occurrence of dry spells, computation of Moisture Adequacy Index (MAI) and Soil Moisture Index (SMI) at mandal level at various phenological stages of major crops grown at mandal level being carried out at ACRC, PJTSAU. Mapping of these agrometeorological conditions are being helped for generation of real time quality Agromet advisories to reduce the impact of adverse weather conditions on crop growth and yield and saving of inputs at farm level and thereby income at farmer level can be enhanced.
Keywords: Geo-Spatial Technologies, Length of the growing period, Moisture Adequacy Index (MAI) and Soil Moisturendex (SMI)
4 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-003 Health Assessment of Citrus Orchards in Central India using Remote Sensing Based Vegetation Indices
P. Vijaya Lakshmi1*, Jugal Kishore Mani2, Ashish Srivastava2, K. Srinivas1 and A. O. Varghese2 1School of Spatial Information & Technology, JNTUK, Kakinada, Andhra Pradesh, India 2 Regional Remote Sensing Centre-Central, ISRO, Amravati Road, Nagpur, Maharashtra, India *E-mail: [email protected] In terms of area under cultivation, citrus is the second largest fruit crop after mango in India and Maharashtra is the largest area under citrus cultivation in India. Even through Maharashtra is having the largest area under citrus cultivation in the country, the production is highest in Telangana followed by Andhra Pradesh, Maharashtra, Madhya Pradesh and Punjab. The disparity between area and production of citrus in Maharashtra needs to be addressed for enhancing the productivity. The present study has been formulated to assess the health of citrus orchards in Central region of India by taking Kalmeswar Tehsil, Nagpur district of Maharashtra as a piolet study site. Vegetation indices such as Normalized Differential Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Atmospherically Resistant Vegetation index (ARVI), Normalized Difference Infrared Index (NDII), Normalized Difference Wetland Vegetation Index (NDWVI) were
5 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______derived and compared to assess the health of citrus crop using Analytic Hierarchy Process (AHP) technique. AHP was used to find the best indices based on evaluation and alternate indices using Pairwise Comparison Matrix (PCM). The relative weights of each of the indices are calculated through the eigenvectors of PCM. The weights are then assessed using the Consistency Ratio (CR).VHI can be derived from Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). VHI ranges from 0 to 100 characterizing changes in vegetation conditions from extremely poor (0) to excellent (100), which is divided into three classes namely, low (0-40), moderate(40-60) and high(60-100). TCI is more sensitive to changes in vegetation density and can be derived from Land Surface Temperature (LST). The use of LST is to monitor water stress in plants which is based upon the relationship between canopy temperature and transpiration. Vegetation Indices and VHI and citrus area were computed using multi-temporal LANDSAT 8 OLI data of 2013, 2016, 2017 and 2018 to assess the health from different perspectives. An area of 3853 ha was found under citrus out of 52138 ha area of total Kalmeswar Tehsil. The citrus area cover around 7.3% of the total area. Maximum and minimum values of ARVI, EVI, NDVI, NDII and NDWVI are observed 0.05-0.51, 0.09-0.60, 0.10-0.64, -0.06- 0.44 and -0.02-0.39 respectively, over citrus area of the study site. The minimum and maximum values of VCI for citrus areafound4.05-86.03, 10.00-79.70, 9.71-79.92, and 11.72-74.71 during 2013, 2016, 2017 and 2018 respectively. The minimum and maximum values of TCI for citrus area observed 50.56-70.84, 33.46-84.50, 33.77-84.44, and 38.25-79.30 during 2013, 2016, 2017 and 2018 respectively. Whereas minimum and maximum
6 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______values of VHI distributed between 30.89-74.32,29.27-73.90, 31.22-74.40 and 28.19-40.96 during 2013, 2016, 2017 and 2018 respectively. The overall vegetation health seems to be varied over the years in the study site. Most of the area under citrus cultivation were found under moderate health conditions. Over the years high range and moderate range of VHI has been decreasing where as low range of VHI is increasing, which indicates that level of stress is being increased.
Keywords: Citrus, Landsat, Vegetation Indices, Consistency Ratio, VHI and Kalmeswar Tehshil.
Abstract # NCGTA-OP-004
Estimating Land Surface Temperature from Satellite Data B. Sailaja1*, S. Gayathri1, D. Subrahmanyam1, P. Raghuveer Rao1 S.R. Voleti1 and R. Nagarjuna Kumar2 1. ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad-30, India 2. ICAR-Central Research Institute for Dry Land Agriculture Santosh Nagar, Hyderabad-59, India *E-mail: [email protected]; [email protected]
Land surface temperature (LST) is an important factor in many areas like climate change, land use/land cover, heat balance studies and also a key input for climate models. Remote sensing has been widely recommended to detect variability in surface
7 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______temperatures. The timing of flowering within the rice crop growing season is largely determined by responses to temperatures and photoperiod. Temperature variations also influence different biotic and abiotic stresses of rice crop. Air temperature varies based on the latitude, composition and elevation of the surface etc. Collecting temperatures at different latitudes and arranging the data is cumbersome. Hence an attempt has been made to estimate Land Surface temperature from satellite images like MODIS and LANDSAT8. Images during flowering period of rice crop in both kharif and rabi seasons were selected. Thermal bands of these images were utilised for computing LST values. Ranga Reddy district from Telangana and West Godavari district from Andhra Pradesh were chosen for this study. Land cover classification is used to define Land Surface Emissivity, which is required for the calculation of LST. The estimated LST values in comparison with temperatures recorded in weather stations indicated that the proposed methodology is capable of estimating accurate LST values, with a correlation coefficient of 0.83. This methodology can be extended further to other districts of India for identifying heat zones to evaluate and recommend heat tolerant rice varieties for improving yield.
Keywords: Rice crop, LST, LSE, Satellite images, Temperature
8 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-005 Spatial Estimation of Methane Emission Using Remote Sensing and DNDC Model in Major Rice Growing Areas of Tamil Nadu N.S. Sudarmanian1*, S. Pazhanivelan2, Ragunath Kaliaperumal3 1Research Scholar, Dept. of ACRC, TNAU, Coimbatore-3. 2Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 3Asst. Professor (SS&AC), Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
A research study on ‘Spatial estimation of methane emission using Remote Sensing and DNDC model in major rice growing areas of Tamil Nadu’ was conducted during rabi 2017 and 2018 (Samba season) to estimate rice area, methane emission and its contribution to methane flux. Multi temporal Sentinel 1A satellite data at VH polarisation with 20 m spatial resolution was acquired between August to January during 2017-18 and 2018-19 at 12 days interval and processed using Maps cape-RICE software to generate Rice area and Start of Season maps. Continuous monitoring was done for ground truth on crop parameters and validation exercise was done for accuracy assessment. Gas samples were collected from thirty fields using static closed chamber and analyzed for field level methane using portable gas analyzer. The rate of methane emission based on IPCC factor ranged from 35.69 to 38.29 and 36.23 to 45.62 kg/ha/season
9 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______during 2017 and 2018 with mean values of 37.13 and 42.10 kg/ha respectively. Whereas LST T factor method recorded methane emission at the rate of 34.80 to 37.50 and 35.52 to 45.15 kg/ha/season during 2017 and 2018 with mean values of 36.05 and 41.44 kg/ha/season respectively. The total methane emission for Cauvery delta zone based on IPCC factor was 19.813 and 20.661 Gg during 2017 and 2018. LST T factor based methane emission was 19.155 and 20.373 Gg whereas DNDC model estimated an emission of 22.69 and 19.86 Gg during 2017 and 2018. Among the methods LST T factor based method recorded the lowest emission rates during both seasons followed by IPCC and DNDC estimated higher values for rate of methane emission. The atmospheric methane flux from GOSAT satellite data ranged from 1.866 to 1.886 ppb during the rice growing season and maximum values were observed during the month of December and October during 2017 and 2018 respectively. The correlation between DNDC based daily methane emission and atmospheric methane flux was found to be positive with R2 values of > 0.52. The higher percent of Agreement between spatially estimated methane emission and observed values indicated the suitability of Remote Sensing based and model driven methods of IPCC Factor, LST T factor and DNDC model in estimation of methane emission for regional or national level GHG monitoring.
Keywords: Methane Emission, DNDC Model, LST, IPCC factor, Cauvery Delta
10 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-006 Groundnut area mapping using Sentinel-2 and Sentinel-1(VH and VV polarization) Satellite data
P. Siva Sneha Jyothi1*, S. Rama Subramoniam2, A. Karthik Kumar3, K. Padma Kumari1 and K. Ganesha Raj¹ 1School of Spatial Information & Technology, JNTU, Kakinada - 533003, Andhra Pradesh, India. 2Regional Remote Sensing Centre (RRSC) –South, NRSC, ISRO, Dept. of Space, ISITE Campus, Bengaluru – 560 037, Karnataka, India. 3Department of Remote Sensing and GIS, Tamil Nadu Agricultural University, Coimbatore. *E-mail: [email protected], [email protected] Groundnut (Arachis hypogaea L.) is one of the most important food and oilseed crop cultivated and consumed in most parts of the world. It is mostly sown in June to July and harvested in October to November in kharif season depending on the varieties, soil and agronomic conditions. The study area is Cheyyar Taluk, Thiruvannamalai district of Tamil Nadu state which is one of the major groundnut producing regions. The associated crops grown in the taluk are Rice, Millets and Pulses cultivated both under irrigated and rain fed conditions. The main objective of the study is mapping and accuracy assessment of Groundnut area
11 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______using multi spectral data (Sentinel-2) and Microwave data (Sentinel-1). Maximum likelihood supervised and unsupervised classifications were applied to optical data from Sentinel-2 to map groundnut crop in the study area. Maximum crop growing stage is considered for classification. Synthetic Aperture Radar (SAR) from Sentinel-1 is used which provide complementary and unique characterizations of vegetation due to its sensitivity to canopy geometry which is unaffected by climate conditions. The backscatter profile of temporal SAR (C band) is generated for Groundnut and associated crops. The variation in backscatter of the order of -9.32 dB and standard deviation of 0.45 is observed in C-band. Multi-date Sentinel-1 SAR data available freely which meets the requirement of VV and VH polarization and decision rule-based classification is performed. Accuracy assessment is done for both optical and microwave data using the ground truth data which is collected for same date as per satellite data acquisition for groundnut and other crops. The classified area obtained for the groundnut crop is 4820 ha for optical data and 4450 ha for microwave data represented reported area is 4092 ha. Results show that the classification accuracy obtained using microwave data is better than the optical data. However, for agricultural regions under frequent cloud cover especially kharif season use of microwave remote sensing for crop monitoring can be reliable. Keywords: Polarization, Microwave Data, Sentinel, Backscattering Coefficient
12 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-007 Assessment of Grasshopper Damage on Maize Using High Resolution Satellite Data M. Prabhakar*, G. Srasvan Kumar, U. Sai Sravan and M. Thirupathi
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad *E-mail: [email protected] Recent outbreaks of short-horned grasshoppers are witnessed in India, though their damage is prevailed in many other countries. Grasshoppers are infamous for their voracity and polyphagy, and can migrate to distant places in quick time. Recently, during September-October, 2019 an acute incidence of grasshopper damage (species yet to be confirmed) was noticed on maize in Siddipet district of Telangana where almost 50-100% crop damage was recorded. Traditionally, the damage assessment is performed with field scouts, which is time consuming and laborious. Remote sensing and geospatial technologies offer timely data to assess the risk of impending pest outbreaks on real- time basis. The study area comprising of 3 villages (Gudikandula, Ghanapur and Govardhanagiri), Thoguta mandal, Siddipet district, Telangana was surveyed. Ground truthing in 40 fields was done for damage assessment, and field position data using Global Positioning System (Trimble GeoXT). The damage incidence was recorded and the incidence was categorized into three grades (healthy, medium and severe). The satellite data sets were acquired from Copernicus Sentinel-2 satellite Level-1C Hub for
13 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______two dates i.e. 27 August, 2019 (pre damage) and 1 October, 2019 (post damage). Different vegetation indices viz., Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI) and Fraction of Vegetation Cover (FCover) derived from the Sentinel- 2 satellite data were used for mapping grasshopper damage in the study area. All the three vegetation indices tested showed significant differences between two dates of satellite data (pre and post damage) in the surveyed fields. Results showed that NDVI value decreased from 0.72 to 0.24, LAI value from 2.53 to 0.57 and Fcover value from 0.70 to 0.32 due to grasshopper damage. These three indices were significant for different severity grades (p=0.001). The study showed the potential use of space-borne remote sensing for assessment of defoliating pest damage and the resultant yield loss. Further, these techniques would enable to develop effective pest management strategies in near future. Keywords: Pest, Space-Borne, Remote Sensing, Vegetation Indices
14 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-008
Integrating time-series SAR data and crop growth model in rice area mapping and yield estimation for crop insurances S. Pazhanivelan1*, N.S. Sudarmanian2, M Venaktesan3 1Professor and Head, Dept. of RS & GIS, TNAU2Research Scholar, Dept. of ACRC, TNAU, Coimbatore 3Senior Research Fellow, Dept. of RS & GIS, TNAU *E-mail: [email protected] Lowland rice in tropical and subtropical regions can be detected precisely and its crop growth can be tracked effectively through Synthetic Aperture Radar (SAR) imagery, especially where cloud cover restricts the use of optical imagery. Parameterised classification with multi-temporal features derived from regularly acquired, C-band, VV and VH polarized Sentinel-1A SAR imagery was used for mapping rice area. A fully automated processing chain in MAPscape-Rice software was used to convert the multi-temporal SAR data into terrain-geocoded σ0 values, which included strip mosaicking, co-registration of images acquired with the same observation geometry and mode, time- series speckle filtering, terrain geocoding, radiometric calibration and normalization. Further Anisotropic non-linear diffusion (ANLD) filtering was done to smoothen homogeneous targets, while enhancing the difference between neighbouring areas. Multi-Temporal Features viz., max, min, mean, max date, min date and span ratio were extracted from VV and VH polarizations to classify rice pixels. Rice detection was based on the analysis of
15 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______temporal signature from SAR backscatter in relation to crop stages. About sixty images across four footprints covering 16 samba (Rabi) rice growing districts of Tamil Nadu, India were obtained between August 2017 and January 2018. In-season site visits were conducted across 280 monitoring locations in the footprints for classification purposes and more than 1665 field observations were made for accuracy assessment. A total rice area of 1.07 million ha was mapped with classification accuracy from 90.3 to 94.2 per cent with Kappa values ranging from 0.81 to 0.88. Using ORYZA2000, a weather driven process based crop growth simulation model developed by IRRI, yield estimates were made by integrating remote sensing products viz., seasonal rice area, start of season and backscatter time series. By generating average backscatter for each time series and dB stack for each SoS, LAI values were estimated. The model has generated rice yield estimate for each hectare which were aggregated at administrative boundary level and compared against CCE yield. Yield Simulation accuracy of more than 86–91% at district level and 82–97% at block level from the study indicates the suitability of these products for policy decisions. SAR products and yield information were used to meet the requirements of PMFBY crop insurance scheme in Tamil Nadu and helped in identifying or invoking prevented/failed sowing in 529 villages and total crop failure in 821 villages. In total 303703 farmers were benefitted by this technology in getting payouts of INR 9.94 billion through crop insurance. The satellite technology as an operational service has helped in getting quicker payouts. Keywords: Rice, Crop yield, SAR, Sentinel 1A, Crop growth model, ORYZA2000, Crop insurance
16 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-009 Reservoir Modeling using Geo-spatial Technology for fisheries management
V. Radhakrishnan Nair1*, P. Pravin3, M.Baiju1, K.V. Kumar2 and N.H. Rao2
1 ICAR-Central Institute of Fisheries Technology, P.O.Matsyapuri, Kochi 2 ICAR-National Academy of Agricultural Research Management, Rajendranagar, Hyderabad, 3 ICAR- Division of Fisheries Science, Krishi Anusandhan Bhawan-II, New Delhi *E-mail: [email protected] Reservoirs are a prominent feature of the hydrology of river systems to impound and store water for public water supply, flood control, irrigation, recreation, hydropower, wildlife habitat and fisheries. Erosion in the catchment area leads to silt deposition in various parts of reservoir which gradually reduces both dead as well as live storages. This poses a threat to the aquatic environment in general and fisheries in particular. Information about the quantity of silt and the consequent reduction in the capacity of the reservoir is necessary for fisheries planning and operation. Sustainable management of fisheries requires information from scientific surveys of the reservoir waterline and base to determine the geomorphological characteristics of its benthic area. In this study, hydrographic survey results are used to assess the physical and bathymetric characteristics of
17 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Malampuzha reservoir located on the Malampuzha river, a tributary of Bharatappuzha reservoir in Kerala and commissioned in 1955. The water storage area of the reservoir is 22.2 sq.km, with its maximum storage of 226 Mm3 and dead storage 2.4 Mm3. A GIS based framework is developed based on hydrographic surveys and 3-D visualization to evaluate the changes in storage characteristics of the reservoir to facilitate sustainable fishery management. The present study estimate the water spread area, a physical characteristic of the reservoir using the 2-D map generated out of GIS tools. The hydrographic survey data collected is used to generate TIN data model for the mapping of bathymetry of the reservoir.
Keywords: Hydrographic survey, Capacity study, TIN, DEM, 3-D view, Contour, Bathymetric map, GIS
18 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-010 Remote Sensing and Global Position System studies in Coastal zone Management -A New perspective
Narshivudu Daggula*, M. Shiva Kumar, M.T. Lakshmipathi, A.T. Ramachandra Naik, H.S. Praveen Josh, R. Mahesh Kumar College of Fisheries, Mangaluru, KVASFSU,Bidar, Karnataka Department of Aquatic Environment Management *E-mail:[email protected]
The coastal zone represents varied and highly productive ecosystems. These ecosystems are under pressure on account of increased anthropogenic activity on the coast. It is necessary to protect these coastal ecosystems to ensure sustainable development. In most of the studies coastal zones are manually digitized from satellite images and calculate the changes using remote sensing technology. GIS and RS technology has been recognized as one of the most dominant tool for quantifying the coastal changes on spatial and temporal scales as it provides the information in digital form, in the present study with the help of Global Position System (GPS) model GARMIN etrex 30, a study carried out from Talapady latitude of 12° 45' 50.3532'' N to Sasihithlu latitude of 13° 02' 14.4288'' N, a total 45.2 hectares of coastal mangrove areas are covered along Dakshina Kannada, coastal dist. of Karnataka and the mangrove of 9 species of8 genera under 5 family total species belong to 4 orders, during the study period the Mangroves reported like viz,
19 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Aegicerascorniculatum, Acanthus ilicifolius, Avicenniaofficinalis, Excoecariaagallocha, Bruguieragymnorhiza, Kandeliacandel, Rhizophoramucronata, Sonneratia alba, andSonneratiacaseolaris.
Keywords: Remote Sensing, GPS system, Coastal zone, Mangroves and GARMINetrex 30
Abstract # NCGTA-OP-011
Integration of GIS and Multicriteria Decision Analysis for Aquaculture Development in East Sikkim
Parvaiz Ahmad Ganie*, Deepjyoti Baruah, KishorKunal, Ravindra Posti, Amit Saxena, Prem Kumar1and Debajit Sarma ICAR-Directorate of Coldwater Fisheries Research, Bhimtal- 263136, Nainital, Uttarakhand 1Indian Council of Agricultural Research, KAB-II, New Delhi-12 *E-mail:[email protected] Study was carried out to identify the potential area for the commencement of sustainable fish farming in East Sikkim with the help of remote sensing and geographical information systems (GIS)based on MultiCriteria Evaluation (MCE) of water, soil and infrastructure database. Quick bird imagery and thematic layers
20 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______were analyzed with ArcGIS v 10.1 and GIS capabilities, and weighted overlay method was adopted to develop a series of GIS models for identifying and prioritizing the appropriate locations for fish farming. The areas delineated were categorized into most suitable for trout culture, moderately suitable for trout culture and suitable for carp. Current land use pattern of the study area (east Sikkim) was extracted from the satellite image (Quick bird) with the help of global positioning system (GPS) data which revealed that about 46 percent of land is available for agriculture and allied activities. Based on the weighted criteria of soil, water and infrastructure quality, availability and accessibility,805 ha (0.86 %) of land was found suitable for aquaculture development of which 104.5ha (0.11%) covering 8 villages falls under most suitable for rainbow trout culture. Around 623.5 ha (0.67 %) covering 47 villages moderately suitable for rainbow trout culture and 77 ha (0.08 %) covering 13 villages was demarcated suitable for carp culture only. Since Sikkim being an entirely mountainous state, agricultural operations face many constraints which result in low yield per unit area for most of the crops. Thus proper site demarcation for aqua cultural operations through GIS can not only result in better stability and functioning of the aqua farms but also strengthen the nutritional and economic status of the farmers thereby uplifting their livelihood security. Keywords: GIS, Aquaculture, Site Selection, Multi Criteria Analysis
21 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-012 Digital Elevation Model (DEM) Extraction for springshed management: A Study in Middle Himalaya of Uttarakhand
Utkarsh Kumar1*, Sher Singh2, J.K. Bisht3, A. Pattanayak4 ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan Almora, Uttarakhand, India *E-mail: [email protected]
Digital Elevation Models (DEMs) are important source of elevation data required for many watershed development works. Contour lines and drainage lines are integral part of springshed management. Moreover, DEMs are often used in Geographic Information Systems (GIS), and form basis for digitally produced relief map. This paper proposes a method of generating DEM by using Google earth elevation data which is open source. In this study elevation data has been extracted for Hawalbagh experimental farm of ICAR-VPKAS Almora, which lies in middle Himalayas using online tool (http://www.zonums.com/gmaps/terrain.php). The output of the extraction process include coordinates (x, y) values (WGS84 projection) including the elevation (z) in meters. These values have been then imported into an excel file for further process in ArcGIS to create DEM The accuracy statistics were computed using the ground point of 42 reference points in the study area. The reference data was collected using GPS mp 76CSx. Accuracy
22 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______assessment of the Google earth derived DEM was reported using root mean square error (RMSE), correlation coefficient (R) and coefficient of determination (R2). The value of R is 0.79, the coefficient of determination (R2) is 0.63 and root mean square error (RMSE) is 11 m. The result showed that the accuracies for the prepared DEM are suitable for hydrological and other water resources modelling. In general Google earth derived DEM can only be used for investigation and preliminary analysis with low initial investment. It is strongly advised that users of Google earth have to test the accuracy of elevation data by comparing with reference data before using it.Based on the results, this study proposes an alternative method in obtaining a DEM data for a wide area which is traditionally time consuming and costly. Keywords: Springshed, Drainage line, Remote Sensing and GIS, Watershed, ArcGIS
Abstract # NCGTA-OP-013 Identification of Ground Water Recharge Potential Zone of Mann River Basin Using GIS and Remote Sensing
Kishor Gharde*, Nikunj Mal, G.U. Satpute, Y. Bisen and M.B. Nagdeve
Dept. of Soil and Water Conservation Engg, Dr. P D K V, Akola *E-mail: [email protected] The ground water of India has been decreasing with a significant rate since last decade. Hence, the present scenario of ground water
23 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______development calls for an urgent step for augmenting ground water resources. The open source Remote sensing and GIS is one of the most advance tool for studying groundwater recharge potential of the particular area of interest. The present study was conducted in Mann river basin is tributary of Tapi river. The total catchment area of the basin was found out to be 2424.43 sq. km with a perimeter of 345.41 km covering partial area of Akola, Buldhana and Washi Districts. The final ground water recharge potential map was prepared by overlaying five thematic maps namely, geology map, slope map, LULC map, drainage density map and soil map using weighted index overlay. The map was divided into four categories i.e. low, moderate, high and very high potential zones. The area under low groundwater recharge potential is found to be nearly 103.8774 sq. Km. The area under moderate groundwater recharge potential was found to be 1855.96 sq. Km. and under high recharge potential was 540.871 sq. Km. The area under very high recharge potential zone was found to be only 15.59 sq. km. Keywords: Mann River, Ground Water Recharge, Remote Sensing, GIS
24 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-014 Flood mapping of agricultural area using remote sensing technology - Optical and SAR Images
Aruna Balla*, Prashant Bagade, M. Bhaskar, and Nalin Rawal National Collateral Management Services Limited, Hyderabad *E-mail: [email protected]
Natural disasters, in recent past, have been causing havoc across the globe to both agricultural and non-agricultural sectors. Global economic losses due to natural disasters stood at about USD 225 billion of which weather-related losses alone account to about 96% during 2018. Floods are the most prominent amongst the weather-related natural disasters and are responsible for significant losses to agricultural crops year-after-year. Globally, India ranked fourth in terms of number of natural disasters during 2005 – 2014 resulting in economic losses of USD 47 billion. India also has the highest number of people, 4.84 million, exposed to risk due to floods. During 2001 – 2012, a total of over 450 lakh hectares of cropped area has been affected by floods. It is important to estimate the damage caused due to floods as precisely and quickly as possible to distribute government compensation, settle insurance claims apart from estimating the production losses. Flood mapping of affected agricultural area is a tedious and time-consuming task using conventional methods. Recent technological advances in remote sensing and GIS. Cloud cover,
25 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______which is present during majority of the flooding season, is a major deterrent to obtain cloud-free satellite images. However, SAR images such as ALOS – PALSAR, RADARSAT 1 and 2, Sentinel 1 etc. can address this problem since their microwaves radar bands are capable of penetrating through the cloud cover to capture cloud-free images. Such obtained SAR images were combined with optical images obtained during cloud-free times and overlaid to generate images. Such images were superimposed with district, tehsil and village boundaries to obtain precise mapping of flooded area down to the village-level. Further, the results were compared against meteorological and field data. Using this method, flood damage at the village level could be precisely determined. Keywords: Flood mapping, Optical and SAR Images, Flood monitoring, Crop loss estimation.
Abstract # NCGTA-OP-015 Uses of geospatial technologies in Inland fisheries sector of India
Basanta Kumar Das* and Sanjeev Kumar Sahu ICAR- Central Inland Fisheries Research Institute Barrackpore *E-mail: [email protected]
India is blessed with huge inland water resources, in the form of perennial and seasonal rivers, estuaries, reservoirs, floodplain wetlands, backwater, lagoon and lakes. The present production of
26 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______11.41 MT comes from inland (65%) and marine (35%) sectors. India is second largest inland fish producer after China. Geospatial Technology is an emerging field of study that includes Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS). Geospatial technology enables us to acquire data that is referenced to the earth and use it for analysis, modelling, simulations and visualization. Geospatial technologies are very much useful in natural resource monitoring and management. Whole of the world are using this technology for monitoring and management. In India various organizations are using Geospatial technology for resource estimation, resource monitoring and management, FMCG supply chain and many more. Fisheries resources, fish habitat identification, waterbodies inventorization and water quality assessment are some areas where remote sensing is being effectively used. ICAR -CIFRI is working from year 2000 in geospatial technology for fisheries resource estimation using Remote Sensing images, algorithms development for water quality assessment and seasonal water area variation. In last two decades ICAR CIFRI had delineated water bodies larger than 5000 m2 in twenty states for two seasons using Indian remote sensing satellite images. Electronic atlas is a tool to disseminate digital maps to the desktop user. Nineteen electronic atlases have been developed to circulate the delineated water area of two seasons to the fisheries department of different states. There are different satellite based remote sensing sensors which can be used to study various water quality parameters like temperature, turbidity, chlorophyll, specific conductivity etc. Various organizations of the world are involved to establish relationship of water quality parameters and various bands of R S sensors.
27 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Region specific studies were conducted by ICAR-CIFRI and establish relationship between water quality parameters developed for temperature, turbidity, salinity, specific conductivity and chlorophyll with IRS P6 LISS III Sensors and Landsat 8 satellite sensors. GIS is a system to present information about the various resources on space in a very effective manner. This is the tool, which enables the resource managers to present their information to the user group. ICAR CIFRI organises various forms of training to use this tool, like winter school / summer school for scientist and faculty, short duration courses for fisheries graduate and post graduate and fisheries professionals of state government and KVKs. Presently many fisheries departments of state governments have started using Geospatial technologies and are trying to use it for various purposes like resource delineation, spatial data management, resource monitoring etc. Keywords: Geospatial Technology, Remote Sensing, Resource Mapping, Water Quality And Electronic Atlas.
28 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-016 Application of GIS for planning water management strategies to enhance farmer’s income
R. Rejani*, K.V. Rao, D. Kalyana Srinivas, K. Sammi Reddy, G.R. Chary, K.A. Gopinath and M. Osman ICAR-Central Research Institute for Dryland Agriculture, Hyderabad, India *Email: [email protected], [email protected]
Farmers income from agricultural lands of semi-arid areas could be enhanced by increasing the productivity of the crops through in-situ moisture conservation by controlling erosion in agriculture lands, proper design of water harvesting structures based on the runoff potential and supplemental irrigation using efficient water application methods, adoption of optimal cropping patterns based on the availability of resources and scheduling of irrigations based on crop water requirements, increasing the support price of the crops etc. In this study, an attempt was made to develop a spatial runoff estimation model for Bastar plateau of Chattisgarh using SCS CN coupled with GIS for determining the location specific runoff potential available for water harvesting and the model was validated using observed data. The runoff was determined spatially and temporally for a period of 63 years (1951-2013). The mean annual rainfall from most of the area runoff varied spatially from 1300 to 1500 mm and runoff ranged from 12.9 to 20% of rainfall. The mean annual runoff was dissolved catchment wise to plan water harvesting structures based on the runoff potential
29 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______available for each catchment. The runoff for the 63 years was divided into periods of 21 years each to find its variability over the years. Mean rainfall showed a decreasing trend over the years but the runoff increased over the years due to high intensity rainfalls occurred in the domain districts. In order to analyze the variability of runoff in different rainfall years, the runoff was estimated for above normal, normal and drought years. Considerable spatial variation in rainfall and runoff was observed during above normal, normal and drought years. Irrigation requirement of predominant crops were also determined spatially and temporally and based on irrigation requirement, surface and groundwater availability during above normal, normal and drought years, the optimal cropping patterns needs to be planned for enhancing the farmer’s income from agricultural lands. Keywords: Farmers Income, In-situ Moisture Conservation, Optimal Cropping Pattern, Runoff Potential, Water Harvesting Structures
Abstract # NCGTA-OP-017 Determining hot spots of female agriculture workers
in eastern India using geospatial tools
Anil Kumar*
ICAR-Central Institute for Women in Agriculture, Bhubaneswar *E-mail: [email protected]
Use of geospatial technologies in social science research goes beyond the simple map making exercise by employing spatial statistics to find out the factors, and answer why something is
30 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______happening. Agricultural workforce participation is rapidly undergoing structural transformation because of our migration of male from villages and the consequent feminization of agriculture. The spatial distribution and clustering of female agricultural workers (FAgW) was done in 183 districts of seven eastern states namely, Assam, Bihar, Chhattisgarh, Jharkhand, Odisha, Eastern Uttar Pradesh and West Bengal under the 'bringing green revolution in eastern India' (BGREI) scheme of government of India. District level analysis of FAgW was undertaken using spatial methods to identify significant clusters with high and low FAgW. A set of 14 variables were taken for understanding the relationship among the variables and determining the predictor variables. Three regression models were applied to examine the relationship between the outcome variable and a set of predictors: a) ordinary least square (OLS), b) spatial lag model (SLM) and c) spatial error model (SEM). A correlation matrix was computed in R software to assess the association between the outcome and predictor variables before moving on the OLS and spatial models. GeoDa 1.14 software was used to compute spatial regression models using rook's weight. Bivariate LISA was also employed to assess the spatial interdependence between the outcome variable and a significant and important predictor variable. The basic map making was done in QGIS 3.4 to delineate the location of districts in eastern states and generate shape file for further analysis in GeoDa. The study indicated that most of the variables were highly correlated among themselves, therefore to avoid multicollinearity the variables were narrowed down to four variables. A spatial and spatial models were run to determine the best model. Compared to a spatial OLS model, the spatial error model (SEM) was found to
31 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______be effective and robust model and the indicators gender gap in literacy, percent scheduled tribe population and percent households with monthly income in the range of Rs 5 to 10000 were significant predictors of female agricultural workers in the Eastern states. Clusters with high concentration of female agricultural worker were identified. There were 43 districts with high FAgW which were also surrounded by high FAgW and 4 districts with high FAgW surrounded by low FAgW. Similarly, there were 53 districts with low FAgW surrounded by low FAgW and 2 districts with low FAgW surrounded by high FAgW. The cluster of high FAgW was concentrated in one location along Chhatisgarh-Odisha-Jharkhand border.The low FAgW were located in three distinct locations, in Bihar-UP border (low-1), West Bengal-Odisha (low-2) and West Bengal-Assam (low-3). The study identified clusters of districts for priority intervention for mainstreaming women in agriculture for rapid agricultural development and empowerment of women in agricultural sector. Keywords: BGREI, Eastern India, Female Agricultural Workers, GeoDa, QGIS
32 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-018 Spatial and temporal variability analysis of soil moisture in jute growing areas of West Bengal using 0.5° × 0.5° gridded data
D. Barman*, Tania Bhowmick, R. Saha & Sikhasri Das
ICAR - Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India *E-mail: [email protected]
Soil moisture plays an important role in plant growth processes such as seed germination, root and shoot growth, root respiration, and water and nutrient uptake by plants. It also influences soil biological processes. Moisture content builds up in soils primarily from rainfall becomes foundation in rainfed agriculture. Soil moisture content has therefore direct correlation with growth and development and ultimately with yield of jute because it is predominantly cultivated in West Bengal as a rainfed crop sown during March-May (pre-monsoon) depending on Nor’wester (locally known as kalbaishakhi) rain, and harvested during July- Aug (monsoon) for extraction of bast-fibre depending on monsoon rain. Q-GIS and R-Studio were used in the present study and non- parametric Mann-Kendall test was applied on NOAA CPC soil moisture gridded data set with spatial resolution of 0.5° x 0.5° to find out positive or negative change in soil moisture over two consecutive 30-year periods (1958-1987 and 1988-2017) and over 60-year period (1958 to 2017) in the jute growing areas of West
33 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Bengal. Sen’s slope was also computed to measure the magnitudes of changes. This analysis will help in water resource planning and management and irrigation scheduling for jute cultivation in West Bengal. Monthly trend analysis over first 30-year (1958-1987) soil moisture data revealed that the soil moisture in March was in decreasing trend in all the districts, but soil moisture in April and in May was in increasing trend in all the districts except in Malda (-0.05 mm/yr) and Dakshin Dinajpore (-0.17 mm/yr) for April and in Alipurduar for May (-0.24 mm/yr). June and July soil moisture was in increasing trend in most of the districts except in Alipurduar (-2.59 mm/yr) and Cooch Behar (-0.90 mm/yr) during June and only in Alipurduar (-1.35 mm/yr) during July. However, the August-soil moisture was in decreasing trend in many districts such as Alipurduar (-1.43 mm/yr), Malda (-0.69 mm/yr), Dakshin Dinajpore (-0.12 mm/yr), Birbhum (-0.45 mm/yr), Cooch Behar (- 0.92 mm/yr) and Murshidabad (-0.88 mm/yr) districts. Monthly trend analysis over second 30-year (1988-2017) revealed that soil moisture in March was in decreasing trend in Howrah (-0.05 mm/yr), South 24-Parganas (-0.26mm/yr) and Purba Medinipore (-0.10) but it was reverse in rest of the districts. Soil moisture in April was in increasing trend in all the districts of West Bengal. In May soil moisture trend was in increasing trend except in Howrah (-0.23 mm/yr), south 24-Parganas (-1.15 mm/yr) and Purba Medinipore (-0.31 mm/yr). In June, soil moisture in Howrah, Hughly, North and South 24-Parganas and Purba Medinipur was in declining trend throughout 30 years period from 1988 to 12017, whereas, it was in increasing trend in Purba Bardhaman, Birbhum and Nadia. Since, last 30 years in July, soil moisture has decreased in Purba Medinipore, in case of other districts soil moisture has
34 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______increased. Soil moisture in August, the harvesting month of jute, was in increasing trend for all the districts of West Bengal. During jute sowing and establish period, the total soil moisture of April+May was in decreasing trend in Howrah, South 24-Parganas and Purba Medinipore districts. But during fibre development and maturity period of jute (Jun-July), soil moisture was in increasing trend in all the districts of West Bengal. Keywords: Spatial and temporal analysis, soil moisture, jute, Q- GIS, R-Studio, West Bengal.
Abstract # NCGTA-OP-019 Monitoring Crop lands using satellite Imagery and Machine Learning
Murali Krishna Gumma*, Prasad S Thenkabail, Pardhasaradhi Teluguntla, Bhavani Pinjarla, Kimeera Tummala, Pranay Panjala and Anthony Whitbread Remote Sensing/GIS Lab, Innovation Systems for the Drylands Program (ISD), ICRISAT, Hyderabad *E-mail:[email protected] Accurate and timely information on the district wise cropland extent is critical for food security monitoring, water management and yield predictions. This information will help stakeholders to monitor the changes taking place between land uses like agricultural lands, fallows of different types (including major crops) and land cover such as forest lands, water bodies and
35 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______wetlands. Land use planning is possible with this type of information. Administrators from the agricultural departments and revenue authorities will need such spatial information at disaggregated administrative levels to disseminate advisories to farmers for timely inputs and crop protection practices. Using available satellite images, land use and land cover areas including major crops and its changes over time can be monitored/generated. Near real time satellite data and advance methods will produce spatial products timely. However, the existing coarse-resolution (>250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, major goal is to develop high spatial resolution (30-m or <30m) baseline cropland extent product of South Asia using Landsat/sentinel-2 satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of imageries correction and feature extraction, ten time-composited satellite sensors bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the 3 time-periods over 12 months (monsoon: Julian days 151-300; winter: Julian days 301-365 plus 1-60; and summer: Julian days 61-150), taking the every 8-day data from Landsat-8 and 7 for the years 2013- 2016, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data- cube was composed for each of the 5 agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out
36 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______reference training data in South Asia. Classification was performed on GEE for each of the 5 AEZs using well-established knowledge-based and RF MLAs. Map accuracies were measured using independent validation ground data. Keywords: GEE, Random Forest, Machine Learning Algorithms,
Abstract # NCGTA-OP-020 Application of machine learning technique for identification of salt-affected soils using remote sensing
Alka Rani1* and Nirmal Kumar2 1ICAR-Indian Institute of Soil Science, Nabibagh, Bhopal – 462038, Madhya Pradesh 2ICAR-NBSSLUP, Nagpur – 440033, Maharashtra *E-mail: [email protected]
Approximately 6.74 million hectares of area is reported to be under salt-affected soils in India. The accurate identification and monitoring of the extent of these salt-affected soils is important for timely decision making and assessing the success of reclamation measures. In this context, remote sensing approach is an inevitable tool for quick and regular monitoring of their area and extent. Conventionally, many unsupervised and supervised classification methods are being used for identification of salt- affected soils using the multi-spectral indices and reflectance in various bands. Nowadays machine learning techniques have proven their applicability in plethora of fields including remote
37 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______sensing. Therefore, in this study, we have used one of the widely used machine learning technique i.e. random forest for identification of salt-affected soils in Unnao district of Uttar Pradesh. Random forest technique is an ensemble learning technique which constructs multiple decision trees based on training datasets and using mode of outputs of individual trees for determining the final class of an object. In this study, an attempt has been made to develop random forest model based on individual bands of the Landsat 8 images and various salinity indices computed using those bands, Digital Elevation Model data, ground water depth data, nearness to canal, and MODIS NDVI 16 days composite data to identify salt affected soils.1680 sample points were taken for training and testing of random forest model of which 599 samples belong to salt-affected soils and remaining 1081 points represented other features. 70% data was used for training and 30% data for testing the random forest model. The trained random forest model was then used for the identification of salt-affected soils in Unnao district. The results were validated with field observations and with high resolution Google Earth data. It was found that the random forest model was able to identify the salt-affected soils in Unnao district with acceptable level of accuracy. The spatial distribution of salt- affected soils also depicted an association with nearness to canal. Thus, it is concluded that random forest method could be used for identification and monitoring of salt-affected soils using remote sensing datasets. Keywords: Salt-Affected Soils, Random Forest, Remote Sensing, Salinity Indices
38 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-021 Advisory services for balanced use of fertilizer using web based spatial Decision support system
Tarun Kumar*1, Anupma Kumari2, D.C. Jhariya3, M. S. Kundu4 and Brajesh shahi5 1,2,4,5 Dr. Rajendra Prasad Central Agricultural University Pusa, Samastipur, Bihar, India 3Department of Applied Geology, National Institute of Technology Raipur-492010, Chhattisgarh, India *E-mail:[email protected]
Balanced use of fertilizer is having the most important role maintain the soil fertility and crop production. Advisory services for balanced use of fertilizer one of the critical farm inputs for any farming activities, of which fertilizer and irrigation information plays an important role in agriculture. If provided in advances, it will help farmers in making decisions and efficient mobilization of farm resources. Across the state of Bihar also collect soil samples, undertake soil analysis and distribute of soil health card amongst the farmers. Soil Health Card provides every farmer soil nutrient status of his land and advise him accordingly on the dosage of fertilizers and essential soil amendments that should be maintained for good soil health. But soil health card farmers properly not utilized, as well as understand for recommendations of fertilizer dose. In present study web-GIS based Spatial Decision Support System (SDSS) developed advisory service for fertility Recommendation dose is the basis for sustainable profitability of the farmers by web application. Using optimal doses of fertilizers and cropping pattern as per the scientific recommendation is the first step towards sustainable
39 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______farming. Different physicochemical and nutrient contents of soil, i.e. pH, electric conductivity, soil organic matter, organic carbon, total nitrogen, phosphorous, potash and boron were assessed by laboratory analysis collected from the different farmer field of Muzaffarpur district of Bihar. These all data sets were used to develop the SDSS. To develop the GIS application, an open source web GIS system based on MapServer such as web GIS server, PostgreSQL, PostGIS, PHP, Apache MapServer and OpenLayer were used for effective dissemination, sharing and management of spatial information to the concerned user. In this study, to develop SDSS, spatial data used as an input, with the help of spatial query, which provide a result shown on map (SDSS), on the bases of spatial query result and as per need suggest provide advisory service for fertilizer as per crop for farmer through mobile application.
Keywords: Fertilizer Recommendations, Soil Health card, WebGIS, Decision Support System, Web Map Service, Geographic Information System
40 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-022 Vegetation Health Monitoring using Drone (Unmanned Aerial Vehicle) derived Multispectral data Kumaraperumal R 1*, Pazhanivelan S 2, Ragunath Kaliaperumal1, Mugilan G R3, Manikandan S3, Venkatesan S3
1Asst. Professor (SS&AC), Dept. of Remote Sensing and GIS, TNAU, Coimbatore 2Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 3Senior Research Fellow, Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
A study was conducted to assess the use of drone derived vegetation indices for monitoring the vegetation health. Flight mission was carried out using the unmanned aerial vehicle (Quad copter drone) with a payload of multispectral sensor in TNAU Wetland farm during 5th of May 2018. The unprocessed multispectral images and the ground truth information were collected from the Department of Remote Sensing and GIS. The multispectral data were processed using the Mica sense software and the different Vegetation indices viz., NDVI, NDVI-Red edge, BNDVI, NGRDI and GNDVI were generated using ArcGIS 10.1 software. From the study it could be concluded that the NDVI and NDVI-rededge index found to be good in discriminating the crop
41 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______health based on greenness and the presence of chlorophyll content. The BNDVI may be used as when no multispectral sensor payload is available and it failed to differentiate the crop with soil. Normalized Green–Red Difference Index is effective in monitoring the crop phenology using temporal stack of drone images and Green Normalized Difference Vegetation Index is good in assessing the crop canopy moisture.
Keywords: Drones, Vegetation Indices, NDVI, NDVI-Rededge, BNDVI, NGRDI and GNDVI
Abstract # NCGTA-OP-023 Climate change and spatial variability in land use pattern of Kashmir valley using geo-spatial technology: A case study of district Ganderbal
F.A. Lone*1, Nayar A. Kirmani2, Ikhlaq A. Mir1, Abid. M. Baba1 1Division of Environmental Sciences, 2Division of Soil Sciences, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Shalimar Campus, Srinagar, Jammu and Kashmir, India-190025 *E-mail: [email protected]
Remote Sensing and Geographical Information System (GIS) plays a pivotal role in assessing land use and land cover, watershed and surface maps of various natural resources. In the present study
42 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______“IRS P6, Linear Imaging Self Scanning (LISS-IV) dataset of Nov- Dec 2017 with a spatial resolution of 5.8 m was used to delineate various natural resources of district Ganderbal Kashmir valley. The study revealed that among the available natural resources snow and glacier occupies an area of 54029 ha (36.39 % of the total area) followed by dense forest 33517 ha (22.9%), agriculture fields 15432 ha (10.5 %), barren land 14625 ha (10.0 %), scrub forest 8393.3 ha (5.7 %), open forest 7173 ha (4.9 %), wetland 2867 ha (2%), builtup 2727 ha (1.9%), mixed plantation 2140 ha (1.5 %), orchards and horticultural plantation 2110 ha (1.4 %),water bodies 1714 ha (1.2 %) and grassland/meadows 1555 ha (1.1 %) respectively. The change detection study was also carried out by comparing it with Landsat ETM satellite dataset of Oct- Nov 2000 which revealed that sectors viz; agriculture, mixed plantation, wetland, water bodies, grassland/meadows shows a decreasing pattern in the last 2 decades. On the other hand orchard/horticulture and built up exhibit an increasing trend. The trends of maximum and minimum temperatures ,precipitation, extreme weather events and other climate change issues of the last 38 years are also discussed.Various \other thematic and supplementary layers were also generated (viz; surface and watershed layers (slope, aspect, shaded relief, contour and drainage maps) which give an insight into the overall on ground scenario. The study shall also provide the essential source of information for planners and decision makers and can be used for environment sustainability and better management practices. Keywords: Land use Land cover, LISS-IV data, Landsat ETM, RS and GIS Technology, change detection.
43 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-024 Geospatial Web Portal and Cloud Computing: Effective Tool to Empower Stakeholders in Agricultural Domain
Rajesh Solomon Paul*, Saurabh Upadhayaya, Pradeep Sharma, Aditi Pandey Excel Geomatics Pvt. Ltd., Noida, India *E-mail: [email protected]
India is a land of agriculture and it is the primary source of livelihood for about 58 per cent of India’s population. The various stakeholders in the field of agriculture such as farmers, importers, exporters, harvester, seed companies, fertilizer companies, agri- insurance companies, aggregator and government can perform better if they can take informed decisions in timely manner. Informed decisions can help not only to perform better but can also help them to save their expenditure by judiciously spending on their resources. Keeping in mind, the importance of right information on right time, Excel Geomatics has developed an effective tool based on cloud computing and WebGIS services to empower stakeholders in Agricultural domain. The `New Generation Software Solution’- Geolytics.AGRO, brings physical and digital worlds together. Geolytics.AGRO is integrated with satellite data, open street map, ERSI map, terrain data and live weather information such as temperature, precipitation, wind speed and air pressure to provide locational and situational awareness to stakeholders. It has the capability to integrate
44 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______different sets of satellite image through their APIs. Once subscribed, satellite images could be made available even on daily basis for any part of the world. Keeping in mind, the requirement of each stakeholder, Geolytics. AGRO comes with cloud computing capabilities where pre-defined algorithms generate thematic maps to visualize the prevailing situation in agricultural fields, on the fly, with just a click of buttons. It’s agile approach allows linking situational intelligence with situational awareness quickly to uncover timely and actionable insights. The dashboard of the software is customized to provide a quick summary of prevailing situations and helps in managing accordingly.
The main features of the Geolytics.AGRO are as follows: The salient features of our intelligent solution are: Satellite Based Weather Manageme Field Survey Weekly Monitoring: Report: nt Module: Module: Reports: • Crop Growth • Temperat • Keep • Location • Project • Crop Health ure Track of Based Field wise • Water Stress • Wind Stage wise • Task • Summari • Nutrient Speed inputs Allocation. zed Stress • Pressure • Manage • Mobile Report • Weeds • Precipitat Financial App based • Harvestin • Temporal ion Expenses Field g Report Change • Production Survey Estimation
Using our WebGIS platform, it is not only possible to get the above data analytics but it is also possible to visualize the change between any two selected image, that too just by a click of a
45 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______button. This platform also provides the provision of interact with the field team by providing the interface to export the points of investigation in CSV format. All these knowledge, once provided to the stakeholders in agriculture, will help them to take informed decision, at appropriate location, and on right time and will create an efficient ecosystem where resources can be optimally utilized while increasing the productivity. The on-line subscription of Geolytics.AGRO provides dashboard showing different analytics of online crop monitoring on weekly/monthly basis with Map Module for real time generation and printing of Maps at different scales. Keywords: Web portal Service, Agricultural Solutions, Satellite based Monitoring, field survey
Abstract # NCGTA-OP-025 Habitat Risk Assessment due to Climate Change along the Coast of Odisha using InVest Model
G. Gopinath*, M. Iyyappan, S.K. Dash, S. Sujith Kumar, G. Vivek, R. Karthikaa, Tune Usha National Centre for Coastal Research, NIOT campus, Pallikarani, Chennai *E-mail: [email protected]
Global climate change and the threat of accelerated sea-level rise exacerbate the already existing high risks of storm surges, severe
46 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______waves and tsunamis in coastal areas. Climate change may not only enhance the most threatening extreme events but also aggravate long-term biogeophysical effects, such as sea-level rise, shoreline erosion, sediment deficits, saltwater intrusion into coastal aquifers and the loss of coastal wetlands. In light of these existing hazards and increasing risks in coastal regions, there is a great need to gain as much insight as possible into the exact nature and extent of possible risk increases related to future climate trends. An integrated approach coupling geospatial tools and InVest models (Coastal Vulnerability and Habitat Risk Assessment) to assess the biophysical vulnerability of Odisha coast due to climate change through potential sea level rise and changing habitat scenarios. The coastal vulnerability index (CVI) for every 1 km of the coastal stretch was calculated for different scenarios (with and without habitats) to identify the highly vulnerable coastal stretches. Based on InVest CVA model it is found that it in the current scenario about 47 percent of the coast line is under vulnerable and highly vulnerable category. By varying the habitat scenario wherein the coastal protection offered by the coastal habitats were removed then the length of the coastline under the above vulnerable category increases to 69 percent. Coastal stretches with high CVI were identified for coastal protection measures which could be either through eco-restoration, eco-conservation (Green options) or eco-engineering (hybrid options). The Habitat risk assessment model was run for large ecosystems and three outputs were developed that emphasize different priorities of coastal stakeholder’s namely current, pro-development and pro- conservation scenarios. The model outputs indicate that in a pro development future, the risk of habitat degradation increased and
47 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______the delivery of ecosystem services decreased. A pro-conservation scenario improves the health of ecosystems but reduced human use of the coastal zone. The findings would helpful in coastal land planning and management and enable decision making which embraces a combination of development and conservation priorities to minimize impacts on coastal and marine ecosystems. Keywords: Coastal Vulnerability, Climate Change, Habitat Risk Assessment
Abstract # NCGTA-OP-026 Impact and Damage Assessment for Tropical cyclone using Sentinel- 1A SAR data and Geospatial techniques M. Iyyappan*, S.K. Dash, G. Gopinath,R. Karthikaa, G. Vivek, Tune Usha National Centre for Coastal Research (NCCR), Ministry of Earth Sciences, Government of India, NIOT campus, Pallikaranai, Chennai *E-mail: [email protected], [email protected]
An increasing frequency and intensity of Tropical Cyclones (TC) due to climate change threatens human communities living the near the coastal areas. The coastal regions of Tamil Nadu is no exception and witness cyclonic storms at periodic intervals including cyclone Gaja which struck Tamil Nadu’s coastal areas
48 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______on 16 November 2018, devastating local agriculture and infrastructure, and destroying thousands of homes. Impact analysis and assessment of damage in the aftermath of the cyclone is crucial to plan recovery and management activities and a geospatial approach using Sentinel-1A SAR data is discussed in this paper. Cyclone Gaja inflicted heavy damage to the coastal vegetation particularly to the coconut plantations, the study is based on a combination of SAR interferometric coherence and intensity correlation techniques to increase the accuracy of the assessment. The results were validated using field data collected immediately after the event. The damage assessment map was generated using weighted overlay analysis ranking method and thematic layers pertaining to metrological and cyclone parameters, population density, land use/land cover, coastal vegetation cover were used to quantify the degree of impact and extensive damage in the coastal areas. The results indicated that Nagapattinam, Thiruvarur, Thanjavur and Pudukottai districts were severely affected by strong wind and rainfall and the areal extent of severely affected areas were about 685, 1150, 1332 and 1530 sq.km, respectively. This methodology would also be useful in future for impact based forecasting which would be highly beneficial for disaster mitigation operations. Keywords: Gaja cyclone, Weighted Overlay Analysis, Sentinel- 1A, Synthetic Aperture Radar
49 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-027 Emerging Geoportal technologies for innovative geospatial applications towards geosmart agricultural planning G.P. Obi Reddy*, Nirmal Kumar1, S. Chattaraj,R. Srivastava and P. Chandran ICAR-National Bureau of Soil Survey & Land Use Planning, Amravati Road, Nagpur-440 033 *E-mail: [email protected]
In the context of climate change, sustainable management of agricultural resources found to be critical especially climate, land and water resources to feed the ever-increasing global population and ensure global food security. Further, optimum utilization and sustainable management of agricultural resources assumes a greater importance in achieving some of the Sustainable Development Goals (SDGs) like no poverty, zero hunger and life on land as proposed by United Nations. The emerging geospatial techniques like remote sensing, GIS and GPS have redefined the agricultural inventory, mapping and generation of geospatial databases on a regular basis for efficient planning, management, monitoring and implementation of agricultural land use plans at different levels. Convergence of these inputs through emerging Web-based information technologies like WebGIS and Geoportals have immense potential in sustainable management of agricultural resources. Web based Geoportal is essentially a master web site, connected to a web server, which contains diversified thematic databases derived from various sources like remote sensing, GIS,
50 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______GPS and field surveys with metadata information about geographic data and services. ICAR-NBSS&LUP developed BHOOMI Geoportal as Web based platform to deploy various thematic services of land and allied resources as Web Map Services and facilitates to visualize, access, query and dissimilate the land resource information. The important Web Map Services of BHOOMI Geoportal encompasses socio-economic status at district and block level, SRTM DEM (30m and 90m) and ALOES DEM (12.5m) of India, mean MODIS NDVI (250m) for kharif season (June-September) of 2000-2018, physiography, sub- physiography and landform units, agro-ecological regions (1992 and 2015), agro-ecological sub-regions (1999) and aridity index (1992 and 2018) of India, benchmark soils, soil series data at states level, soil based services at various scales, soil organic carbon, land degradation, soil loss and land degradation status of India, crop suitability for various crops at national and state level, soil and allied resources for selected aspirational districts of India. BHOOMI Geoportal platform enable the users to visualize various cross-domain applications in land resource management, land degradation assessment and geosmart land use planning in India.
Keywords: Web Map Services, GIS, GPS, BHOOMIGeoportal, DEM, NDVI, Agro-ecological regions
51 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-028 Time series Satellite data for identification and mapping of degraded lands
Nirmal Kumar*, G.P. Obi Reddy ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur
*E-mail: [email protected] Land degradation is recognized as a serious threat to environment. Restoring degraded lands and soils is one of the Sustainable Development Goals (SDGs) of the United Nations Development Programme (UNDP). Given the importance of the problem, many attempts have been made word wide to map the distribution, type and severity of degradation. In India, most of the country level frameworks for land degradation assessments are based on expert opinion and visual interpretation of satellite data and have provided estimates ranging from 47 m ha to 187 m ha. None of the studies in India have considered the crop phenology and productivity as an indicator of land degradation. Further, these approaches are subjective inconsistent and time and cost consuming. These delays in assessments lead to a delayed solutions. A quick, simple, robust, quantitative, cost effective and consistent method has been developed to identify and map degraded lands at regional scale. It utilizes MODIS NDVI (250m) time series data (16 days composite for 18 years) as a proxy indicator of land productivity. Technique is based on the
52 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______assumption that the degraded lands exhibit a consistently low NDVI in the time series. High resolution contextual information from Landsat/ Sentinel 2A MSI data were used for developing the output map on large scale. The data on topography, hydrology, and legacy data were used in the technique to identify the types and severity of degradation. Finally, the method relies on field observations along with other data available in public domain to validate the overall assessment. The simplicity and quantitative nature of method, use of freely available input data, and triangulation methods of validation make it suitable for rapid assessment of land degradation on a national scale. Thus, the framework provides an opportunity for accurate identification of degraded lands with their types and severity, and is relevant for designing national strategies and policies that address land degradation. The robustness of the methodology has been validated through field verifications in different agro-ecological regions of India. Keywords: NDVI, degraded lands, MODIS Data, field Observation, High Resolution Data
53 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-029 Assessment and management of coastal multi- hazard vulnerability along Andhra Pradesh Coast using Remote Sensing and GIS Technique
R. S. Mahendra*, P. C. Mohanty, E. Pattabhi Rama Rao and P.A. Fransis Indian National Centre for Ocean Information Servises (INCOIS), Ministry of Earth Science, Govt of India, Hyderabad
*E-mail: [email protected]
The present study portrait the multi-hazard assessment along the Andhra Pradesh coast based on the long term sea level observation tide gauge data during 1950 to 2018 period. In this study the extreme water level were extracted after removed astronomical tidal factors from observation tide gauge data. This extreme water levels at each tide gauge stations are used to calculate the return period using Gringorten method to project the future reoccurrence of the Extreme event (water level) along the study location. The extent of future Multi hazard zone along the Andhra Pradesh coast were extracted by synthesizing of return period extreme water level with Airborne Lidar Terrain Mapping (ALTM) high resolution topography and shoreline change rate data. In addition to this, the land use and land cover (LULC) data were overlay and assess the impact of hazard zone on the different LULC area. It was observed that the extend of hazard zone along the southern Andhra Pradesh coast showing higher impact then northern part of coast line due to low-lying area at & around Krishna and Godavari deltaic environs. Multi-hazard Vulnerability maps were further reproduced as risk maps with the land use information using Remote sensing and GIS Technique.
54 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______These maps represented here can aid as a critical information during a disaster for the evacuation process. It can also be used as a tool in planning a new facility and future development purpose.
Keywords: Extreme Water level, Return period, Risk, Multi-Hazard Zone, Shoreline Change, Topography
Abstract # NCGTA-OP-030
Thermal stress on coral bleaching and their spectral characteristics around Andaman Island
P.C. Mohanty1*, R.S. Mahendra1, Sahu, B.K2. and E. Pattbhi Ramarao1.
1Indian National Centre for Ocean Information services (INCOIS), Hyderabad-90 2Dept. of Marine Sciences, Berhampur University, India *Email: [email protected]
Corals are diverse shallow marine ecosystems and they play an important role as a habitat for organisms in their environs. therefore, it is important to assess the coral bleaching due to abnormal rise in Sea Surface Temperature (SST). present study is an attempt to quantify the intensity of coral bleaching using Marine Heat Wave (MHW) using AVHRR data based on persisted SST over 90 percentiles in the Andaman environs during March to May, 2010. The In-situ Observation coral bleaching data were
55 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______collected during study period and established the relationship between intensity (Percentage of bleaching) of Coral bleaching with persistence of MHW. In addition to this, assess the spectral behaviors of coral bleaching at different intensity using MODIS Aqua data. In this study we have used the two contracting spectral bands ratio Index (412 & 531 nm of MODIS Aqua) and established the relation between coral bleaching Intensity. The threshold limit of ratio index value 2.8 was established from the present study to confirm the onset of coral bleaching. This study can enhances the capabilities of the operational coral reef monitoring programs and assess the coral bleaching intensity at synoptic level using Remote sensing data. Keywords: Remote Sensing Reflectance, Marine Heat Wave, Thermal stress, Coral bleaching, AVHRR, Modis Aqua
56 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-OP-031 A high sense of urgency for Participatory Geospatial Information and Decision Support Systems (PGI DSS) in Sustainable Natural Resources Management using Google Earth Engine Mohammed Hussain* Professor, Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad
*Email: [email protected] The forest fires in different parts of the world during this year and the associated permanent loss of biodiversity , flora and fauna (particularly empathising with the pain of screamed animals which were injured and died) have to motivate everyone for urgent compassionate action at both individual and collective levels on daily basis for sustainable natural resource management towards prevention of such disasters. Sustainable Natural Resources Management is possible by Participatory Decision- making by all the concerned stakeholders with the available Geospatial and Nonspatial information. Participatory Rural Appraisal (PRA) tools and techniques are required to be used. Global average annual forest cover loss and top fertile soil loss are all well documented. The Google Earth Engine (GEE) is a cloud computing platform designed to store and process huge datasets (at Petabyte scale i.e. Ten to the power of fifteen) for planetary scale environmental data analysis and ultimate decision making. Huge Data sets, Immense Compute Power, Application
57 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Programme Interfaces (APIs) in Java script and Python and Code Editor are the four main components of GEE. Case studies are also available on GEE cloud platform. The journal of Remote sensing (which is an open access journal published by MDPI) has published an Open access special issue on GEE applications. Participatory Geospatial Information and Decision Support Systems (PGI DSS) are required now which use PRA tools and techniques. i) Village Resource and Agro ecological Maps ii)Maps showing Soil Pollution and Water Pollution iii) Validating all the spatial data and maps using GPS ( Global Positioning System) iv)Geo-referencing and Correcting Village maps are some of PRA techniques. On line Courses on Spatial Data Analysis using R and QGIS are useful .Center of Excellence for Geospatial Information Science (CEGIS)of United States Geological Survey is relevant to use the geospatial information for natural resources conservation and management.
Keywords: GEE, PRA, QGIS, API, Natural Recourse Management
58
Poster
Presentations
National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-032 Application of Geospatial Technologies and Integrated Approaches for doubling farmer’s income in sugarcane based farming system in Uttar Pradesh- Policy Options
L.S. Gangwar, A.D. Pathak and Brahm Prakash
ICAR- Indian Institute of Sugarcane Research, Lucknow *E-mail: [email protected], [email protected]
Sugarcane cultivation and its diversified processing has key role in agrarian based Indian economy. There were 3.5 million cane farmers and agricultural labourers engaged in sugarcane cultivation and provides employment to 0.23 million workers in sugar mills in U.P. It has huge potential for bioethanol and power cogeneration to supplement fossil fuel. It provides economic avenues to meet future energy demand. In India, molasses, B heavy molasses are raw material, as government did not permit ethanol production directly from cane juice. Similarly, bagasse used as fuel for power cogeneration by integrated sugar complexes. Geospatial technologies such as GPS, GIS, ICT and remote sensing have numerous applications in cane production, processing and environmental pollution control. These technologies are used for crop varietal planning, survey and forecasting cane supply during sugar season through simulation techniques and econometric models. U.P is a vital sugarcane growing state in India. There were 119 sugar mills produced 12.05
59 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______m t sugar with recovery 10.85 % during sugar season 2017-18. The developmental strategy for cane cultivation and sugar sector was largely persisting to improve productivity and processing efficiency. To achieve specific goals through adoption of innovative technologies such as varieties, quality seed, irrigation and chemicals; infrastructural development and institutional arrangement, government policies, support and programme. However, it did not recognize need to raise farmer’s income and welfare. Therefore, cane farmer’s profitability has not enhanced much with sugarcane production. Economic benefits accrued through sugarcane and sugar production was not mutually shared with the farmers and other stakeholders. An attempt has been made in this study to explore possibilities of doubling farmer’s income in sugarcane based system in U.P. To explore potential of sugarcane sector an initiative has been taken by the ICAR- Indian Institute of Sugarcane Research, Lucknow in Public Private Partnership (PPP) mode by partnering with DSCL Sugar group in command areas of four sugar mills from two districts from U.P. during year 2016-17. Two villages from each mill were identified for complete enumeration with 2028 farm families having 2091 ha cultivable area to measure farmers baseline income and technologies adoption level. To achieve goals of improving farmers income a holistic approach along with sugarcane technological interventions, dairy, poultry, apiculture, micro- entrepreneurship and allied non-farm income activities has been adopted. The baseline survey reveals that the average annual income of marginal, small and large farmers was ` 53,431, `76,346 and `173,168 respectively for year 2015-16. The positive impact of adoption of innovative cane technologies was evident as income
60 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______from sugarcane crop has increase 30-35 % over base year income due to yield improvement and per unit input cost saving during year 2017-18. The productivity gain and cost reduction would be key facts to enhance cane farmer’s income by year 2022. It concludes that state government should take policy decision to address sugar mills and farmers’ problem to enhance per unit profitability for realizing goals of doubling farmer’s income by adoption of cutting edge technologies and entrepreneurship development. The geospatial technologies could play supportive role in solving problems faced by cane farmers. Its optimal use with innovative and conventional technologies could contribute in improving cane productivity, food security; and promote judicious resource use. India has made progress in frontier areas of biotechnology for breeding biotic and abiotic stress resistant varieties, remote sensing and ICT tools. However, its potential is underexploited due to appropriate program and policy issues.
Keywords: Sugarcane, GIS, Former’s Income, ICT, GPS
61 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-033 Soil nutrients and jute fibre quality mapping using Geo-spatial technology: A case study of Karimpur-I block of Nadia District of West Bengal B. Saha, Koushik Manna, and Saptarshi Sarkar
ICAR-National Institute of Natural Fibre Engineering and Technology, 12 Regent Park, Kolkata *E-mail: [email protected]
Physiochemical properties of a soil greatly influence its use and behaviour towards plant growth. Fertility status of soil has high impact on agricultural activities in the Nadia district. The soil with a proper combination of texture, structure, moisture, pH and organic nutrients controls the yield of agricultural crops. Jute is one of major agricultural crop in West Bengal. Jute fibre quality is very much dependant on soil nutrients. A comprehensive soil nutrient status and Jute fibre quality of the Karimpur-I block Nadia District of West Bengal ware investigated during 2018-19.The study was carried out eight gram panchyets of Karimpur-I block. Composite surface soil samples (0-15cm) from Jute field and jute fibre samples were collected with geographical information ( using GPS). Soil samples were analyzed for pH, OC (%) and available N, P, K, Ca. Most of the soils were found to be clayey in texture. Jute fibre quality parameters Strength Fineness and Grade were analyzed. A strong positive correlation between soil fertility parameters and fibre quality parameters were observed. The
62 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______spatial distribution maps of soil nutrients(pH, OC (%), available N, P, K, Ca) and jute fibre quality (fineness, strength, grade) were prepared for decision maker to make easier and more efficient management decisions and maintain the overall improvement of Jute sector.
Keywords: Soilfertility, GPS, GIS, Soil Nutrients Maps, Fibre Quality Maps.
Abstract # NCGTA-PP-034
Uses of Geospatial Technology in Seed Spices Cultivation
G. Lal*, A.K. Verma, M.K. Vishal and M.D. Meena
ICAR-National Research Centre on Seed Spices, Ajmer, Rajasthan--306205 *E-mail: [email protected] Geospatial technology is a vital tool and gaining popularity in agriculture field because it used to indicate the data that has a geographic component to it. Geospatial technology comprises Geographic Information Systems (GIS), Remote Sensing and Global Positioning Systems (GPS). All these technologies assist the user in the collection, analysis and interpretation of spatial data. GIS technology helps to improve the present systems of acquiring and generating data on seed spices. This technology has been used in seed spices to study the spatial change in area, production and productivity. By this study, the potential area in
63 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Jalore, Barmer, Jaisalmer, Jodhpur and Nagaur districts for cumin production and Hadoti region (Kota, Baran and Jhalawar) of Rajasthan and Neemuch, Mandsour and Guna districts in M.P. has been identified. Geospatial technology has proved to be an efficient and effective tool for spatial analysis and management of natural resources in seed spices. The technology has been extended to analyse the soil suitability evaluation in seed spice crops. By the use of GIS it was concluded that most of the potential areas of seed spices falls within the arid and semi-arid parts of India. It also analyses the cropping pattern and crop rotation in seed spice crops. Satellites, drones and manned aircraft are used for remote sensing, which is the gathering of information about the earth’s surface by scanning it from high altitudes. GIS has been successfully used for diversity analysis to locate rich diversity, yield and oil quality attributes. GIS can be effectively used in several areas of plant genetic resource management of seed spices. GPS system has been used in seed spices crops to know the use of information communication technology in seed spices by farmers in western India. The essential oil constituents across cumin growing Agro-Ecological Sub Regions of India have been studied and identified the area for higher oil content. Hence, use of spatial technology could be integrated to enhance the quality seed spice production in India. Keywords: Cropping System, Geospatial Technologies, GIS, Land Use, Remote Sensing, Seed Spices.
64 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-035 Developing a Framework for Computing GHG Emission rates for Peri-Urban Agriculture in Hyderabad
Manoj P. Samuel*1, A Suresh and P.D Sreekanth2 1 ICAR-Central Institute of Fisheries technology, Kochi 2ICAR-National Academy of Agricultural Research Management, Hyderabad *E-mail: [email protected]
Little information is available on the Green House Gas (GHG) emission rates with respect to change in land, water and energy usage in peri-urban agricultural systems. This information is necessary in the changing paradigm of climate smart agriculture with less carbon foot print. The decreasing trends in water availability, agricultural area and productivity, coupled with negative changes in agricultural land use pattern make the agriculture, especially fruit and vegetable cultivation in peri-urban areas of Hyderabad city, highly vulnerable to climatic variations. Hence a study was contemplated to develop a methodological frame work to study the change in land, water and energy use and its impact on GHG emissions and thereby on agricultural production and productivity, with the help of GIS. Two sites where peri-urban agriculture is practiced (Jukal village in RR district and Lingotam village in Nalgonda district) were selected, in consultation with the officials of Department of Agriculture. Data with respect to climate, land use and cropping pattern,
65 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______agriculture production and productivity for the last one decade were collected both on macro and micro scale and analysed. Graphs/charts were generated with respect to changes in rainfall variability, distribution, existing cropping pattern, energy usage, water source, land use and cropping pattern. The change in energy use and extent of change in Green- House- Gas (GHG) emission was also studied using empirical formulae. The variations in GHG emissions and carbon credit in the identified sites were also calculated w.r.to the change in land use and energy usage. Subsequently an accounting framework for GHG emission calculation is developed with graphical interpretations. The developed accounting and modeling framework was utilized to compute the emissions in the identified villages and was found that there is an increase of GHG emissions amounting to 3.27 and 10.45 MT due to change in land use in Jukal and Lingotam village respectively. Similarly, the change in energy use accounted for an increase in emission of 24.76 and 65.82 MT respectively. The developed framework can be utilized for prediction of GHG emission and carbon foot print with respect to climate change and urbanization in peri-urban areas. Keywords: GHG Emissions, Land Use, Water, Energy, Peri- Urban Agriculture, GIS
66 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-036 Ecological Niche Modelling (ENM) for the potential habitat distribution patterns of the critically endangered tree species Madhuca insignis
P.E. Rajasekharan* and K. Souravi Division of Plant Genetic Resources ICAR-Indian Institute of Horticultural Research Bangalore Karnataka *E-mail: [email protected]
MaxEnt Niche Modelling approach links species distribution information built only on identified presence data and it also makes predictions based on this. This method has been used for predicting M.insignis potential distribution information based on known presence. In the case of M.insignis Western Ghats region covering the states of Karnataka, Goa,, Maharashtra and Kerala are the potential places of distribution. Since M.insignis has a very small sample size of distribution the relative contribution of the environmental variables also considered in the model. Sometimes the model leads to over prediction or under predictions, hence shortcomings of the software need to be also taken in to consideration while analysing the predictions. The potential distribution sites predicted by the model have been validated by conducting exploration missions in those areas an three accessible and highly predicted areas were found and newer populations of M.insignis were found with a very few numbers of the plant . This study illustrates the potential of ENM in identifying additional
67 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______populations of rare and endangered species such as M.insignis. this study also helps in land use management around the existing natural populations identifying hotspot regions, newer populations and suitable niches , finally it serve as a good potential tool in conservation and recovery planning of critically endangered plant species such as M.insignis This data utilized to do the re- introduction of this species to nature. Two natural habitats, Nadoli in Hosmata and Kidu in Kukke Subramanya, previously documented and validated niche habitats using ENM; were chosen accordingly for the reintroduction (augmentation). In the Nadoli forest range a total of 150 seedlings of M. insignis seedlings were planted both inland and near the banks of Gundiya River. Keywords: Madhuca insignis. ENM modelling, niche, re- introduction
Abstract # NCGTA-PP-037 Digital Communication for Agricultural Research Management
M. Elangovan
Principal Scientist, ICAR-Indian Institute of Millets Research Rajendranagar, Hyderabad 500030, Telangana E-mail: [email protected]
Digitalization in agricultural research is essential to handle huge data. A mobile based application technology for data collection named Field book is developed by Kansas State University.
68 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______ICAR-IIMR has customized this app as one stop solution for the PGR Management, AICRP trials, other experimental data collection both in the field and lab. This mobile app can reduce manpower and paper sheets; increases accuracy and authenticity of the data. Field book is an open-source Android app used to collect 12 different data types on and off the field. The electronic data collection and management will be essential to save papers- trees-environment. This application can be used to collect field data on exploration/collection of germplasm and characterization of germplasm with appropriate customization of the application. The ICAR-IIMR has customized this app to collect field data on characterization of millets genetic resources viz., Sorghum, Pearl millet, Finger millet, Foxtail millet, Barnyard millet, Little millet, Kodo millet, Proso millet and 35 other crops. We have customized the app for PGR exploration for the first time in the country with zero usage of paper sheets. Field book can be downloaded from Google Play Store on your mobile phones and tablets. The app folder contains nine folders viz., Field export – to store the exported data files; Field import – to store the experimental field book files; Plot data – to store associated data on audio and photos in a sub-folder; Resources - holds the pictures and files that can be helpful when out in the field and is accessible from the main data collection screen; Database - contains the exported backing up the database file; Trait: to store trait/variable files; Updates – to store the update files; Error – to store transcription error files and Archive – to store archive files. Field book import files should, at the least, include three columns: a unique ID, a primary order, and a secondary order. Each entry should be assigned a unique identifier. Twelve different data types can be taken using the trait
69 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______file. They are numeric, categorical, date, percent, rust rating, text, boolean, multi-category, location, counter, photo and audio. Traits can be created by pressing the add trait button at the bottom of the screen. The designed field file can be transferred to the Android device via apps like shareit, dropbox or manually with a USB cable. Collected data can be exported to CSV files. The export dialog allows the user to customize the database or table format of exporting the files. The database can be backed up and transferred between tablets. When exporting the database, two different files are exported: one containing the database, and one containing the user settings when the database was exported. To re-import the database, both files need to be present in the database folder. The location data with latitude and longitude geo-reference information helps the researchers to create a geo-tagging of experimental pictures especially in germplasm exploration, FLD monitoring, online AICRP trial monitoring, technology impact survey, time-series analysis etc. The app can be effectively used in agricultural research management to reduce papers, save time and accurate data collection. These georeference based mobile apps can be useful for the plant scientists to collect the fast disappearing landraces, detecting and advising disease, pest menace and communicate to the scientists by the farmers, periodical monitoring of their field through geo-tagging and get expert advice in cultivation practices, online seed availability at crop institutes, agricultural market information, communicating the famers on contingency crop plans during the adverse weather conditions etc.
Keywords: Digital, Mobile App, Field Book
70 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-038 Land Evaluation of Bharatnur-3 Micro-watershed in North Eastern Dry Zone of Karnataka for Sustainable Land Use Planning Maheshkumar1*, K. Basavaraj*, B. M. Chittapur3 and N.L. Rajesh2 1Dept of Soil Science and Agricultural Chemistry, College of Agriculture, Kalaburagi, UAS, Raichur, India 2Dept of Soil Science and Agricultural Chemistry, College of agriculture, UAS, Raichur India 3 Directorate of Extension, UAS, Raichur 584104, India *E-mail: [email protected]
A study was undertaken to evaluate five soil series belonging to different landforms of Bharatnur-3 micro-watershed of Kalaburagi district in North Eastern Dry Zone (Zone-2) of Karnataka for sustainable land use planning. Five soil series were tentatively identified and mapped into seven mapping units using GIS technique. These mapping units varied from very shallow (<25 cm) to Deep (100-150 cm) in depth, clay in texture, very gently (1-3 %) to gently sloping (3-5 %), moderate erosion and non gravelly (<15 %) in nature. These seven mapping units were grouped into land capability class II and III with limitations of soil characteristics and erosion. Soil-site suitability evaluation for twenty major agricultural and horticultural crops reveled that Nima Hosahalli series was highly suitable (S1) for all crops except jackfruit and cashew. Chimmanboda series (CMBmC2g0) was moderately suitable (S2) with limitation of texture for all
71 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______agricultural crops. Chincholi and Kalgi series were not suitable (N) for growing of agricultural and horticultural crop due to severe limitations of rooting depth, texture and topography.
Keywords: Land Capability Classification, Land Forms, Crop Suitability
Abstract # NCGTA-PP-039 Genetic analysis of Rice Genotypes under aerobic conditions
B. Srinivas*, D. Padmaja, T. Kiran Babu and Y. Chandramohan and Dr. S. Thippeswamy Rice Research Scheme, Regional Agricultural Research Station, Polasa, Jagtial, Telangana, India-505 529 *E-mail: [email protected] Paddy is mostly cultivated as transplanted rice across the world. The situations of depleting water levels day by day triggers alarms for a need to cultivate paddy in aerobic conditions. The water requirement during the crop period under aerobic situation is less compared to anaerobic condition. In aerobic rice, severe occurrence of brown spot and increased weed population are major concern needs to be addressed. Present situations demand suitable genotypes with good yield potential and resistant to major pest and diseases for aerobic cultivation. A set of 20 genotypes were evaluated in aerobic condition in 3 replications during
72 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Kharif, 2016 at Rice Scheme, Regional Agricultural Research Station, Jagtial, Telangana, India to study the correlations, diversity and brown spot resistance. The study revealed that the traits, effective bearing tillers/M2, plant height, panicle length and number of grains per panicle recorded highly significant and positive correlations with grain yield both at phenotypic and genotypic levels indicating the direct selection for these traits in positive direction could improve the yield. Divergence studies revealed, grouping of 20 genotypes in 5 clusters with maximum number of genotypes (12) accommodated in cluster I. Highest inter cluster distance was observed between cluster I and IV followed by cluster III and V, indicating that crossing among the genotypes from these clusters could yield desirable transgressive segregants. Cluster means revealed that, Varalu (cluster III) cloud be used as parent for selecting early maturing genotypes from segregating generations. Similarly, JGL 28833 (Cluster V) and JGL 23834 (Cluster IV) could be a good source for development of fine gain rice varieties. 1000 grain weight contributed maximum (41.05%) towards total divergence, thus present experimental material could be good source for development of varieties with various grain segments under aerobic condition. The incidence of brown spot revealed that the cultures JGL 28833, JGL 28815 and JGL 20777 were found to be moderately resistant to brown spot under filed conditions and these lines would be useful in disease resistant breeding programme under aerobic conditions. Keywords: Rice Genotypes, Disease Resistant, Clusters,
73 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-040 Geospatial technologies for precise nutrient management in oil palm (Elaeis guineensis jacq.) plantations
K. Manorama*, K. Suresh, R. K. Mathur, B. N. Rao and K. Ramachandrudu
ICAR-Indian Institute of Oil Palm Research, Pedavegi, West Godavari District, Andhra Pradesh *E-mail: [email protected]
Soil test based nutrient recommendations are very general and guide for only blanket recommendation without considering the variation within the field at micro level. Geospatial technologies are real advancements in spatially analysing the nutrient status data to develop precise management strategies which help in protecting natural environment by avoiding excessive use of chemicals and aim at providing point specific recommendations. Geostatistical analysis allows examination and understanding of spatial dependency of a soil property through autocorrelation. Oil palm (Elaeis guineensis Jacq.) is an introduced crop to India in 1970s and it is the highest oil yielding perennial crop ever in the world. Its economic life span being 30 years or even more, it requires very careful management of water and nutrients. There are location specific general recommendations of nutrients for this crop based on yield targets and nutrient uptake pattern. However, application of geostatistics is expected to enhance the yield levels
74 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______substantially as it gives way for point specific recommendations through development of interpolation maps. In the present study, 67 soil samples were collected from oil palm growing regions of Krishna District of Andhra Pradesh and were analysed for different soil parameters (viz., pH, electrical conductivity (EC), organic carbon (OC), available phosphorus (P) (Olsen-P), potassium (K) (NH4OAc-K), exchangeable calcium (Ca) (Exch. Ca) and magnesium (Mg) (Exch. Mg), available sulphur (S) (CaCl2-S) and hot water soluble boron (B) (HWB)) using standard analytical procedures. Then the data is subjected to descriptive analysis to find out the variability and then to geostatistical analysis to design best fit models having minimal error for developing prediction maps. Finally, kriging maps could be developed to interpolate the nutrient levels in unsampled areas for designing variable rates for nutrient applications. From the classical descriptive analysis, except pH, no other parameter was found normally distributed. All the other parameters were positively skewed except OC. Among different soil parameters, highest variation was observed in exch. Mg and the lowest in pH. The mean values of soil pH, EC (dS/m), OC (g/kg), Olsen-P (mg/kg), NH4OAc-K (mg/kg), Exch. Ca (mg/kg) , Exch. Mg (mg/kg), CaCl2-S (mg/ kg) and HWB (mg/kg) were 7.32 ± 0.08, 0.25 ± 0.02, 0.87 ± 0.03, 101.47 ± 6.95, 566.14 ± 42.97, 4.72 ± 0.24, 2.46 ± 0.27, 60.86 ± 2.6 and 5.98 ± 0.25 respectively in the surface layer (0-20 cm) of the soil. From descriptive statistics, it was not possible to identify the spatial variability of soil properties at the unsampled sites. Whereas, Geostatistical analysis revealed wider spatial variability in surface soil properties and they had circular, Gaussian, spherical, stable and exponential best fit
75 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______semivariogram models for evaluating dependency. The wide spatial variability of soil properties warrants site specific nutrient management for higher oil palm production. Keywords: Nutrient management, geospatial technologies, best fit models, interpolation
Abstract # NCGTA-PP-041 Comparative Study on Nutritional Values of fodder produced by using Vermiwash and Water with Hydroponic Technique
M.N. Ambore1*, A.S. Hembade2, P.H. Nandedkar3
1Scientist (Veterinary science), Krishi Vigyan Kendra, Pokharni, Nanded, Maharashtra 2Associate Professo & Head, Department of Dairy Science, Yeahwant College, Nanded. 3Associate Prof M.G. College of Agriculture Biotechnology, Pokharni, Nanded, Maharashtra *E-mail: [email protected] The present study was done at Krishi vigyan Kendra, pokharni i.e. production of maize fodder in hydroponic unit and the biochemical analysis estimation was done at M.G. College of Agriculture Biotechnology, pokharni affiliated to V.N.M.K.V. Parbhani. In the study the maize (African tall) fodder was grown in hydroponics plastic tray in green shade net house. Total ten (10)
76 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______trays are used out of which five (5) are grown by spraying only water at an hour interval and another five trays with water mixed with 50ml vermiwash daily. The hydroponics fodder grown with vermiwash has more nutritious than only simple water sprayed fodder. The crude protein in vermiwash sprayed fodder is 0.8mg/ml as compare to control water sprayed was 0.5mg/ml. same like the crude fibre, crude fat , moisture is 13.5%, 3.8%, 80% respectively more as compared to control water sprayed was 13%,3.4%, 78.8% respectively. Also vitamin C (ascorbic acid) was more in vermiwash sprayed fodder than control water sprayed fodder i.e. 134mg/100ml & 126mg/ml respectively which were helpful to increase the immunity of livestock. It was observed that the vermiwash sprayed fodder was nutritious to feed the livestock as compare to routine fodder produced by farmers.
Keywords: Hydroponic, Fodder, Vermiwash and Nutritive Value.
Abstract # NCGTA-PP-042 Variability Assessment in SOC Stocks Influenced by Land Use and Cropping Systems Using Geographic Information Systems (GIS) Techniques in Chittoor District of A.P
Madaka Madhan Mohan*, T.N.V.K.V. Prasad, K.V. Naga Madhuri, and P. Ratna Prasad Regional Agricultural Research Station, Tirupati, ANGRAU. E-mail: [email protected]
77 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______
The soil organic carbon plays an important role in improving soil structure, aggregate stability, water holding capacity, nutrient retention, recycling by enhancing the soil microbial diversity. The organic carbon status of soils is a function of climate, land use and management practices. The present research was conducted to study the organic carbon captured under different land use/ cropping systems in alfisols of Chittoor district located between 120 37’ to 140 08’ N Longitude and 780 03’ to 790 55’ E latitude. The major land use/ cropping system identified in the study area were rice based cropping system, Sugarcane based cropping system, vegetable based cropping system, Groundnut based cropping system, casuarina and eucalyptus plantations, mango orchards, mulberry based cropping system, fodder crops, flower crops, forest land use, fallow land use and waste land etc. For each land use/ cropping system, three bench mark locations were fixed at different directions of the district during preliminary survey. At each location, the surface samples (0-15 cm depth) were collected, labelled and also recorded GPS coordinates. The soil samples air dried processed and pound to 0.2 mm sieve and analyzed the organic carbon content with modified Walkly and Black method. The highest organic carbon content recorded in forest land use (10.0 g kg-1) followed by paddy-tomato (9.9 g kg- 1), mango orchards >15 years (9.2 g kg-1), eucalyptus plantations (9.2 g kg-1) and sugarcane – vegetable (9.0 g kg-1). Whereas, lowest was recorded in current fallows (2.9 g kg-1), rainfed groundnut (2.9 g kg-1)and sugar cane- sugarcane (3.0 g kg-1) cropping systems. Similarly, carbon sequestration potential highest in forest land use (28.2 Mg ha-1) followed by mango
78 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______orchards >15 years age (21.1 Mg ha-1), sugarcane-vegetables (20.4 Mg ha-1) and paddy-tomato (19.9 Mg ha-1) cropping systems. The lowest carbon sequestered is rainfed groundnut (5.0 Mg ha-1) followed by current fallows (7.2Mg ha-1) and sugarcane-sugarcane (9.2 Mg ha-1) cropping systems. The SOC content in each land use/cropping system was mapped using Arc GIS ver.9.3.2 software. The status of organic carbon was Very low (0.2 – 0.4 %) in rainfed groundnut, Current fallows and sugarcane-sugarcane cropping systems; Low (0.4 – 0.6 %) in mulberry, groundnut- groundnut, casuarina plantations, cultivable waste, flower crops, groundnut-tomato/vegetables, paddy-paddy and tomato- vegetables cropping systems; Medium (0.6 – 0.8%) in mango<5 years, sugarcane-paddy, paddy-groundnut and fodder plantations; and High (> 0.8 %) in sugarcane-vegetables, forest land use, paddy-tomato, mango>15 yrs. and eucalyptus plantations. The variation in organic carbon content in soils under different land use and cropping systems is mainly to addition of organic matter through FYM, fallen leaf litter, root biomass production, soil cultivation practices and duration of land cover in a year. Keywords: Geographic Information System, Land Use, Cropping System, Organic Carbon and SOC Stocks
79 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-043 Acreage Estimation of Kharif Rice Crop using Sentinel-1 SAR Data
V.V.S.S. Nandepu Teja Subbarao1*, Jugal Kishore Mani2, Ashish Shrivastava2, K. Srinivas1 and A.O.Varghese2 1School of Spatial Information & Technology, JNTUK, Kakinada, Andhra Pradesh, India 2RRSC, NRSC, ISRO, Amravati Road, Nagpur, Maharashtra *E-mail: [email protected]
Rice is one of the most important food crop in India covering about one-fourth of the total cropped area and India accounts for 21% of the world’s total rice production. Rice is fundamentally a kharif season crop and grown in mainly rain fed areas. India is the second largest producer and consumer of rice in the world. It seems that there is a considerable increase in production, area and yield of rice crop in India. Rice is the second important crop after Jowar in Maharashtra and mainly cultivated in Vidarbha, Konkan and Western region. The total area under rice crop remained stable around 15 lakh hectare and production around 24 lakh tones with 1.7 to 1.9 t/ha productivity during last 15 years. Bhandara is one of the major district for rice production hence called as the ‘RICE BOWL’ of Maharashtra. Temporal monitoring of crop area under cultivation is essential for the sustainable management of agricultural activities on both national and global levels. As a practical and efficient tool, remote sensing is widely used in such applications. The present study is planned to estimate area under
80 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______kharif rice in Bhandara district, Maharashtra. One of the most important drawback of using optical remote sensing in rice acreage estimation is the unavailability of cloud free data during kharif session. Microwave SAR remote sensing has the ability to penetrate through clouds as well as vegetation canopy. So, the present study, multi-temporal Sentinel-1 SAR data with dual polarization (VH and VV) were used for acreage estimation of kharif rice. Sentinel-1 data for Bhandara district were downloaded from the ESA’s Sentinel Scientific Hub. Image pre-processing steps like Radiometric Calibration, Speckle Filtering & Terrain Correction were carried out using SNAP (Sentinel Application Platform) Toolbox to calculate Radar Back-Scatter coefficient (σ0) which is a measure of the reflective strength of a radar target or normalized measure of the radar return from a distributed target. Subsequently the ‘σ0’ data containing VV & VH polarization for kharif season were stacked, mosaiced & clipped for entire Bhandara district. The rice area is extracted using Random Forest (RF) Classification techniques. RF is a classification technique based on generating a large number of decision trees, where each is constructed using a different subset of the training set. These subsets are usually selected by sampling at random and with replacement from the original data set. The decision trees are then used to identify a classification consensus by selecting the most common output. In our study, we classified rice and other land use land cover (LULC) classes by random forest classifier available in SNAP tool. Masking of non-rice area for the study region was carried out and validated rice crop area using the ground observation collected from the field. An area of 176045 ha (47.3%) was found under kharif rice out of 371915 ha area of total
81 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Bhandara district with 86% classification accuracy. The result shows that SAR data can be successfully utilized in acreage estimation of the rice crop during Kharif session in India.
Keywords: Rice, Sentinel-1 SAR, SNAP, LULC, RF Classifier and Bhandara district
Abstract # NCGTA-PP-044 Delineation of Potential Production Zones of Soybean using Cropgro-Soybean Model and GIS-As Tool in Telangana State
N. Mahesh1*, G. Sreenivas2, P. Leela Rani3, Akhilesh Gupta4, P.D. Sreekanth5, K. Surekha6 1Assistant professor, Department of Agronomy, Agricultural College, Jagtial, Telangana 2,3,4,6Professor Jayashankar Telangana State Agricultural University 5ICAR-National Academy of Agricultural Research Management, Hyderabad *Email:[email protected]
Soybean is being mainly grown in black soils of north Telangana districts of Adilabad and Nizamabad. Recently the crop is being grown in small area in black soils of north and south Telangana districts under rainfed conditions. Soybean was considered as potential alternate crop to cotton, as it has multiple beneficial
82 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______effects of improving soil health besides providing vegetable protein to the human beings. In this context an attempt was made to delineate potential mandals for soybean cultivation in Telangana State to make the crop more remunerative to double the farmer income with suitable management practices. Applicability of models can be extended to a much broader spatial scale by combining them with a Geographic Information System (GIS) as it shows the special and temporal variability simultaneously. The calibrated and validated CROPGRO-Soybeanmodel was used to predict the potential and water limited yields of soybean across 584 locations (mandals) of Telangana state. Simulations were carried out using historical weather data (1986-2015). Similarly, different management strategies were also simulated after identifying constraints in low yield potential zones. Simulation results were linked to a Geographic Information System for presentation and to contribute to the identification of hotspots for interventions aimed at yield improvements. Strategies worked for low yield zones (mandals) with different planting dates starting from 15 June to 15 July across the state. Further, applied irrigation at flowering, pod development and combined irrigation at flowering & pod development as another management strategy to reduce the yield gap. The simulated yields revealed that potential non-water limited yield decreased gradually from western parts to eastern parts of Telangana State. The simulated mean potential non-water limited yields of Telangana State was ranged from 2911 kg ha-1 to 3940 kg ha-1 and potential water limited yield varied between 1009 kg ha-1 to 1459 kg ha-1 across different dates of sowing i.e., 15 June to 15 July. Based on strategic analysis, early sowing (15 June) of soybean with strategic irrigation realized
83 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______maximum yield improvement across the state. The mean seed yield of soybean was increased to maximum extent of 169 kg ha-1 with strategic application of irrigation water at flowering and pod development stage across all sowing dates in Telangana. Soybean yield can be improved by giving strategic irrigation at pod development, if only one irrigation is available and application of irrigation water at flowering and pod development is remunerative, if two irrigations are available. Keywords: CROPGRO-Soybean model, GIS, Potential yield, Water limited yield
Abstract # NCGTA-PP-045 Spatial characterization of long-term agricultural drought in Myanmar using Google Earth Engine
Bhavani Pinjarla1*, Murali K. Gumma1*, P.S. Roy1, Anthony M. Whitbread1
1Remote Sensing/GIS Lab, Innovation Systems for the Drylands Program (ISD), International Crop Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad *E-mail: [email protected]
Droughts affect ecosystems, communities, and agrarian economies. More than 75 % of arable land of Mynamar is rainfed and experiences spatial precipitation variability. The region experiences agricultural drought directly impairing farmer’s
84 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______livelihood system. The agricultural drought impacts all the aspects like “economic,” “environmental,” and “social” settings. All of these impacts need to be considered in assessing and planning response system for drought proofing. Satellite remote sensing data has contributed significantly in monitoring drought at global or regional scale and has provided valuable inputs for assessment and monitoring. Google's Earth Engine (GEE) platform (GEE) platform provides very good performance in terms of enabling access to the large volume of remote sensing products on the cloud platform. It has brought in paradigm shift on real-time information processing and dissemination to the stakeholders. The present study uses seasonal MODIS datasets to assess the intra/inter- annual drought related stress Google Earth Engine platform to access long-term satellite and climate data during 2002-2018. We derive integrated agricultural drought index for determining the stress levels in the cropped areas during the assessment period. The MODIS derived indices and parameters viz., Normalized Vegetation Differentiation Index (NDVI), Evapotranspiration (ET) and Leaf Area Index (LAI); and the meteorological data (CHRIPS precipitation) are used as object-based classification in GEE platform. Integration of bio-physical and meteorological anomalies (Deviation of NDVI, LAI, ET and Standardized Precipitation Index (SPI) computed to assess spatial severity of long-term agricultural drought at national level during three cropping seasons. Keywords: GEE, Meteorological Anomalies, MODIS, Agricultural Drought
85 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-046 Assessment of Vegetation loss during the Cyclonic Storm Fani in Puri and Khordha Districts of Odisha, using Remote Sensing and GIS
N. Sahoo*, R. Dalai, A. Rout, D. M. Das and B. C. Sahoo Geo-Spatial Technology Centre, SWCE, CAET, OUAT, Bhubaneswar *E-mail: [email protected]
Tropical cyclone always creates a catastrophic situation on human day-to-day life and also on the natural ecosystem in the coastal belt of India. An extremely severe cyclonic storm “Fani” was one among the strongest tropical cyclones that hit the coastal Odisha on 3rd May 2019 with wind speed varying from 185-250 km/h. Cyclone Fani made its landfall in Puri district of Odisha. The vegetation cover of Puri and Khordha districts was severely damaged by the cyclone. As per the Government of Odisha report, around 55 lakh trees in Puri and 10 lakh trees in Bhubaneswar were damaged by the cyclone. However, this calculation is mostly based on eye estimation. Therefore, in this study, a trial has been made to estimate the vegetation loss using satellite images in a GIS platform. GIS is an advanced technology that has been a great asset in natural resources studies. GIS has the ability to combine a variety of remote sensing data to generate a spatial map of the earth's surface. Normalized Difference Vegetation Index (NDVI) is one of the most popular indexes used for quick identification of the vegetation cover using multispectral remote sensing data. The
86 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______study has been conducted in two most severely affected districts of Odisha i.e., Puri and Khordha. In this study, Landsat 8 image is used for calculation of NDVI using the ArcGIS 10.6.1 package. NDVI is calculated before and after the cyclone to estimate the change in vegetation cover. Multiple ground truthing was done to verify the result.
Keywords: Vegetation, GIS, Remote Sensing, Ground truthing.
Abstract # NCGTA-PP-047 Maize Area Estimation using Multi-Temporal Features extracted from Sentinel 1A SAR Data M. Venkatesan1*, S. Pazhanivelan2, N.S. Sudarmanian3 1Senior Research Fellow, Dept. of Remote Sensing and GIS, TNAU, Coimbatore. 2Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore. 3Research Scholar, Dept. of ACRC, TNAU, Coimbatore. *Email: [email protected]
Maize crop is cultivated nearly 100 million hectares in developing countries. In India, maize is one of the major rainfed crop cultivated primarily in kharif season and its productivity is increasing constantly at national level. In near future, maize could be a major food and cash crop in India. Hence, estimating the maize cultivation area and predicting the yield during the crop growing period will help in important policy decisions. A research
87 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______study was conducted to estimate area of maize in Ariyalur and Perambalur districts of Tamil Nadu, India using multi-temporal features extracted from time-series Sentinel 1A SAR data. Multi- temporal Sentinel 1A GRD data at VV and VH polarizations and SLC products were acquired for the study area at 12 days interval and processed using MAPscape-RICE software. Multi-temporal Sentinel 1A data was used to identify the backscattering dB curve of maize crop. Analysis of temporal signatures of the crop showed minimum values at sowing period and maximum during the tasseling stage which decreased during maturity stage of the crop. The maximum increase in the signature was observed during seedling to vegetative growth period. The signature derived from dB values for maize crop expressed a significant temporal behavior with the range of -21.26 to-13.18 in VH polarization and -14.05 to -6.54 in VV polarization. Considering the accuracy of SAR data to phenological variations of maize growing period, Multi-Temporal Features were extracted from multi-temporal dB images of VV and VH polarization and coherence images. Multi- Temporal Features viz., max, min, mean, max date, min date and span ratio were extracted from VV and VH polarizations of Sentinel 1A GRD and SLC data to classify maize pixels in the study area using parameterized classification approach. Classified maize area in Ariyalur and Perambalur districts were 14236 and 41632 ha respectively with an overall classification accuracy of 91 percent with kappa score 0.82.
Keywords: Maize, SLC, Parameterized Classification, Multi- temporal features.
88 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-048 Mapping banana growing area in Tamil Nadu using SAR data A. Karthik Kumar1*, R. Jagadeeshwaran2, M. Venkatesan1 1Senior Research Fellow, Department of Remote Sensing and GIS, TNAU, Coimatore 2Associate Professor, Crop Management, TNAU, Kudimiyanmalai. *E-mail: [email protected]
Microwave remote sensing images are being widely used for the purpose of crop area mapping in different countries. The SAR (Synthetic Aperture Radar) backscattering mechanism in agricultural studies shows a blend of surface scattering, volume scattering and double bounce that depends upon the properties of plant such as structure of the canopy, di-electric nature of the canopy, canopy density, row orientation as well as the presence of plant moisture. The changes in mechanism of SAR backscattering components are utilized for crop identification studies. In India, Mango, Banana, Citrus and Guava are largely cultivated over a total area of 8.58 lakh hectares. Among these fruit crops, banana is largely cultivated in the states of Tamil Nadu, Maharashtra, Karnataka, Gujarat, Assam and Madhya Pradesh. Since, banana is considered to be very popular fruit for its lower price with higher nutritive values among the living population. Providing an accurate and timely data on banana growing area will be useful for policy decision making and agricultural community. A research study was conducted to map banana growing area in Tamil Nadu
89 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______during 2017-18 using time-series Sentinel 1A SAR data. Using data from VV and VH polarizations of the SAR data, spectral dB curve was generated for banana crop. The mean dB values were ranged from -7.426 to -6.082 dB in VV polarization and -13.459 to -12.209 dB in VH polarization. Multi-temporal features viz.VHmax, VHmin,VHmean,VHmax date,VVmax,VVmin,VVmin date,VVmean were extracted from the time series SAR data and utilized in parameterized classification approach for banana area estimation. Banana area in Karur, Tiruchirappalli and Erode districts of Tamil Nadu estimated using the parameterized classification approach was 18754 hectares with the overall classification accuracy of 86 per cent and kappa index of 0.74.
Keywords: Synthetic Aperture Radar (SAR), Parameterized Classification, Banana, kappa index
Abstract # NCGTA-PP-049 Cotton Area estimation using Parameterized Classification of Sentinel 1A SAR Data S. Pazhanivelan1*, M. Venkatesan2, S. Thirumeninathan3, G. Srinivasan3, A. Karthik Kumar2 1Professor and Head, Dept. of RS and GIS, TNAU, Coimbatore. 2Senior Research Fellow, Dept. of RS & GIS, TNAU, Coimbatore. 3PhD Scholar, Dept of Agronomy, TNAU, Coimbatore. *E-mail: [email protected]
The need for timely and reliable information on crop area and production for strategic decision making by the stakeholders of
90 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______agriculture and the government is well-known. With the global shift in the market economies, reliable agricultural information has gained more importance than ever before. Remote Sensing is presently the only technology that can provide timely and accurate crop inventory information. Since, the optical remote sensing data has limitations especially during monsoon seasons; microwave remote sensing provides cloud free data for near real-time crop monitoring and area estimation. SAR (Synthetic Aperture Radar) has the potential to discriminate objects based on the sensitivity of the radar backscattering to the dielectric properties and geometric structures of the object. Multi-temporal Sentinel 1A SAR data was acquired for 2018-19 cropping season in both VV and VH polarizations and processed. The mean backscattering values for cotton ranged from -10.53 to -7.89 dB and -20.59 to -14.53 dB in VV and VH polarizations respectively. Multi-temporal features were extracted from the time series SAR data and utilized in extraction of cotton area in Perambalur district of Tamil Nadu using parameterized classification approach. Multi-temporal features viz. VHmax, VHmin,VVmax, VVmin,VVmindate, VHmaxdate,VHspanratio and ccmax, extracted from Sentinel 1A data was utilized for the classification and the overall classification approach was found to be 87 per cent.
Keywords: Cotton, Synthetic Aperture Radar (SAR), Polarizations, Multi-temporal
91 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-050 Evaluation of Sugarcane crop area distribution under sugar mills in Villupuram and Cuddalore districts of Tamil Nadu Kumaraperumal Ramalingam1*, S. Pazhanivelan2, S. Nithya3 1Asst. Professor, Dept. of Remote Sensing and GIS, TNAU, Coimbatore-3 2Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore-3. 3Research Scholar, Dept. of Remote Sensing and GIS, TNAU, Coimbatore-3 *E-mail: [email protected] Sugarcane is one of the most important sugar crop cultivated in India. During 2017, India ranked second in terms of sugarcane area and production with 3.2 million ha of crop area, a total of 348.4 million tonnes of productivity which accounted for 14.68% of global sugarcane production. Near real time accurate information on crop area, suitable area for expansion and setting up of processing industries are vital for making policy decisions. Keeping these aspects in view, the present study was conducted to estimate sugarcane area in Villupuram and Cuddalore districts of Tamil Nadu using Sentinel 1A SAR data and the distribution of the area under sugar mills. Time-series Sentinel 1A data for the study area was downloaded and processed using MAPscape software. A significant increase in backscattering coefficients obtained for sugarcane crop was observed from the planting to harvesting period. Parameterized maximum likelihood classification of SAR data was adopted for extracting sugarcane
92 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______crop area. The area estimated was 11849 ha and 30723 ha in Cuddalore and Villupuram districts with the overall accuracy of 85 per cent. Sugarcane crop area distribution under sugar mills was evaluated using Thiessen analysis based on distance between sugarcane cropping area and sugar mills in ArcGIS environment. Dharani Sugars & Chemicals in Villupuram district and ThiruArooran sugars in Cuddalore district were found to have more area (>50%) than the other 8 mill of the study area. This reveals there is higher load on these industries compared to the other in the study area. Hence, there is a possibility to setup additional processing industries in these regions to distribute the coverage of sugarcane area and to reduce the loads of these two particular industries.
Keywords: Sugarcane mapping, Theissen analysis, Sentinel 1A, SAR
93 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-051 Remote Sensing In Weed Management N. Varsha1 and Lavanya2* 1PhD scholar, Department of Agronomy, College of Agriculture, Junargadh, JAU. 2PhD scholar, Department of Agronomy, College of Agriculture, Rajendranagar, PJTSAU *E-mail: [email protected]
Remote sensing is the science and technology of making inferences about material objects from measurements made at a distance without coming into physical contact with the objects under study. Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance (typically from satellite or aircraft). It is useful in field of agriculture for various purposes like Crop acreage estimation, Crop production estimation, Identification of crop pests and diseases, Soil mapping, Tree census, Crop damage estimation, Agriculture zonation, Groundwater prospecting, Monitoring of dynamic characteristics like crop growth, studying climate change, precision farming, building up database on soil, climate, land characteristics, monitoring deforestation, rainfall prediction, weed identification, creation of global soil map, LiDAR for farmers, vegetative analysis, bioprospecting and crop information system (Baruah, 2010). Weeds are the major biological constraint in increasing crop productivity. Among the weeds, insects and pests, highest amount of damage is caused by weeds which is around 34%, while
94 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______18 and 16% by insect and pests respectively (Oerke, 2006).Remote sensing can be used as a tool for detection and mapping of weeds in agricultural crops. ‘Weed mapping’ is used in the sense of all procedures using spatial information on weed distribution. Weed mapping methods include data collection, descriptive and analytical statistics and a graphical interpretation of results. Remote sensing offers a non-invasive method of acquiring a synoptic view of the population of weeds on a ground target. Biological traits that help distinguish weeds from their surroundings and relative amount of weed cover compared to other vegetation are considered in remote sensing for weed mapping. The plant characteristics like flowers and/or bracts, early green-up/senescence or late senescence, plant pubescence, canopy architecture, dicot weeds in grasslands, vegetation inhibiting root exudates, shadowing from tall weeds, growth form(s), fall coloration are used for detection of weeds. While in weed management its essential to study the invasive species and remote sensing plays a major role in detection, mapping and control of various invasive species using different tolls like aerial photography, hyper spectral images etc. remote sensing has a major role in case of precision weed control where the weeds can be detected and control measures can be taken only at the site where the weeds are present. Thus, it plays a significant role in present day agriculture. Keywords: Remote Sensing, LIDAR, Crop Estimation, Weed Management
95 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-052 Smart agriculture based on Internet of things (IoT): Friendly Fields
M. Shanmukhi1*, P. Mukesh2, K. Harinath3 1&3 Department of IT, Mahatma Gandhi Institute of Technology, Gandipet, Hyderabad-500075 2ARIS Cell, ICAR-IIMR, Rajendranagar, Hyderabad-30, *E-mail: [email protected]
Despite the understanding individuals may have relating to the farming procedure, the reality is that today's agriculture industry is data-centered, precise, and smarter than ever before. The fast appearance of the Internet-of-Thing (IoT) based modern technologies upgraded practically every market including "wise agriculture" which relocated the industry from statistical to measurable techniques. Such revolutionary changes are shaking the existing agriculture approaches and developing new chances along a series of challenges. This short article highlights the capacity of wireless sensors as well as IoT in agriculture, along with the challenges expected to be encountered when integrating this modern technology with the typical farming techniques. IoT tools as well as communication methods related to wireless sensors experienced in agriculture applications are examined thoroughly. What sensing units are offered for details agriculture application, like soil preparation, crop standing, irrigation, pest and disease discovery are provided. Just how this innovation aiding the cultivators throughout the crop phases, from sowing
96 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______until harvesting, packaging and also transport is described. Furthermore, the use of unmanned aerial automobiles for plant monitoring and other positive applications such as optimizing plant return is taken into consideration in this short article. Modern IoT-based designs as well as systems utilized in agriculture are likewise highlighted any place suitable. Finally, based on this complete evaluation, we recognize present as well as future fads of IoT in farming as well as emphasize potential research study difficulties. Keywords: Agriculture, IOT, Wireless Sensors, Crop Management
Abstract # NCGTA-PP-053 Use of GIS for potential production estimation in selected beels of Assam
Manisha Bhor, Sanjeev Kumar Sahu*, B. K. Bhattacharya, Simanku Borah, Taniya Kayal and Basant Kumar Das ICAR- Central Inland Fisheries Research Institute Barrackpore *E-mail: [email protected] Assam is a state where beels are a vitally important fishery resource. They are a highly productive ecosystem efficiently converting solar energy to organic carbon when rich nutrients are available from natural sources. When judiciously managed these wetlands endow high and rich benefits to the people of the state. Fish production in these beels are an effective way to reduce the
97 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______gap between demand and supply of fish. Assam Fisheries Development Corporation limited is a State Government company, incorporated on 01 Mar, 1977. At present, there are 185 nos. of beel Fisheries with total area of 12016.48 Ha and total productive water area of 9365.00 Ha is under the management and administrative control of AFDC Ltd. It has near about 20,000 registered S.C Fisherman and near about 2000 registered S.C Fish traders. This study focuses upon a few of these beels and observes how the recorded area and the field area differs for each of them. It is observed that nine of the studied beels have a greater field area compared to recorded data and eight of them have a lesser field area compared to recorded data. The paper endeavours to observe the relation between productivity and the difference in area, between recorded and field data, of these beels. Keywords: Beels Fisheries, Fish Production, GIS, AFDC
Abstract # NCGTA-PP-054 Applications of Microwave Remote Sensing in Agricultural Crop Identification.
V. Srilatha*and P. Sowmya M.SC, Department of Soil Science, College of Agriculture, Rajendranagar-50030, PJTSAU *E-mail: [email protected] Remote sensing studies addressing the monitoring of crop phenology are mainly based on images acquired in the visible and near- infrared wavelengths. The main limitations of remote
98 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______sensing approaches are related to the properties of optical images. (almost unusable in conditions of heavy cloud cover). Microwave remote sensing operates between 1mm-1m wavelength region. Microwaves penetrates through clouds and helps in getting information about Kharif crops. The penetration capacity of microwaves depends on band in which it operates. Different bands likes L-band (23.5cm), C-band (5.8), X- band (3cm) having different depth of penetration capacity. In the microwave domain, studies have demonstrated the application of radar data for crop monitoring, in particular the contribution of the multi-frequency, multi-polarization or multi- incidence aspects. Multiple scattering within a canopy can be useful for discrimination of crop using radar RS. Research using multiple dates of radar data has demonstrated that radar RS could play a very important role in agricultural applications. The synergy associated with data acquired by SAR and optical sensors has led to intensive research activities towards the application of RS technologies. Used together, optical and radar data provide a valuable information source for agricultural applications. Results have been very promising for a wide range of specific applications including crop type identification, crop condition, crop monitoring and crop yield. SAR sensors in the microwave system is nearly independent of weather conditions. The longer wavelength of radio waves enables transmitted signals to penetrate clouds and other atmospheric conditions, which make radar system highly reliable in terms of data provision, especially during periods in which optical sensors fail. Keywords: Microwave Remote Sensing, SAR, Crop monitoring
99 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-055 Site Specific Nutrient Management as a Tool for Yield Maximization and Cost Reduction to Double the Farmers Income
M. Shankaraiah1*, P. Surendra Babu2, M. Chandidni Patnaik3 and Purma Soniya4 1Senior Scientist, 2 Principal Scientist & Univ.Head 3 Principal Scientist 4 Research Associate All India Coordinated Research Project on Micronutrients, PJTSAU, ARI, Rajendranagar, Hyderabad *E-mail: [email protected]
Site Specific Nutrient Management is a component of precision agriculture and can be used for any field or crop. It combines plant nutrient requirements at each growth stage and the soils ability to supply those nutrients and applies that information to areas within a field that require different management from the field average and it allows for fine tuning crop management system along with right source, rate, time and place of nutrient usage by improving fertilizer use efficiency over blanket and soil test based fertilizer recommendations to get attainable yields ( targeted yields) by addressing local conditions in particularly on site based. Soil, nutrient supply capacity is highly vary from site to site within the field and on skilfulness among the formers. The Site Specific Nutrient Management without automation consists of different components Viz., intensive geo-reference soil sampling and analysis; geo-statistical analysis or semi-variogram analysis;
100 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______krigging stochastic simulation for interpolation of nutrients; developing nutrient management zones and fertilizer prescription on targeted yield basis. Castor crop has taken as case study and implemented in Inceptisols of Mahabubanagar district under irrigated condition during rabi season. In one hectare of farmer’s field 42 grids were developed @15 x 15 m space and collected geo-referenced soils from the each grid and analysed for chemical and available major, secondary nutrient i.e S and micronutrients. Based on the geo-statistical analysis varoni maps were developed with different models for different nutrients and the analysed nutrients were interpolated for krigging and developed different nutrient zones. In castor crop for nitrogen & potassium, sulphur, micronutrients zinc, copper, manganese, iron and boron 2 and for phosphorous 3 nutrient zones were developed. The fertilizer prescriptions were made on targeted yield (30 q/ha) equation of FN= 15.40T-2.30SN; FP2O5= 4.72T-6.44SP & FK2O=4.75T- 0.44SK in SSNM field @ 92N, 53P, 15K, 40S & 25ZS kg/ ha over 80N, 40P & 30K in RDF and 100N, 40P &30K in Farmers practice. The Site Specific Nutrient Management without automation was compared with farmers practice (FP) and recommended dose of fertilizers (RDF),where variable rates of fertilizer applications were used in balanced mode in SSNM by correcting deficient nutrients zinc and sulphur in soils thereby could achieved/ attained attainable yields of 30q/ha through increasing soil supply system and fertilizer use efficiency when compared to 12.5 and 15 q/ha in farmers practise and recommended dose of fertilizer plots, respectively. The over reduction in the usage of nitrogen and potassium there by reduced
101 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______in the fertilizer cost and zinc & sulphur were supplied in integrated mode to maximized the yields to 30 q/ha Keywords: Nutrient Management, Fertilizers, Castor crop, micronutrients, Yield Maximization
Abstract # NCGTA-PP-056 Temporal image analysis to observe creation of a 'beel' through a geomorphological development in the course of river Hooghly.
Sanjeev Kumar Sahu*, Manisha Bhor and Basanta Kumar Das ICAR- Central Inland Fisheries Research Institute Barrackpore *E-mail: [email protected]
Topography and geomorphological features play an important role in fisheries resource management. ‘Beels’ as large lakes / water- bodies are known in parts of West Bengal and Assam are significant contributors to fish and fisheries. They are very rich in bio-diversity and they also have significant species richness under perfect environmental conditions. A river in it’s entire course passes through and contributes to a wide variation of topography before draining into the sea. One such geomorphological feature is an ox-bow lake found in it’s lower course. These lakes are known by different local names, one such name being a ‘beel’. These extraordinary inland water resources form the basis of a
102 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______variety of fishes contributing to a large part of the production. This study observes the formation of one such ‘beel’ in the course of river Hooghly, a major distributary of the mighty river Ganga, near a place called Karalia in West Bengal. This has been done with the help of satellite imagery and GIS. It can be considered as a pilot study and many such occurrences can be studied likewise. Keywords: Topography, inland water resource, beel, remote sensing, GIS.
Abstract # NCGTA-PP-057 GIS Tools for Combating Climate Change through Precision and Sustainable Agriculture
S. Rakesh1*, Sumanta Kundu2, G Somashekar1, G. Ranjith Kumar1, R. Manasa1 and Ch. Srinivasarao1 1ICAR-National Academy of Agricultural Research Management, Hyderabad, Telangana, India 2ICAR-Central Research Institute for Dryland Agriculture, Hyderabad, Telangana, India *E-mail: [email protected]
“Agriculture” is the reliable source of life for humankind, as well as one of the honest sources of income. This entails hard work by contributing to the country’s food and nutrition security. Currently, agriculture and its allied sector viz., forestry, dairy, horticulture, poultry, beekeeping, mushroom, sericulture etc. are affected by climate change and its variabilities which is a major concern for scientific community. As our climate continues to heat up the favorable atmosphere and the impacts of warming tends to
103 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______be more frequent and severe, farmers and farming communities are putting under risk and increasingly challenged. Extreme activities of climate change alter weather conditions, thus has a direct and biophysical effects on agricultural production. Due to on-going climate change issues like floods and droughts, agriculture sector has become severely vulnerable to the irregularities of weather. Thus, ensuring global food security through sustainable production and achieving environmental quality through smart management of natural resources has become a greatest challenge in current agricultural system. Sustainability is entirely dependent on the judicious management of available resources like soil, rain and underground water, forest, etc. through an effective technological approach. A thematic mapping technology like geographical information system (GIS) in modern agriculture is important for resource management as well as prediction of current and future fluctuations. Visual analysis of the satellite imagery data produced by GIS tools is beneficial in farming industry. GIS in agriculture is helping farmers to achieve higher rates of production by providing precise information of agrometeorological data that transforms conventional agriculture to precision agriculture through improving the resource use efficiency. Farmers, especially who are vulnerable to flash floods and droughts would be able to make a decision before the happening of negative incident by anticipatory preparation and following the advanced management strategies like sowing time, irrigation, fertilizer application, spraying, harvesting etc. The rice water balance model linkage predicted a water indent for the irrigation requirements at the head of the distributary for the next 14 days of the irrigation cycle after
104 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______accounting for conveyance losses through GIS in the command area of Patna canal system. Classification of severity of drought (no drought, slight drought, and moderate drought) was made by generating patio-temporal drought risk maps in Iraq using Normalized Difference Vegetation Index (NDVI), seasonal rainfall and Standardized Precipitation Index (SPI) values by combination weighted overlay method. Application of N fertilizers were reduced through Site-Specific Nitrogen Fertilization by GIS modelling in Greece. The system further divides the area into zones where specific types of fertilizers should be applied, giving a certain prescription for the method and time of fertilization. Likewise, application of GIS helps stakeholders to predict future fluctuation maps of precipitation, temperature etc. Proper application of technology offers a way to precision agriculture within in the traditional system. Modern farming is all about optimizing the agriculture production. Incorporation of GIS tools into standard cultivation practices helps farmers and researchers to improve the precision in management by implementing them at subfield scale. For addressing some of the burning issues at present day agriculture viz., managing degraded natural resource base, farm distress due to price fluctuation, poor market intelligence, intense global competition and environmental hazards, GIS may be a cost effective decision support tool. Agriculture must continue to embrace GIS to adapt with increased awareness of geospatial technologies and its role in society to accomplish sustainability and environmental safety. Keywords: GIS tools, Climate Change, Agriculture, Precision and Sustainable Farming
105 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-058 Identification of Groundwater Recharge Potential Zones in Hyderabad using Remote Sensing and GIS
V. Anuragh1*, D. Doneshwari1, K. Veerendra Gopi2, T. SrinivasaRao2 1Under graduate, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad 2Assistant Professor, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad *E-mail:[email protected]
Surface runoff alone is not just enough to meet the water demands of the people. Therefore, groundwater serves as the alternative to meet the water demand not only at present but also in the future. To have the sustainable growth recharge of groundwater is a necessary action. Now-a-days large amount of water is being used for various purposes such as industry, domestic purpose, etc. hence increase in water demand occurs and ultimately groundwater is overexploited by the humans leading to the depletion of groundwater levels. If proper recharge methods are not deployed to increase the groundwater levels, it will cause scarcity of water further leading to other problems. Hyderabad is one of the biggest cities in Telangana State, and has large amount of area covered with concrete with which the surface runoff increases with decrease in infiltration rates leading to low recharge rates of groundwater. To find out those areas which are most efficient in capturing groundwater a remote sensing and GIS based
106 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______methodology is adopted in the current study. GIS methods permit rapid economic and natural resource survey and management. Remote sensing is collecting the information about an object without physically being contact with the object. Remotely sensed data serves as a chief tool in groundwater prospecting. Various parameters which affects the occurrence of groundwater are land use land cover, slope, lineament, soil, drainage density. These parameters for the study area were collected from satellite images- Landsat 8 satellite image was taken for land use land cover map, USGS Earth Explorer website was used to get Aster GLOBAL DEM (Digital Elevation Model), soil data was obtained from Food and Agricultural Organization of United States (FAO). the slope map was prepared from DEM. all the raster files are reclassified based on their importance to affect the groundwater recharge potential at a region. All thematic information after being reclassified were overlaid in ArcGIS software to identify recharge potential zones. The resultant raster map was classified in to very poor, poor, moderate, good and excellent. The regions categorized under best are considered as the best regions for ground water recharge. The groundwater recharge potential zone map will be useful to implement suitable recharge methods to increase the groundwater levels. Keywords: Remote Sensing, GIS, Ground Water Recharge, DEM
107 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-059 Dynamics of Evapotranspiration in an Irrigation Command Area using SEBAL Model for Planning of Water Resources
K. Krupavathi, M. Raghu Babu, A. Mani, P.R.K. Prasad and L. Edukondalu
Asst.Professor Acharya NG Ranga Agricultural University Bapatla, Guntur Dt., Andhra Pradesh *E-mail: [email protected]
Optimal planning and management of the limited water resources for maximum productivity in agriculture requires quantifying the irrigation water applied at a regional scale. Evapotranspiration (ET) is an essential component of the water balance to quantify the irrigation water applied. The ET of any region tends to vary dramatically both in time and space with diversified cropping patterns and climate. Which renders the accurate estimation of yearly or seasonal ET a difficult task. Reliable estimates of temporal fluctuations of ET is required to understand the coupled water and energy cycles and to improve water management. Meteorological or climatological methods of ET estimation are based on point data, which cannot provide a good estimation of ET in large areas. Although the water balance method can estimate evapotranspiration on a basin scale, it works in the long term, generally yearly, and cannot meet the requirements of short-term studies. Viewing these problems, remote sensing methods are used
108 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______to do ET estimation, which provide ET estimated results on pixel- by-pixel scale for shorter periods over a large area. The study included the Surface Energy Balance Algorithm for Land algorithm, a spatial ET estimation method based on energy balance and a satellite remote sensing technique partitions between sensible heat flux and latent heat of vaporization flux. Compared to the estimated evapotranspiration from climatological data, calculated ET by SEBAL agreed well. During the period of study, the highest per cent of error in ET estimation between FAO PM method, SEBAL method was found as 7.64 %. In paddy crop, 67 % of observations have less than 4 % error. In sugarcane crop, most of the cases the error is in the range of 1-4 %. 62.5 % of observations have less than 6 % error. The spatial distribution characteristic of daily evapotranspiration was analyzed by referencing the land-use map of 2016. It was found that the open water body has high evaporation rate, while the crop land, grassland and rural residential land took the second place, and the overflow land, town constructed land and bare soil were at the lowest evapotranspiration rate, which accorded with the evapotranspiration theory. This study demonstrates the considerable potential of Landsat for water use estimation at regional scale.
Keywords: Evapotranspiration, SEBAL, Landsat 8, spatial map.
109 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-060 Assessment of Soil Erosion Risk and Watershed Prioritisation in the Upper Subarnarekha Basin Using SWAT Model
Chinmaya Panda*, D. M. Das and B. C. Sahoo
Department of Soil and Water Conservation Engineering, CAET, OUAT, Bhubaneswar *E-mail: [email protected]
Soil erosion is one of the most serious land degradation processes, which decreases the soil depth and fertility status. It is due to the complex interplay of many factors such as climate, land use, topography, and human activities. Various soil water conservation measures are being adopted to conserve the precious soil resources. Installation of soil and water conservation structures involves high cost and labour. Therefore, correct assessment of the amount of soil loss and the potential area of soil erosion is very much essential for economic installation of these structures. In the present study a trial has been made to use the Soil and Water Assessment Tool (SWAT) model, embedded with ArcGIS interface, to predict the monthly streamflow and sediment yield from the upper catchment of Subarnarekha basin in order to adopt the appropriate management interventions. The performance of the model is quite satisfactory for simulating the monthly streamflow with R2 and NSE values of 0.90 and 0.90 respectively during calibration and 0.85 and 0.83 respectively during
110 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______validation. Again, the model also showed its capability to simulate monthly sediment yield with R2 and NSE values of 0.78 and 0.76 during the calibration period and 0.76 and 0.75 during the validation period, respectively. The entire basin was divided into nineteen sub-basins and prioritization was made among the sub- basins based on sediment yield, dominant soil type, land use and percentage of land slope to identify the sub-basins for adopting conservation practices. Based on the prioritization process, the nineteen sub-basins were divided into four categories. The results revealed that a larger part of the watershed (51 %) fell under low, 44% fell under moderate soil erosion risk and only one sub-basin (5 % of basin area) was most vulnerable to soil erosion with an estimated sediment loss exceeding 10 t/ ha/year. From the study it is concluded that spatial differences in erosion rates within the basin are mainly caused by differences in land cover type, agricultural practices, and gradient slope. Application of the SWAT model demonstrated that the model provides a useful tool to predict the surface runoff and soil erosion hazard and can also be successfully used for prioritizing the vulnerable areas within a basin where more focus may be given for installation of soil conservation structures. Keywords: Sediment yield, Soil erosion, SWAT, Watershed Prioritization
111 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-061 Soil Fertility Mapping of Brahmanakotkur Watershed in Kurnool district of Andhra Pradesh
S. Satish*, K.V.Ramana, M.V.S. Naidu, G. Prabhakara Reddy and P. Sudhakar
Department of Soil Science and Agricultural Chemistry, S.V. Agricultural College, Acharya N.G.Ranga Agricultural University, Tirupati, Andhra Pradesh *E-mail: [email protected]
Two hundred thirty one soil samples from Brahmanakotkur watershed in Kurnool district of Andhra Pradesh were drawn at 320 m grid interval and assessed for their fertility parameters. Soil fertility maps were prepared for each parameter under GIS environment using Arc GIS v 10.3. Major proportion of the watershed area was moderately alkaline followed by slightly alkaline, strongly alkaline and neutral with non-saline in nature and soil organic carbon content was low to medium. Mapping of available N by GIS revealed that 91% area in the watershed was low and 8.65% area was medium, available phosphorus (P) and potassium (K) were low (0.10 and 0.07), medium (2.87 and 10.42) and high (97.03 and 89.52) per cent respectively and available sulphur (S) was deficient (79%) to sufficient (21%). Regarding available micronutrients, zinc (Zn) and iron (Fe) were deficient in
112 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______about 80.25 and 75.27 per cent of the watershed area respectively whereas, available copper (Cu) was deficient (0.52%) to sufficient (99.48%) and available manganese (Mn) was sufficient (100%) in the soils. The mapping of nutrients by GIS technique in watershed revealed that, available N, S, Zn and Fe are important soil fertility constraints.
Keywords: Soil fertility map, Arc GIS, watershed, soil fertility constraints
Abstract # NCGTA-PP-062 DSS for Estimating Water Requirements of Grape and Pomegranate Crops
R. Nagarjuna Kumar1*, V. S. Rathore2, K. Srinivas Reddy1, M. S. Nathawat3, C.A. Rama Rao1, K. Sammi Reddy1, G. Ravindra Chary1 and B. Sailaja4
1ICAR-Central Research Institute for Dryland Agriculture, Hyderabad 2Birla Institute of Technology (BIT), Ranchi-835215, Jharkand 3Indira Gandhi National Open University (IGNOU), New Delhi 4ICAR-Indian Institute of Rice Research, Hyderabad
*E-mail: [email protected], [email protected]
113 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______In India, growing horticultural crops such as grape and pomegranate crops are highly productive due to wide variability of climate and soil. Grape and pomegranate horticulture crops are the potential agricultural enterprises in accelerating the growth of economy in country like India. But crop productions are dependent upon weather conditions. Studies have revealed that due to climate change a significant change in temperature, precipitation amount and variability in their spatial and temporal distributions is inevitable. These changes will have profound effect on water requirement of crops in India. The arid and semi- arid regions of India, where dry land farming is common with limited water supply will face enormous challenges in the near future. In view of the existing availability of water resources and increasing demand of water for grape and pomegranate crops, a holistic well planned long-term strategy is needed for sustainable water resources management in India. For this reason, a Decision Support System (DSS) is needed that help in efficient water resources management. Therefore, an attempt was made to develop an integrated system called Decision Support System (DSS) comprising of spatial information, the validated crop and climate model and a Graphical User Interface (GUI) for assessing the impact of climate changes on future water requirement of grape and pomegranate crops. Different components were identified to develop Decision Support System. Each component is from different platform i.e. remote sensing, climate model, CROPWAT model and user interface developed using programming language and Geographical Information System (GIS). For developing the Decision Support System, Ranga Reddy a semi-arid region of Telangana, and Anantapur an arid region of
114 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Andhra Pradesh were selected as study areas. The relevant input data for developing DSS at district level are: climate, crop parameters, soil and classified area maps. Initially to store and manage information on climate, soil and land use non-spatial and spatial databases were designed using GIS. Ancillary information were collected from Grape Research Institute, Department of Economics and Statistics, Departments of Horticulture and Institutes of Indian Council of Agricultural Research (ICAR). The CROPWAT model estimated future crop water requirement of grape and pomegranate fruit crops by using generated future climate data as input. The database (spatial and temporal) and model were integrated into a decision support system. Graphic user interface of DSS was designed to link spatial databases with climate and CROPWAT models in order to facilitate the selection of target area, crop, and climate data for assessing the impact of climate change on future water requirement of grape and pomegranate crops at district level.
Keywords: Horticulture, DSS, GIS, Remote sensing, Water requirement
115 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-063 Effect of Stage wise Irrigation Schedule on Yield and Quality of Thompson Seedless Grown on Dogridge Rootstock
D.Vijaya1*, Jagdev Sharma2, A.K. Upadhyay3, Ram Reddy4 Prakash Patil5
1, 4Grape Research Station Hyderabad, 2CPRI Shimla, 3NRCG Pune, 5IIHR Bangalore *E-mail:[email protected] A considerable gap exists today between our scientific knowledge on irrigation and its implementation in everyday practice. Irrigation water needs to be used judiciously since it involves both cost and energy. The study was conducted with an aim to study the influence of stage wise irrigation scheduling based upon pan evaporation on yield and quality of Thompson Seedless cv grafted on Dogridge rootstock at AICRP (F) on Grape at Rajendranagar, Hyderabad. Eight different irrigation schedules (treatments) were tested at variable replenishment rates based on pan evaporation at different growth stages of vine for 6 years i.e. from 2011-12 to 2016-17. The results revealed that Thomson Seedless irrigated with a replenishment rate of 60 per cent pan evaporation at shoot growth and berry set to harvest stages and at 20 to 40 per cent depending on rainfall at bud differentiation, bud development and flowering stages i.e. treatment (60-20-60-20-60-0) per cent pan evaporation at different stages of growth gave significantly higher yield which was on a par with uniform replenishment rate at 80
116 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______per cent pan evaporation(check treatment) and also replenishment at 80-60-80-60-80-40, 60-40-60-40-60-20, 80-40-80-40-80-20 and 60-20-60-20-60-0 per cent pan evaporation at different stages of growth viz shoot growth and fruit bud differentiation to cane maturity after foundation pruning and shoot growth, flowering, berry set to harvest and rest period respectively. The new schedule standardized reduced the irrigation requirement by 46 per compared to check treatment and improved the water use efficiency to 0.4 t/ha/cm without effecting yield and quality during all the years of study. The increase in yield can be attributed to significantly increase in number of bunches and bunch weight. It was noted that treatments which received less amount of irrigation recorded higher TSS.
Keywords: Irrigation treatments, Dogridge rootstock, Thomson Seedless, Evaporation, Yield improvement
Abstract # NCGTA-PP-064 Assessing the Supplementary Irrigation for Improving Productivity of Cole Crops using SWAT Model
J. Padhiary1 and D. M. Das2
1Department of Civil Engineering, NIT Rourkela 2Department of Soil and Water Conservation Engineering, OUAT, BBSR E-mail: [email protected]
117 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Irrigation sector is the highest consumer of the water in India. The increasing demand of water in other sectors has led to water shortage for irrigation. This creates danger for sustainable food security for the growing population of the country. Therefore, increase in water use efficiency and accurate irrigation scheduling is the call of the hour. This study has been conducted at Jaraikela catchment in Bramhani river reach, situated in semi-arid region of India. The crop productivity in the region is very low and can be improved by proper irrigation scheduling. Hence, it is very important to optimize irrigation scheduling to minimize the water use and increase the crop productivity. Cole crops (cabbage and cauliflower) are the most economic crop in the region during winter. Yield of winter Cole crops is simulated for rabi season (October–February) by using Soil and Water Assessment Tool (SWAT) considering both rainfed and irrigated scenarios. The water stress gradually increasing with shifting the planting period from Oct-15 to Nov 5 at 10-day interval. The average water stress days of the crop is 43 days with yield of 25 t/ha. Irrigated Cole crops with supplementary irrigation of 100–120 mm were resulted in improved yields of 40 t/ha with 28 water stress days. Among the sowing periods Oct-15 shows relatively larger water stress period and Nov-5 shows lowest. Keywords: Supplemental Irrigation, Cole Crop, SWAT, Irrigation Scheduling
118 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-065 Applications of Geospatial Technologies in Soil and Water Conservation Engineering- A critical review
S. S. Salunkhe*, B. L. Ayare and H. N. Bhange Department of Soil & Water Conservation Engineering, College of Agricultural Engineering and Technology, Dr. BSKKV, Dapoli, Ratnagiri, Maharashtra. E-mail: [email protected]
This paper deals with the applications of geospatial technologies in planning and designing of soil and water conservation (SWC) structures in the watershed. Various parameters are considered for site suitability of SWC such as drainage network, soil, land use/land cover, topography, etc. Classification of land according to its capability class is very much important for identification of the area for appropriate soil conservation measure for effective planning and management of watershed. The site suitability for SWC structures requires a considerable great investment as well as it consumes more time. Remote Sensing (RS) and Geographic Information System (GIS) techniques are widely used to planning and site selection of SWC structures because of it avoid cumbersome process and save the time. To select each location requires more time and cost. So, the application of RS and GIS analysis must be preceded by field survey before the actual implementation of conservation structures to verify the suitable site locations. Geospatial tools give the accurate site location as ground truth applicability. These tools
119 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______have also developed to meet ever-increasing demand for more precise and timely information. These techniques meet both the requirements of reliability as well as speed for generating spatial information. Thus, it has been proved to be use of RS and GIS are efficient, accurate and time saving and it is cost effective method for soil conservation site selection. Therefore, uses of these techniques are as preliminary method and can be applied as a first step for identifying the site locations for SWC structures. Thus, in the present study, geospatial technologies are integrated to determine the potential areas for soil and water conservation (SWC) structures in watershed.
Keywords: RS, GIS, site suitability, SWC structures
Abstract # NCGTA-PP-066 Use of Remote Sensing and Geographical Information System in Water Resources Planning and Management -A Critical Review
Dara Rooha Blessy1*, Suvarna Kale2 and B.L. Ayare3 1,2M.Tech. (Agril. Engg.) Students College of Agricultural Engineering and Technology, Dapoli 3Professor and Head, SWCE, College of Agri Engg. & Tech, Dapoli. Dist, Ratnagiri Maharashtra *E-mail: [email protected] Water is the basic necessity for the functioning of all life forms that exist on earth. It is safe to say that water is the reason behind earth being the only planet to support life. This universal solvent is one of
120 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______the major resources we have on this planet. Since there is a declining availability of water and increasing demand, the need has arisen to conserve and effectively manage this precious life-giving resource for sustainable development. Hence water resources are to be planned and managed properly using advanced technology. While Remote Sensing (RS) and Geographical Information System (GIS) techniques are often applied in the field of hydrology, there is still a deficit in the use of these techniques in planning, design and operation of water resources systems. To overcome this deficit and encourage water managers to use remote sensing (RS) techniques more widely, several successful examples of applications of remote sensing to water management are highlighted in this paper. The main aim of this review paper is to highlight the work done by earlier scientists in planning and management of water resources using Remote sensing (RS) and Geographical Information System (GIS). The usefulness of Remote sensing for crop classification, rainfall and snowfall estimation, soil moisture analysis, surface and groundwater use are shown that can be used for water resources planning and management in combination with Geological Information System (GIS). The Remote Sensing data cannot be directly used for these purposes but the electromagnetic data observed by spectral sensors have to be transformed into hydrologically relevant information. This transformed information can be used for water resources planning and management. These are the objectives of this review paper. Keywords: Water resources, Water management, Remote Sensing, Geographical Information System
121 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-067 Planning and Designing of Watershed Using Remote Sensing and Geographic Information System
Suvarna Sunil Kale1*, Dara Rooha Blessy2 and B. L. Ayare3 1,2M.Tech (Agril. Engg.) Students 3Professor and Head, Deptt. Of Soil and water conservation Engineering, College of Agriculture Engineering and Technology, Dapoli, Dist.- Ratnagiri (Maharashtra) *E-mail:[email protected] India is one of the most densely populated nations in the world. Due to growing needs of human being, the resources are getting depleted. This gives rise to problems such as deforestation, desertification, soil erosion, salinization, falling of water tables, etc. To overcome these problems scientific and rational land and water management is needed. Watershed planning means conservation of soil and water, improve ability of soil to hold water, maintaining vegetative cover to reduce soil erosion, rain water harvesting, ground water recharging. Remote sensing is a science and art of collecting information about objects, areas and phenomena from a distance without being in contact with them. Geographical information system (GIS) is attribute data or information describing the characteristics of a spatial feature. A defining feature of a GIS is the ability to link the attribute databases to the spatial feature database for geographical analysis. Also, land evaluation using a scientific procedure is essential to
122 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______assess the potential and constraints of given land parcel for agriculture purposes. Land capability classification method developed by USDA can be used in the study to estimate different land capability classes in the watershed. Crop suitability indicates the state of fitness crop growing well not in all types of soil but in particular types of soils which must contain major qualifies, suitable enough to meet the basic soil requirements of crops either party or wholly. These databases and associated attribute data may be part of GIS or GIS model linkage. The analysis result may be presented in tabular or graphical form and are intended to provide key information necessary for users or managers in making meaningful decisions about management, conservations and land use planning. An environmental resource assessments is a planning and decision making tool. The objectives of Environmental Resource Assessments are to minimize or avoid adverse environmental effects before they occur and incorporate environmental factors into decision making. The databases are used extensively to provide model input data to estimate water amounts and quality.
Keywords: Watershed Planning, Remote sensing, Geographical Information System, Land Evaluation, Crop Suitability, Environmental Resource Assessments.
123 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-068 Deficit water management practices influence on yield, water use efficiency, and consumptive use of rabi maize (Zea mays L.) N. Ramya, N.V. Lakshmi*, K. Chandrasekhar and K.L. Narasimha Rao Dept. of Agronomy (Water Management), Advanced Post Graduate Centre, Lam, Guntur, Andhra Pradesh Assistant Professor, APGC, Lam, Guntur-500 034, ANGRAU, Andhra Pradesh *E-mail: [email protected]
A field experiment was conducted on sandy loam soils of Agricultural College Farm, Bapatla, Guntur district of Andhra Pradesh, during rabi, 2017-18 to study the influence of deficit water management practices on yield and water use efficiency of maize. The experiment was conducted using split-plot design with furrow irrigation as main plots, i.e. alternate furrow irrigation (AFI) (I1) in which neighboring furrows were alternately irrigated during consecutive watering, fixed alternate furrow irrigation (FAFI) (I2) in which irrigation was fixed to either of the furrow in every irrigation and conventional furrow irrigation (CFI) (I3) where all the furrows were irrigated. Depth of irrigation was taken as subplots i.e., 60 mm (D1), 45 mm (D2) and 30 mm (D3). The crop was sown on November 4th 2017. The volume of water to be given for each treatment was calculated by multiplying the area with depth and the measured quantity of water was given to different treatments according to depth of irrigation by using Parshall flume. Field capacity of the soil was 24.5 cm per meter
124 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______depth of soil. Soil moisture content was determined by using thermo-gravimetric method from different soil layers and the values were used to compute the consumptive use and moisture extraction pattern by the crop. The results of the experiment revealed that the maximum water use efficiency (16.4 kg ha-mm- 1) was noticed with alternate furrow irrigation when compared to conventional furrow (13.3 kg ha-mm-1) and fixed alternate furrow (12.4 kg ha-mm-1) irrigations. Irrigating the crop at 30 cm depth recorded the highest water use efficiency (15.4 kg ha-mm-1) which was 11.7 % and 14.3 % more over 45 mm (13.6 kg ha-mm-1) and 60 mm depth (13.2 kg ha-mm-1). The highest kernel yield (7566 kg ha-1) was observed under alternate furrow irrigation at 60 mm depth of irrigation (I1D1) which was significantly superior over rest of the treatments. Consumptive use of water was found maximum under conventional furrow irrigation (422.2 mm) followed by alternate furrow irrigation (385.4 mm) and the lowest was recorded under fixed alternate furrow irrigation (381.3 mm). Among the depth of irrigation, irrigation provided at 30 mm depth reduced the consumption of water by 46.5 per cent compared to 60 mm depth. Moisture use rate by crop was significantly higher under conventional method of irrigation (3.8 mm day-1) over alternate furrow irrigation (3.5 mm day-1) and fixed alternate furrow irrigation (3.5 mm day-1). Irrigation at 60 mm depth recorded significantly higher soil moisture use rate (4.5 mm day- 1) compared to irrigation given at 45 mm (3.5 mm day-1) and 30 mm depths (2.8 mm day-1). Keywords: Furrow irrigation, alternate furrow irrigation, moisture use rate, consumptive use, maize
125 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-069 Comparative Assessment of Water Quality Parameters in Aquaculture Grow-out Using Conventional Methods and Real Time Sensors Ajay Adarsh Rao Manupati1*, Tapas Paul1, Rajesh Kumar Dash1, S.M. Raffi2 1Aquatic Environment Management, ICAR- Central Institute of Fisheries education, Mumbai 2Faculty of Fisheries, Kerala University of Fisheries &Ocean Studies, Kochi *E-mail:[email protected]
In the present study the water quality parameters, especially, water temperature, dissolved oxygen concentration and pH from a shrimp grow-out was analysed using conventional methods for a period of 90 Days of Culture (DoC). There was a gradual increase in temperature as the days of culture proceeds which fluctuated from 27 from 1st DoC to 330C at 90th DoC. Dissolved oxygen exhibited a gradual decline as the days of culture progressed and it fluctuated from 6 to 4.1 O2 mg/l; whereas, pH doesn’t exhibit wide variation and it fluctuated only between 7.6 to 7.8. The data obtained for water temperature, dissolved oxygen and pH by real time sensors exhibited perfect coherence with that of by conventional method which was cross checked at an interval of three hours. A comparative study was also performed on round the clock basis for 45 days of culture was conducted so as to unravel the efficiency of real time monitoring sensors vis-a-vis conventional laboratory techniques with the aim of optimize the
126 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______device as fault proof ones. The entire data generated out of real time sensors worked with the help of computer software named ARDUINO.
Keywords: Water quality parameters, Real Time Sensors, ARDUINO, Days of Culture.
Abstract # NCGTA-PP-070 Rainfall Runoff Analysis by Advanced Hydrological System and Artificial Neural Network
Nidhi Kumari1*, P. Singh2, M. S. Kundu3 and B. Shahi4
1. Subject Matter Specialist, Krishi Vigyan Kendra (KVK) Muzaffarpur (Additional), Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa, Samastipur, Bihar 2. Head, Krishi Vigyan Kendra Muzaffarpur (Additional), RPCAU, Pusa, Samastipur, Bihar 3. Director Extension Education, RPCAU, Pusa, Samastipur, Bihar, 848 125 4. Nodal officer of KVKs of RPCAU, Pusa, Samastipur, Bihar *E-mail # [email protected]
The main objective of the present study is to conduct laboratory experiment for the generation of rainfall runoff data using rainfall simulator (Advanced hydrological System). For the validation of
127 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______observed data, a model is established for estimating observed runoff data using Artificial Neural Network (ANN) technique. The ANN model for the runoff discharge evaluation was developed using MATLAB Software. The MATLAB tool used for the creation of ANN model is Neural Networks tool. We collected some data for runoff discharge at the laboratory using advanced hydrological systems. Laboratory experiments were conducted several times with rainfall simulator to generate runoff hydrograph using various bed slope and rainfall intensity over the catchment. The validation of observed runoff hydrograph data was simulated using ANN. The ANN model was developed using collected data point to compute runoff discharge. For developing ANN model, the available data were separated as 70% for calibration and 30% for validation. Predicted results using ANN model performed better estimation with observed values which is useful for water resources planning and management. For the testing of model performance Nash-Sutcliffe efficiency criteria were used which gives NSE greater than 90%. Comparison of observed and predicted runoff hydrograph reveals that ANN predicts the runoff data reasonably well in observed hydrograph. It is found that ANNs are promising tools not only in accurate modeling of complex processes but also in providing insight from the learned relationship, which would assist the modeller in understanding of the process under investigation as well as in evaluation of the model.
Keywords: Rainfall simulator, ANN, MATLAB, Hydrograph, Nash-Sutcliffe efficiency
128 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-071 Estimation of runoff from Kunaji micro watershed, Western Ghats by using soil conservation service curve number method along with remote sensing and geographical information system tools
K. M. Madhu1*, S. S. Shirahatti1, M. S. Shirahatti2
1University of Agricultural Sciences, Dharwad, Karnataka 2Regional Agricultural research station, Vijayapura, *E-mail: [email protected]
The information on spatial and temporal availability of runoff, one day maximum runoff and rainfall and runoff relation is helpful for safe and cost effective planning and design of water harvesting and drainage line treatment structures. Runoff was simulated from Kunaji micro watershed (478.19 ha) of Uttara Kannada in Western Ghats, Karnataka, India. The watershed is characterized by hilly topography with the slope ranging from 0 to 35 percent. The region receives an annual rainfall of around 2500 mm, with minimum of 1210 mm and maximum of 3500 mm. Reporting period, i.e.,in the year 2014 received 3327.6 mm of rainfall. The watershed consists of two types of soil according to NBSSLUP classification i.e. fine loamy and fine clayey. Runoff for the year 2014 was simulated using Soil Conservation Service Curve Number (SCS CN) model along with the inputs from remote sensing and Geographical Information System (GIS) tools. Among the different runoff assessing methods, the USDA – Soil
129 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Conservation Service (SCS) curve number method is a well- accepted tool in applied hydrology. The method is also called as hydrologic soil cover complex number method. The use of Geographic Information Systems (GISs) and remote sensing to facilitate the estimation of runoff from watershed and agricultural fields has gained increasing attention in recent years. Land use land cover map, hydrologic soil group map and curve number maps were prepared using GIS software IDRISI. Total runoff of 1690.2 mm corresponding to the runoff coefficient of 0.50 was simulated in micro watershed. Rainfall and runoff are related to each other and that relation is studied using regression analysis. The R2 value of 0.92 signifies a greater relationship between runoff and rainfall in Kunaji watershed. The runoff occurred during five months i.e. May to October. The maximum runoff of 800.15 mm was recorded in July followed by August (502.53 mm) and September (237.76 mm) months. Apart from more rainfall, the factors contributing to more runoff are the hilly topography, clay nature of soil and growing paddy on the banks of the stream. The quantitative data of runoff occurring in a watershed is very essential in designing the water and soil conservation structures. The above said data would be very helpful in formulating watershed management plans.
Keywords: GIS, Runoff Coefficient; SCS Curve Number; Remote Sensing, Soil and Water Conservation Structures
130 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-072 Mapping and Monitoring of water spread area in PWD tanks of Tamil Nadu using Remote Sensing data
M. Venkatesan1*, S. Pazhanivelan2, Ragunath kaliaperumal3
1Senior Research Fellow, Dept. of RS & GIS, TNAU, Coimbatore 2Professor and Head, Dept. of RS and GIS, TNAU, Coimbatore 3Asst. Professor, Dept. of RS and GIS, TNAU, Coimbatore *E-mail: [email protected]
Surface waterbodies are essential water storage units and for irrigated agriculture in India, surface water bodies such as reservoirs and tanks are the major water resources. Mapping and monitoring of tanks is necessary as they are dynamic in nature in terms of water spread area and volume of water. Microwave remote sensing data from SAR sensors will result in extracting spatio-temporal information on water spread area in surface water bodies which is essential for monitoring and planning of irrigation activities. In the present study, time-series Sentinel 1A SAR data was downloaded and processed using MAPscape-RICE software. The processed data was used to monitor the temporal changes in water spread area of the PWD tanks in lower Tamirabarani and lower Palar sub-basins of Tamil Nadu. Parameterized classification of Sentinel 1A SAR data in VV polarization was
131 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______utilized for extracting water spread area in the tanks and temporal changes in the area during August 2017 to January 2018 was monitored using the time-series data. In lower Tamirabarani sub- basin water spread area in PWD tanks during August, 2017 was 14508 ha which reduced to 11144 ha in December, 2017 as a result of agricultural irrigation activities in the region.
Keywords: Water spread mapping, Sentinel 1A, SAR and Microwave Remote Sensing.
Abstract # NCGTA-PP-073 Effect of macro and micro nutrients on growth, yield and economics of linseed (Linum usitatissimum) under irrigated condition
B. M. Wakchaure, P.N. Karanjikar* and V.G. Takankhar
College of Agriculture, Latur VNMKV, Parbhani *E-mail: [email protected]
An experiment entitled studies on nutrient management in linseed (Linum usitatissimum) under irrigated condition was conducted during rabi season of the year 2018-19 at Experimental Farm, Agronomy Section, College of Agriculture, Latur. The experimental plot was clayey in texture, low in available nitrogen (125.3kg ha-1), medium in available phosphorus (18.20 kg ha-1) and high in available potassium (498 kg ha-1). The soil was clay in texture with moderate water holding capacity and slightly alkaline in reaction PH (7.07). The experiment was laid out in a Randomized Block Design with 7 treatments replicated thrice. The
132 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______treatments were T1- 100% RDN, T2- RDF, T3- RDF + Sulphur @ -1 -1 20 kg ha , T4- RDF + ZnSO4 @ 20 kg ha , T5- RDF + FeSO4 @ -1 -1 - 20 kg ha , T6- RDF + ZnSO4 @ 20 kg ha + FeSO4 @ 20 kg ha 1 and T7- Control. The gross and net size of each experimental unit was 5.4 mx 4.5m and 4.8 m x 3.9 m, respectively. Sowing was done by dibbling method on 18th Oct., 2018. The fertilizers were applied as per treatment before sowing. The recommended cultural practices and plant protection measures were under taken as per recommendation. Among the different treatments, -1 -1 application of RDF + ZnSO4 @ 20 kg ha + FeSO4 @ 20 kg ha was found most effective for increasing growth and productivity of linseed. Application of RDF in combination with ZnSO4 @ 20 -1 -1 kg ha and FeSO4 @ 20 kg ha was found beneficial in increasing growth and yield attributing characters and seed yield of linseed than RDF alone or combination with ZnSO4, FeSO4 or sulphur alone respectively. Application of RDF in combination with zinc -1 -1 sulphate @ 20 kg ha and ferrous sulphate @ 20 kg ha (T6) recorded highest oil yield (476 kg ha-1) which was followed by application of RDF + zinc sulphate @ 20 kg ha-1(412 kg ha-1) and application of RDF + ferrous sulphate @ 20 kg ha-1( 402 kg ha- 1).Application of RDF in combination with zinc sulphate @ 20 kg -1 -1 ha and ferrous sulphate @ 20 kg ha (T6) treatment recorded higher gross monetary returns (Rs. 71,880 ha-1) and net monetary returns was (Rs. 36,426 ha-1) with higher B:C ratio (2.03)which was followed by treatment T4 i.e. application of RDF + zinc sulphate @ 20 kg ha-1(Rs. 62,700 ha-1).
Keywords: Linseed, Sulphur, Ferrous sulphate, Zinc suphate, Growth, Yield, Economics
133 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-074 Hydrological Modeling of a Sub-Basin of Mahanadi River Basin using Swat Model Munish Kumar1*, Ramesh Verma2 1Department of Soil Conservation & Water Management, Chandra Shekhar Azad University of Agriculture & Technology, Kanpur, India 2Deptt. of Farm Engg. I.Ag.Sc., Banaras Hindu University, Varanasi, India *E-mail:[email protected], [email protected]
Hydrological modeling has important role for designing, planning and managing any water resource developmental project. In developing countries like India it become more relevant to model the river basin as discharge measurement at various locations is a costly affair. Once a hydrologic model is calibrated for a basin it may be used to produce the discharge time series at any location of interest. In the present study, an attempt has been made by using soil and water assessment tool (SWAT) model to understand different hydrological processes occurring in Kesinga basin. Various hydro-climatic data and spatial data have been used for the study, which were collected from different global and local databases. After data processing, the ArcSWAT interface of ArcGIS was used to build up the parameters along with hydrologic components, which are required in the SWAT model. The study was conducted for a period of 21 years (1990-2010). During the calibration period of 11 years (1990-2000) the model resulted into
134 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______R2 and NSE values of 0.81 and 0.72 respectively. Similarly, during the validation period of 10 years (2001-2010) R2 and NSE values were calculated as 0.84 and 0.76respectively. Sensitivity analysis of SWAT model was performed using LH-OAT technique and out of twelve calibrated parameters, five parameters were found to be sensitive.
Keywords: HRUs, LH-OAT technique, Sensitivity analysis, SWAT Model
Abstract # NCGTA-PP-075 Comparing SPI and RDI for Parambikulam Aliyar Project (PAP) basin of Tamil Nadu using DrinC
V. Guhan1*, V. Geethalakshmi2, K. Senthilraja3, P.J. Prajesh4, S.P. Ramanathan5
1Ph.D scholar, Agro Climate Research Centre, TNAU 2Director, Directorate Crop Management, TNAU, Coimbatore 3Research Associate, Directorate Crop Management, TNAU 4Senior research fellow, Dept. of RS and GIS, TNAU 5Professor and Head, Agro Climate Research Centre, TNAU*E- E-mail: [email protected]
Drought and wetness events were studied in the Parambikulam Aliyar Project (PAP) basin with Standardised Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) using Drought indices Calculator (DrinC) version 1.7. PAP basin is located in the south western part of the Peninsular India covering areas in Kerala
135 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______and Tamil Nadu States with average maximum temperature of 27.2oC, average minimum temperature of 19.6oC and average annual precipitation of 710 mm with 121 rainy days respectively. SPI only uses precipitation data while RDI uses a ratio between precipitation and potential evapotranspiration (PET). The latter was computed with the Thornthwait equation, thus using temperature data only. Monthly precipitation and monthly temperature data were obtained from Kings gridded data. Data sets cover the period from 1981 to 2017. Using ordinary kriging, the gridded temperature and Precipitation data was interpolated to entire PAP basin, thus providing to compute SPI and RDI. SPI and RDI were therefore compared and results shown that both indices revealed more sensitive to drought when applied in them PAP basin, differently, more wetness events were detected by RDI in PAP basin. Comparing both indices, they show a coherent and similar behavior, however RDI shows smaller differences, which is an advantage relative to the SPI and is likely due to including PET in RDI. Results also reveals that DrinC software may be used in a variety of applications, such as drought monitoring, assessment of the spatial distribution of drought, investigation of climatic and drought scenarios, Water resource planning and management, irrigation and water usage. The applications of DrinC in PAP basin of Tamil Nadu, is gaining ground as a useful research and operational tool for drought analysis, water resource planning and management. Keywords: Drought Indicies Calulator, Standardised Precipitation Index, Reconnaissance Drought Index, Potential Evapotranspiration.
136 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-076 Applications of Thermal Remote Sensing in Agriculture
D. Anil kumar*, B.Soujanya, T.L. Neelima, M. Uma devi Water Technology Center, College of Agriculture, PJTSAU, Rajendranagar, Hyderabad-030, Telangana State, India *E-mail: [email protected]
Thermal remote sensing is based on the infrared portion of the spectrum and measures emitted thermal energy. Thermal Remote sensing is a type of passive remote sensing since it detects naturally emitted radiation and operates in 3-5 μm and 8-14 μm wavelengths range. The primary advantage of Thermal remote sensing is that, the features which cannot be detected by optical RS can be detected with Thermal IRand can detect true temperature of the objects. Thermal imaging has been growing fast and playing an important role in various fields of agriculture starting from nursery monitoring, irrigation scheduling, soil salinity stress detection, plants disease detection, yield estimation, maturity evaluation and bruise detection of fruits and vegetables. Significant correlations between seedling temperature and degree of damage can help in nursery monitoring. A new approach was developed to schedule irrigation based on Evapotranspiration rates and water requirements using ground based remote sensing systems. TIR could also be used to detect pathogen before visible symptoms occur, by exploring the potential of thermal imaging for pathogen detection. Accurate assessment of the extent of crop
137 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______residue is necessary for proper monitoring and implementation of conservation tillage practices. By examining the differences in soil surface temperature between conventional and no-till systems, the potential of thermal images can be used for mapping residue cover and tillage practices. Thus Thermal remote sensing has a greater potential and will play a more significant role in various fields of agriculture Keywords: Thermal Remote Sensing, Crop residue, Tillage
Abstract # NCGTA-PP-077 Role of Remote Sensing and GIS in Water Resources Management
B. Soujanya1*, D. Anil kumar2, B. Balaji Naik3, T.L. Neelima4, M. Uma Devi5 1,2 M.Sc, Ag Agronomy Water Management, WTC, College of Agriculture, PJTSAU, Hyderabad 3Senior Scientist (Agronomy), Agro climatic research center, ARI, Rajendranagar, Hyderabad 4Scientist (Agronomy), RS & GIS lab, PJTSAU, Hyderabad 5Director, WTC, College of Agriculture, PJTSAU, Hyderabad *E-mail: [email protected] Agriculture consumes 80-85% of water resources. In India the efficiency is 35%, while the countries like Japan and China have efficiency of 50-60%. Availability of per capita fresh water is major concern in India as the population continue to increase although the average annual rainfall including snowfall in India is
138 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______4000 Billion Cubic Meters. Measurement and knowledge of availability of water resources in different parts of the country helps in management of water. Hydrological observations and modelling using satellite data is important for sustainable management of water resources over large region. Remote sensing of water resources involves generating information ranging from regular inventory of surface water bodies to assessment of rainfall, snow and glacier studies, irrigation water management, reservoir sedimentation, watershed management, disaster management, identification of potential irrigable lands, water quality assessment, soil moisture estimation, evapotranspiration, snow melt runoff and ground water assessment. Satellite provides an important platform from where measurements can be done in any part of electromagnetic spectrum suitable to detect different phases of water i.e. solid, liquid and gas over a large region. Various Indian satellite platforms used in Hydrological Remote Sensing are SARAL-Altika Mission (Inland Water level), RISAT- 1 SAR Mission (Surface water spread, Soil Moisture), Resourcesat-1/2 Missions (Snow cover, Wetlands, Land use Land cover, Water quality), Cartosat Missions (DEM),Scatsat-1 and INSAT-3D Missions (Rainfall, Solar Radiation etc.). The electromagnetic information obtained by spectral sensors has always to be transformed into other information, which is relevant in the field of hydrology. This transformed information can be used for water management purposes.
Keywords: Hydrological Remote Sensing, GIS, DEM, Water Resource Management
139 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-078 A diagnosis of water table depth and water quality dynamics in the salt affected paddy fields of Bhadra command, Karnataka
C.N. Nalina*, P.K. Basavaraja, T.S. Vageesh and S.S. Prakash
Department of Soil Science and Agricultural Chemistry, college of Sericulture, University of Agricultural Sciences, GKVK, Bengaluru *E-mail: [email protected]
Irrigation has played a significant role in increasing the productivity globally. At the same time, unscrupulous, indiscriminate and excessive use of irrigation water, particularly in the command areas, become a potential source of recharge which caused a continuous rise in the water table and degrade the soil resource in terms of water logging and soil salinization. The study is conducted during 2016 at Tyavanagi village (75° 53' 20" to 75° 53' 02" E longitude and 14° 14' 48" to 14° 14' 16" N latitude), Davanagere district of Bhadra command area, where the farmers grow flooded rice as a sole crop. The topographic survey was carried out to arrive Up land, mid land and lowlands covering 121 acre area. Totally 25 observation tubes were installed across all the land classes along the suspected water flow paths. The water table was monitored in each observation tube at monthly interval by recording depth of water table at the same time water
140 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______samples were collected and evaluated for quality parameters (pH, 2+ 2+ + + 2- - - 2- EC, Ca , Mg , Na , K , CO3 , HCO3 , Cl and SO4 ) to compute water quality indices (SAR and RSC) using standard procedures. Different krig maps were prepared by ordinary krigging for water table depth and water quality variables. The study records shallower water table during kharif compared to rabi and summer, indicating fluctuating water table over seasons which largely dependent on canal supplies. The water quality varied seasonally, the samples collected during summer belongs to C4S1 category, while the samples collected during rabi and kharif belongs to C3S1 category. Salinity has increased during summer compared to rabi and kharif. Salinity of water increased slightly with shallower water table (mid lands) compared to up lands and low lands, due to vertical and horizontal seepage of water from surface, all along the topography along with soluble salts. Hence the study reveals that, in the command area, application of heavy irrigation have led to the rising of water table to a critical zone of <1.5 m in rice fields, in addition, neglecting the drainage have also aggravated the situation. Also the results clearly showed that the water drained through the soil were saline in nature, hence not suitable for irrigation or for leaching if it is used directly. The results further helps to develop appropriate drainage design and drainage water management criteria's in salt affected soils. Key words: Salt affected soil, Water logging, Water table, Observation tubes, Water quality, Krig maps.
141 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-079 Geospatial Appraisal of Odisha Inland Water Resources Manisha Bhor*, Sanjeev Kumar Sahu, and Basanta Kumar Das ICAR- Central Inland Fisheries Research Institute Barrackpore
*E-mail: [email protected]
Geographical information system (GIS) is a tool for reading, retrieving, storing, visualizing, analyzing, modeling and presenting the spatial data. It provides immense power to natural resource managers to visualize and assimilate the data for decision making. As the natural resource management and planning needs spatial tool to integrate the spatial information with biological information. GIS tools are the solutions under these circumstances. ICAR-CIFRI has evaluated the impact of fingerling stocking in eighty three small reservoirs of 19 districts of Odisha which was stocked by Department of fisheries, Government of Odisha under SC/ ST development programme during 2012-13 and 2013-14. Under this program (PFCS) the highest increase in production has been recorded in Jamuna bandha reservoir in Ma Basanti PFCS. In six reservoirs, there has been an increase in production by more than 100 MT. An increase of more than 50 MT production has occurred in four reservoirs. In 21 reservoirs there has been an increase in production of up to 50 MT, 27 reservoirs have a decrease in production and there are still a few others in which a negligible change in production has occurred.
Keywords: GIS, Reservoirs, Production
142 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-080 Geospatial appraisal of Bihar inland water resources
Manisha Bhor, Sanjeev Kumar Sahu*, Ganesh Chandra and Basanta Kumar Das ICAR- Central Inland Fisheries Research Institute Barrackpore *E-mail: [email protected]
Bihar is a land locked state located in the Northern part of India with a variety of topographical features and many rivers flowing through it creating several inland fishery resources in the process. Bihar has wide variety of water bodies ranges from 0.1 ha to thousands of hectares. Present study analyses LANDSAT 8 images, which were used for water area delineation. In the study, three bands of 30-meter spatial resolution and one band of 15- meter spatial resolution were processed using fusion technique. In Bihar, there are a larger number of waterbodies in the north of river Ganga in comparison to southern parts of this mighty river. The state has a total of 54632 water bodies with 16938 perennial and 37694 seasonal waterbodies. The state has 74112 hectares of post-monsoon water spread area and 25877 hectares of pre- monsoon water spread area. Approximately 46 percent of water bodies have post monsoon area more than 5000 square meters and only 126 water bodies have area more than 50 hectares. District Madhubani has the maximum number of waterbodies followed by Darbhanga. while Purba Champaran has the maximum water area followed by Madhubani. Bihar state fish production data of 2016-
143 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______17 also shows same pattern. Madhubani followed by Purba champaran and Darbhanga gives highest fish production. Average water body area is maximum in Khagariya and minimum in Madhepura. District Khagariya shows the highest fish production per unit and in Jamui district, per unit production is lowest. In case of per ha production Munger is the leader and Jamui is at the lowest rank. These study-based maps give more spatial information and scope for spatial analysis so that resource managers find it easy for better management of these resources.
Key words: LANDSAT 8, Remote sensing, Delineation.
Abstract # NCGTA-PP-081
Identification of Erosion-Prone Areas and Prioritization of Micro-Watersheds: A Remote Sensing and GIS Approach
V. T. Shinde*and M. Singh Navsari Agricultural University, Navsari-396 450, Gujarat, India *E-mail: [email protected]
Agriculture is the major source as well as victim of non-point source pollution and sediment is most important ingredient of non- point source pollution along with pesticides and fertilizers. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. Quantitative assessment of
144 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______average annual soil loss in micro-watersheds of Ambika watershed of South Gujarat region was made using the well- known USLE with a view to know the spatial distribution of average annual soil loss in the watershed. The use of GIS and remote sensing data enabled the determination of the spatial distribution of the USLE parameters. Annual average soil loss for the entire watershed was estimated as 22.41 tha-1yr-1. The micro- watershed prioritization indicated that 50 micro-watersheds are falling under moderately high to very high category which required immediate attention for soil conservation treatment. As the average slope of all these micro-watersheds varies from 5-8%, contour bunds and terraces were recommended to reduce soil erosion in these micro- watersheds. The annual average soil erosion for the entire watershed is reduced to 17 tha-1yr-1 from 22.41 tha-1yr-1 after incorporating the effect of suggested soil conservation measures. The cumulative effect of soil conservation treatment on soil erosion for priority class 1 to 3 was analyzed. Reduction in the area affected by average soil erosion magnitude from 7.5% to 0% for priority class 1, 49.75% to 37.19% for priority class 2 and from 22.41% to 17.63% for priority class 3 was observed. Hence, remote sensing and GIS technology can be used as an alternative to conventional method of soil loss estimation and subsequent prioritization of micro watersheds for implementing soil conservation practices.
Keywords: Remote sensing; Soil erosion; GIS; USLE; Priority
145 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-082 Flood Inundation Modelling in Cauvery Basin Using HEC-RAS: A Case Study of T Narsipura Discharge Site
Tippu Kareemulla Sharif* Department of Geography and Geo-informatics, Bangalore University, Jnanabharathi, Bengaluru
*E-mail: [email protected]
Flood inundation models play a central role in both real-time flood forecasting and in flood plain mapping Flood inundation models work with discharge and water level as upstream, downstream or as internal boundary conditions. The aim of this study is to produce Flood Inundation model of Cauvery River at different epochs in order to detect the changes that have taken place particularly in the flooding pattern and subsequently predict changes that might take place in the same area over the next few years. Also, in this study, unsteady flow analysis has been performed because in a river the flow of water is unsteady as the rate of flow, discharge, velocity or any such parameters are not constant, are rather considered as variables instead. Based on the data analysis, it is evident that discharge of water, Water Surface Level, Terrain of the river channel and banks, Depth, Velocity are few parameters which are very crucial in determining the inundation boundary. The study concludes that the use of HECRAS forms an essential tool for inundation modelling and
146 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______this type of modelling in this case study has helped to determine the maximum and the minimum flood inundation boundary. Keywords: Cauvery Basin, flood inundation model, HECRAS forms, discharge of water
Abstract # NCGTA-PP-083 Role of Big data for smart agriculture in India for doubling farmer income.
G. Majeed*, Mouneshwari R Kammar, ICAR-Krishi Vigayn Kendra, Bagalkot *E-mail:[email protected] In modern days due to advent of information communication technology, senor based internet of things (IoT) and new satellites launching programmes by India Space Research Organization with the help of Artificial Intelligence technology using the voluminous data generated by agriculture from selection of quality seeds, fertilizer management and efficient water conservation technology and optimum use of pesticide and market linkage may definitely lead to increase in yield with minimal resources. The Big data analytic may also help for insurance company for scientific method of crop insurance and governments. In present days by employing sensor based Internet of Things (IoT) technology which efficiently regulates water management activities for agriculture including optimal utilization of
147 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______electricity, water and fertilizers. Central and state government stakeholders, crop insurance companies. Government scheme for crop insurance, doubling farmer’s income and rural development will drive the adoption of Big Data analytics into the agriculture sector, this will improve decision intelligence about crops, their prices, soil and weather pattern. The business opportunities range from helping executing flagship programs of the government in the agri sector by providing them a data-driven planning tool for assisting financial institutions in risk management and helping large agri commodity trader hedge against price volatility. Niti Aayog also making an experiment to use precision farming by using big data analytics on pilot basis. In future, artificial intelligence coupled with Internet of things (IoT) create revolution in agriculture for benefit of farming community and government flagship programmes. Keywords: Artificial Intelligence, Internet of Things (IoT), Agriculture
148 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-084 Assessment of Water Yield and Reuse Options for Enhancing Cropping Intensity in Sub-basin Scale using SWAT and Linear Programing Technique
J. Soren*, D. M. Das, B. C. Sahoo and S. K. Raul
Department of Soil and Water Conservation Engineering, OUAT, Bhubaneswar *E-mail: [email protected]
Rainfed agriculture in India spreads over 94 million ha which is 65% of its net sown area. Cropping pattern is this region is mostly mono-cropped and very often susceptible to crop failure due to increasing uncertainties in monsoonal rain. About 80% of mean annual rainfall is received during four monsoon months in high rainfall zones like Odisha, West Bengal, Chhatisgarh, and Jharkhand and report reveals that this trend is gradually worsening due to the effect of climate change. Again, harvesting a second crop from this area under dismal residual soil moisture condition is associated with a risk factor which is beyond affordability of a common farmer. Unless rainwater surplus and groundwater potential of rainfed regions in basin/sub-basin/watershed scale is assessed and means to harvest them for meeting the irrigation requirement is planned properly, it may not be possible to enhance the cropping intensity of this disadvantaged areas. In this study, SWAT model is used to estimate the streamflow in the middle catchment of Baitarani river basin in Odisha. The model efficiency
149 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______in simulating monthly streamflow has been established through R2, %PBIAS and NSE values of 0.85, 13and 0.84 during calibration, and 0.81, 18 and 0.79 during validation, respectively. The basin was divided into 7 sub-basins, and the most agriculture intensive sub-basin was considered for water yield assessment using SWAT. Water yield assessment includes the surface runoff, lateral flow and groundwater flow contributing to the streamflow from the sub-basin. Linear programming technique was used to estimate the increase in irrigated area in winter utilising 10, 20, 30, 40, and 50% of the water yield with an objective to maximize the net return within the constraints of net cultivable area and water availability. Major crops selected for the study sub-basin are mustard, greengram, chickpea, blackgram, brinjal, tomato, and groundnut, which are usually cultivated in the study area during winter. It was found that by utilising 10, 20, 30, 40 and 50% of water yield, the cropping intensity in the sub-basin can be enhanced to 130, 148, 166, 184 and 200%, respectively resulting 49, 69, 145, 193 and 237.5% of increase in net-benefit, respectively than the control (mono cropping system).
Keywords: Water yield, Cropping intensity, SWAT, Linear Programming
150 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-085 Study of Comparative Performance of WEPP and USLE Model For Prediction Of Soil Loss Using Remote Sensing and GIS
N. N. Bandgar*, B. L. Ayare and H. N. Bhange
Department of Soil and Water Conservation Engineering, College of Agriculture Engineering and Technology, Dapoli, Dist- Ratnagiri, Maharashtra *E-mail: [email protected]
The present research work was undertaken to study the comparative performance of Water Erosion Prediction Project (WEPP) model and Universal Soil Loss Equation (USLE) were used for prediction of soil loss using remote sensing and GIS from Karli river catchment of Kudal taluka of Ratnagiri district, Maharashtra. The average annual soil loss from hill slopes and channels was found to be 42.89 t/ha/yr and 8.78 t/ha/yr, respectively. The WEPP model also calculated the sediment yield of Karli river catchment that was17.92 t/ha/yr. The WEPP model predicted 9.01 t/ha/yr more soil loss than the USLE model. The average annual erosivity obtained for study area was 6635.65 MJ- mm/ha-hr-yr. Soil erodibility factor values were estimated using sand (%), silt (%), clay (%), organic matter content (%), structural code and permeability code of each village. Weighted soil erodibility factor for Karli river catchment was found to be 0.041 t-ha-hr/ha-MJ-mm. The value of topographic factor (LS) for Karli
151 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______river catchment was found in the range of 1.81 to 4.53. The crop management factor associated with erosion losses is site specific. Land use land cover was obtained from LANDSAT imageries and field survey. Crop management factor (C) values of Karli river catchment were ranging from 0.024 to 0.12. Considering support conservation practice factor value as 1, soil loss was estimated for Karli river catchment and its micro watersheds using USLE. Along with the prediction of the soil loss by using WEPP model and its comparison with USLE model the sediment yield predicted by WEPP and observed data by Government department was also considered and for the purpose. From observed data, average annual sediment yield was 8.12 t/ha/yr whereas predicted sediment yield from the WEPP model was 17.92 t/ha/yr. which is 120 % more predicted than observed data. The sedimentation rate was also 15.71 % and 34.68% more than the predicted soil loss by WEPP model and for observed sediment yield and predicted sediment yield, respectively. Comparative performance shows that, the WEPP model over estimates the soil loss value and sediment yield value than the USLE model. WEPP model was best suitable model for Karli river catchment due to its less input files, less time consumption, ease to operate and understand, and less data requirement with minimum pre-processed data.
Keywords: WEPP, USLE, Soil Loss, Sediment Yield, Karli River
152 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-086 Advanced Smart Irrigation System based on GSM and Bluetooth-A Case study
Jilakarra* Venkatesh, Killi Srinivas and Dr. K Padma Kumari School of Spatial Information & Technology, JNTUK, Kakinada, Andhra Pradesh *E-mail: [email protected]
Agriculture plays a vital role in developing countries. India being an Agrarian Society, it has great impact of agriculture on the economy of the country. Many issues are hindering the development of agriculture in India. One of the main issue is the proper supply of water without wastage. Water being a very precious resource as only 1% of the world water is fresh water, it has to be conserved. A proper usage of irrigation system is very necessary as large amount of water goes waste. Another issue is the problems faced by the farmers who operate manual pumps at odd hours, especially during nights. There were some fatal cases faced by the farmers. A smart irrigation system is the need of the hour. The highlighting feature of this project includes smart irrigation with smart control and intelligent decision making based on accurate real time field data and monitoring the operation via android application in any smartphone. Present project, irrigation of the field can be remotely control by the farmer (or user) with Android application which has been developed in three modes namely Automatic, Manual and Schedule. In Automatic mode, the
153 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______pump can be controlled based on the moisture level of the soil. In manual mode, the pump can be turn ON/OFF by manually selecting the ON/OFF button in the App. In Schedule mode, one can schedule the irrigation of the field by the android application. The humidity and temperature sensors reports status of current climatic conditions of the field. The benefit of employing these techniques is to decrease human interference, control the water usage and subsequently conserve the water from overexploitation. The system smart irrigation is designed to be assistive to the farmer (or user). Using this “Advanced Smart Irrigation System”, the problems facing by farmers will be mitigated. Keywords: Agriculture, Smart Irrigation, Micro controller, Sensors, Android application, Automatic mode, Scheduled mode, Manual mode, AURDINO.
154 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-087 An Ensemble Based Clustering Approach for Metagenomics Data
Anu Sharma1*, Dipro Sinha2, Anil Rai1, D.C. Mishra1, S.B. Lal1 and Mohammad Samir Farooqi1
1Centre for Agricultural Bioinformatics, ICAR-IASRI 2PG School, ICAR-IARI, New Delhi *E-mail: [email protected]
Metagenomics also known as environmental genomics, eco- genomics or community genomics is the study of microorganisms. Separation and assembly of the genomes obtained from different organisms is a difficult task as they are very large in number and also all the genomics reads are jumbled up. Binning indicates to the process of classification DNA sequences into clusters that might be the true representative of an individual genome or genomes from taxonomically related microorganisms. Shotgun sequencing in metagenomics is widely used to examine the genetic materials and sequence composition of microbial communities. It has been used to rebuild the genomes of individual species. In this study a new methodology has been developed for binning of metagenomics data using correspondence analysis for dimensionality reduction and ensemble based clustering approach. Various codes for this methodology are developed using PHP programming language
155 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______and R software package. The developed methodology might be useful in efficient binning of metagenomics data.
Keywords: Binning, Ensemble, Machine Learning, Metagenomics
Abstract # NCGTA-PP-088 Expert system approach for digital soil mapping of Coimbatore district of Tamil Nadu
Kumaraperumal Ramalingam1*,Ragunath kaliaperumal1, Pazhanivelan S2, Janappriya M3
1Asst. Professor, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 2Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 3Research Scholar, Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
The spatial variations in soil properties and the pedological characterization of soils were done based on its relationship with environmental covariates and other socio-economic factors. The purpose of classification is to understand the complex soil properties and grouping them into similar categories for various uses like agronomic practices. The basic information on soils was
156 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______provided by soil surveyors through conventional survey and laboratory analysis of the field data. These conventional maps lack in detailed information on soil properties and this led to the emergence of remote sensing technology, to potentially extend its soil datasets. A study was conducted to predict the soil class information at subgroup level using decision tree algorithm. Digital soil mapping overcomes the shortcomings in the conventional mapping methods and provides the data on spatial scale. It combines the existing soil data, environmental covariates, classification algorithms, geostatistical models and expert knowledge on deriving the soil class and attribute information. A total of 33 layers of environmental covariates were layer stacked to a common resolution and it was used to predict soil classes by decision tree algorithm. A complete decision tree and rule sets was derived with the help of See5 algorithm to predict soil classes. Based on the rules generated by the algorithm, the digital soil subgroups were generated and it consists of 25 subgroups. Validation of the output was done by generating the confusion matrix between the reference and predicted data. The overall accuracy of the classified map is 79.35 per cent and the kappa coefficient of 0.78 shows that the performance of the classifier is very good.
Keywords: Digital Soil Mapping, Geostatistical models, See5 algorithm, Soil survey
157 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-089 Cloud computing, web services and portal in Geospatial applications TNIAMP Server Ragunath Kaliaperumal1, S. Pazhanivelan2, Kumaraperumal Ramalingam1
1Asst. Professor (SS&AC), Dept. of Remote Sensing and GIS, TNAU, Coimbatore 2Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore E-mail: [email protected]
TNIAMP (Tamil Nadu Irrigated Agricultural Modernization Project) funded by World Bank is a follow up of Tamil Nadu Irrigated Agriculture Modernization and Water Bodies Restoration and Management (IAMWARM) Project. This project will rehabilitate and prioritize tank irrigation systems in 66 sub basins of Tamil Nadu, improved irrigation infrastructure, Crop diversification through high value crops, Climate resilient technologies for improved productivity, Improved market access system of value addition, Institutionalizing Participatory Irrigation Management (PIM) & Improving water management were the major areas focussed in this project. TNIAMP server had been hosted by Department of Remote sensing and GIS, Tamil Nadu Agricultural University in 2019 for Tamil Nadu Irrigated Agricultural Modernization Project. The main purpose of this server is to retrieve geotagged information of interventions from
158 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______sub basins of Tamil Nadu done by line departments of this project and to monitor the progress of each line department over their target at monthly basis.
Keywords: TNIAMP. Interventions, Geotagging, Webserver
Abstract # NCGTA-PP-090 Spatio-Temporal Analysis of Vegetation Variability as a Response to Agricultural Drought Aridity
P.J. Prajesh1, Balaji Kannan2, Kumaraperumal Ramalingam3, S. Pazhanivelan4
1Senior Research Fellow, Dept. of Remote Sensing and GIS, TNAU, Coimbatore. 2Associate Professor and Head i/c, Dept. of SWCE, TNAU, Coimbatore. 3Asst. Professor, Dept. of Remote Sensing and GIS, TNAU, Coimbatore. 4Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore. *E-mail: [email protected] Increasing temperature and altered precipitation pattern has lead to extreme weather events such as the drought. Drought as an extreme climate event has lead to a decline and widespread impact on ecosystem. While vegetation parameters and their response are
159 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______paramount in providing drought related information, understanding drought from multiple perspectives is critical. In this paper an attempt was made to assess analysis and monitor the agricultural drought based on aridity index obtained using geospatial datasets for the state of Tamil Nadu during cropping season of 2018 and 2019. The aridity index map was generated using a weighted combination of three different vegetation indices viz., NDVI, NDWI and MAI which effectively mapped the sensitivity of vegetation towards moisture and precipitation stress. In addition a cumulative rainfall departure statistics, district wise and block wise statistics were incorporated within this work in order to examine the effect of rainfall and agricultural drought severity respectively over the study area. The specific drought assessment summarized that humid, arid and semi-arid regions of Tamil Nadu had been exposed to recurrent agricultural drought of moderate to mild drought during the last two years. The year to year change and spatial distribution of agricultural drought aridity over the arid and humid region agreed to the changes as derived from the meteorological parameters. Therefore, combining the vegetation indices and comparison of meteorological parameters, the study provided an effective understanding of regional agricultural drought aridity.
Keywords: Aridity Index, Drought Monitoring, Rainfall Departure, Vegetation Variability
160 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-091 Crop detection using SAR data Manikandan1*, M.Venkatesan1, B. Sabarinathan2, G. Srinivasan3, S. Pazhanivelan4 1Senior Research Fellow, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 2Research Scholar, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 3PhD Scholar, Dept. of Agronomy, TNAU, Coimbatore 4Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
The aim of this study is to detect the crop by its backscattered curve obtained from the Synthetic Aperture Radar (SAR) imagery. Microwave radar imagery is weather independent and consequently can provide imagery of cloud covered area. Sentinel- 1A, with its C-SAR instrument, can offer reliable, repeated wide area monitoring. Sentinel-1A is a European radar which provides dual polarization capability, very short revisit times and rapid product delivery. The main contributors to radar wave back-scatter are surface roughness or coherent structure relative to the radar wavelength, and soil moisture content. Multi-temporal Sentinel 1A data was used to identify the backscattering dB curve. Multi- Temporal Features viz., max, min, mean, max date, min date and span ratio were extracted from VV and VH polarizations of Sentinel 1A GRD and SLC data will be used for crop classification. Ground truth data from the traditional ground truth
161 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______survey for major crop growing areas of Tamil Nadu was used to extract the dB curve for the each crop. The dB values for rice ranged from -12.76 to -9.95 dB and -19.25 to -15.15 dB in VV and VH polarizations respectively. The signature derived from dB values for maize crop ranged from -21.26 to-13.18 in VH polarization and -14.05 to -6.54 in VV polarization. The backscattering values for cotton ranged from -10.53 to -7.89 dB and -20.59 to -14.53 dB in VV and VH polarizations respectively. Using data from VV and VH polarizations of the SAR data, spectral dB curve was generated for banana crop with the dB values were ranged from -7.426 to -6.082 dB in VV polarization and -13.459 to -12.209 dB in VH polarization. For Mango, the backscattering values were ranging from -10.99 to -5.62 dB in VV polarization, in case of VH polarization the dB values were ranging from -18.57 to -14.15. Likewise, different crops can be detected by using the radar backscattering dB values.
Keywords: Crop signature, dB value, backscattering, polarization
162 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-092 Remote Sensing based Disaster Assessment Assessing Gaja cyclone damaged areas using drones and satellite imageries
S. Pazhanivelan1, Kumaraperumal Ramalingam2, Ragunath Kaliaperumal2, G.R. Mugilan3, M. Venkatesan3
1Professor and Head, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 2Asst. Professor, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 3Senior Research Fellow, Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
Damage caused by Gaja cyclone to Banana and Coconut plantations were assessed drones and satellite by the Department of Remote Sensing and GIS, Tamil Nadu Agricultural University in Lalgudi block of Tiruchirapalli district and Madukkur, Pattukottai and Peravurani blocks of Thanjavur district. The base maps and area statistics of coconut plantations in four districts were shared to support enumeration work by State Department of Agriculture with Web maps containing polygons showing individual plantations. Two Drones of Copter type and Fixed wing were used to assess the damages caused to coconut plantations in Madukur, Pattukkotai and Peravurani blocks. In 11 sorties an area
163 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______of 100 km2 was covered using fxed wing with 8 cm spatial resolution. Large scale damage assessment was done by using Sentinel-1A SLC-radar satellite data acquired during 8th and 20th November, 2018 at 5m resolution. The multi temporal features of span ratio, maximum Increment and minimum increment with coherences were used for identifying damaged plantation. The Preliminary assessment shows that 38.74 lakh trees were damaged in total in Thanjavur, Thiruvarur and Pudukkottai districts. Pattukkottai, Peravurani and Sethubhavachatiram were the major blocks accounting for more number of damaged trees of 830548, 769701 and 603914 respectively. About 38% of banana plantations in 1500 ha area were found to be affected by Gaja cyclone in Lalgudi block of Tiruchirapalli district.
Keywords: Gaja Cyclone, Drones, Damage Assessment, Sentinel 1A
Abstract # NCGTA-PP-093 Wireless and mobile GIS for Agricultural field work TNIAMP - Mobile App G R Mugilan1*, Ragunath Kaliaperumal2, S Manikandan1 1Senior Research Fellow, Dept. of Remote Sensing and GIS, TNAU, Coimbatore 2Asst. Professor, Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
164 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______TNIAMP (Tamil Nadu Irrigated Agricultural Modernization Project) funded by World Bank is a follow up of Tamil Nadu Irrigated Agriculture Modernization and Water Bodies Restoration and Management (IAMWARM) Project. This project rehabilitates and prioritizes tank irrigation systems in 66 sub basins of Tamil Nadu,improved irrigation infrastructure, Crop diversification through high value crops, Climate resilient technologies for improved productivity, Improved market access system of value addition, Institutionalizing Participatory Irrigation Management (PIM) & Improving water management were the major areas focussed in this project. TNIAMP mobile app had been launched by Department of Remote sensing and GIS, Tamil Nadu Agricultural University in 2019 for Tamil Nadu Irrigated Agricultural Modernization Project. The main purpose of this app is to geotag the interventions from sub basins of Tamil Nadu. The information of the beneficiary (farmer), area which the intervention comes under, nearby tank and geotagged photos of the intervention had been given as input to the TNIAMP app that had been connected to the TNIAMP server. These information being used to monitor the progress of each line department that comes under the project and ensuring the farmer had benefitted from the project.
Keywords: Geotagging, IAMWARM, Mobile Application, Interventions
165 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-094 Wireless and mobile GIS for Agricultural fieldwork Mobile App for Geotagging Crop Cutting Experiments
S Manikandan*, PJ Prajesh, A Karthik Kumar Dept. of Remote Sensing and GIS, TNAU, Coimbatore *E-mail: [email protected]
The yield estimates of major crops are obtained through analysis of Crop Cutting Experiments (CCEs) conducted under scientifically designed General Crop Estimation Surveys (GCES). At present over 95% of the production of food grains in India is estimated on the basis of yield rates obtained from the CCEs. The CCEs consist of identification and marking of experimental plots of a specified size and shape in a selected field on the principle of random sampling, harvesting and threshing the produce and recording of the harvested produce for determining the percentage recovery of dry grains or the marketable form of the produce. The information retrieved from CCEs had been used by Insurance agencies, Agriculture and Statistics Department to estimate the production and productivity of crops at village level. In 2018 TNAU had launched CCE mobile app as a part of TNAU NADP - RIICE project by Department of Remote sensing and GIS, Tamil Nadu Agricultural University to ensure the reliability of CCEs related information by geotagging the photos of CCE site and weight of the produce. Prior to the introduction of TNAU CCE app the information retrieved from the CCEs had some drawbacks
166 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______such as data entry errors and it took some time to reach the users (Insurance agencies, Agriculture and Statistics Department). But with TNAU CCE app the information can be utilised quickly as it reaches the server immediately after geotagging of CCEs.
Keywords: Crop Cutting Experiment, Geotagging, Yield estimation
Abstract # NCGTA-PP-095 Delineation of Risk zones for cultivation of rainfed cotton crop using Remotely Sensed Data
Ragunath Kaliaperumal1*, Balaji kannan2, Kumaraperumal Ramalingam1, Pazhanivelan S3
1Asst. Professor, Dept. of RS and GIS, TNAU, Coimbatore 2Associate Professor, SWEC, TNAU, Coimbatore 3Professor and Head, Dept. of RS and GIS, TNAU, Coimbatore *E-mail: [email protected] Water, the most precious natural resource for human livelihood is being mismanaged in all aspects. The increasing need for water has drawn our attention towards sustained management of this resource. Agriculture, one of the major consumer of water is facing crises due to non-judicial use of this resource especially for the rainfed crops. Understanding the natural systems that govern the hydrologic cycle is very important for water resource
167 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______management. Use of remote sensing in water resource management has been widely acknowledged. However, in reality, the operational applications of remote sensing in this area are few. In this study, the applicability of WRSI, a Soil Crop Water requirement integrated method main available remote sensing based techniques used in the assessment of Crop Water Requirement is evaluated.
Keywords: Crop water requirement, Crop coefficient, WRSI, water management.
Abstract # NCGTA-PP-096 Impact of climate change on rainfed maize productivity over Tamil Nadu
R. Gowtham*1, V. Geethalakshmi1, M. Dhasarathan2, K. Senthil Raja3, A. Senthil4 and S. Panneerselvam5 2Agro Climate Research Centre, TNAU, Coimbatore 1,4Directorate of Crop Management, TNAU, Coimbatore 3MANAGE, Hyderabad. 5Director, Water Technology Centre, TNAU, Coimbatore *E-mail: [email protected] A study was conducted to understand the impact of climate change in the mid-century (2040 to 2069) on rainfed maize productivity over Tamil Nadu. The RCP 4.5 and 8.5 was selected to represent the stabilization and over shoot pathways of emission. Future climate was projected through 29 climate models listed in CMIP5,
168 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______out of which five climate models under RCP 4.5/8.5 were selected to represent Cool-Wet (BNU-ESM/ MIROC5), Cool-Dry (CCSM4 / GFDL-ESM2), Hot-Wet (CMCC-CM / CMCC-CM), Hot-Dry (CanESM2/ CanESM2 ) and Middle (CMCC-CMS / HadGEM2-AO) conditions and these model outputs were forced with DSSAT model to simulate the impact on rainfed maize productivity over Tamil Nadu. Adaptation options such as advancing the sowing date and additional nitrogenous fertilizer application were also simulated to understand the possible advantages of adaptation options. TNAU Maize Hybrid CO 6 was utilized in the study, as it is commonly grown by majority of the farmers in Tamil Nadu. Maximum temperature was expected to increase up to 2.7°C while minimum temperature was expected to increase up to 2.9°C. The increase in minimum temperature is higher than that of maximum temperature. Among the monsoons, SWM is projected to be warmer than NEM. Rainfall is anticipated to vary from a decrease of -33.0 per cent to 45.1 per cent. Influence of rainfall on rainfed maize yield was significant across Tamil Nadu (Pearson’s r =0.53). Under changing climate, the rainfed maize productivity is expected to decline to a maximum of 30 per cent from the current yield levels due to climate change. Among the two climate scenarios, the magnitude of decline in yield would be more in RCP 8.5 (30.7 % spread across Tamil Nadu) over RCP 4.5 (10.6 % of Tamil Nadu). Impacts of future climate change could be reduced by altering the date of sowing (early sowing) to September 1st against September 15th (normal sowing) during Rabi under RCP 4.5 and RCP 8.5. Additional dose of (25%) fertilizer had positive response with yield increase up to 15 per cent under future climatic conditions. Though earlier date of sowing and
169 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______supplemental fertilizer application had considerable gains in yield under both current and future climate conditions, their magnitude diminished considerably under future climate conditions. Keywords: Climate Change, Maize, Hybrid CO6, Yield improvement
Abstract # NCGTA-PP-097 Land evaluation of Soils in Semiarid region of Tatrakallu Village of Anantapuramu district in Andhra Pradesh
G. Sashikala*, M.V.S Naidu, K.V. Ramana, K.V. Nagamadhuri, A. Pratap Kumar Reddy and P. Sudhakar Department of Soil Science and Agricultural Chemistry, S.V. Agricultural College, Acharya N.G.Ranga Agricultural University, Tirupati, 517502, Andhra Pradesh *E-mail: [email protected]
A study was undertaken to evaluate fourteen soil series belonging to semi-arid ecosystem of Tatrakallu village (2469.29 ha), Anantapuramu district of Andhra Pradesh for sustainable land use planning. The soil series were Tatrakallu-1 (TTK1), TTK2, TTK3, TTK4, TTK5, TTK6, TTK7, TTK8, TTK9, TTK10, TTK11, TTK12, TTK13 and TTK14 mapped into twenty one soil mapping units and soil map was generated using GIS technique. The
170 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______fourteen soil series were classified into six land capability sub- classes such as IIIs (TTK9 and TTK14), IIIw (TTK11 and TTK13), IIIws (TTK12), IVs (TTK7, TTK5 and TTK10), IVes (TTK3, TTK4, TTK6 and TTK8) and VIes (TTK1 and TTK2). These soil series accounts to an area of 222.24 ha (9.00 %), 333.50 ha (13.50 %), 111.12 ha (4.50 %), 444.47 ha (18.00 %), 333.30 ha (13.50 %) and 1024.46 ha (41.50 %) of total geographical area of village, respectively. Similarly, the soils of study area were grouped into four land irrigability sub-classes namely, 3s (TTK3, TTK4 and TTK7) which accounts to an extent of 449.29 ha (18.19 %) of total geographical area of the village, 4s (TTK9, TTK12, TTK13 and TTK14) which accounts to 521.00 ha (21.11%), 5s (TTK2, TTK5, TTK6, TTK8, TTK10 and TTK11) with spatial extent of 886.00 ha (35.88 %)and 6s (TTK1) which occupy an area of 613.00 ha (24.82 %) of total geographical area of village
Keywords: Land evaluation, land irritability, crop suitability and GIS.
171 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-098 GIS based Analytical Hierarchy Process of Evaluation of Land Suitability of Vegetables and Flowers for Agricultural Sustainability around Thermal Power Plant
Subhas Adak1*, Kalyan Adhikari2 and Koushik Brahmachari3
1Agricultural Training Centre & State Agricultural Management and Extension Training Institute, Ramakrishna Mission, Narendrapur, Kolkata, West Bengal, India. 2Professor, Department of Earth and Environmental Studies, National Institute of Technology, Durgapur,West Bengal, India. 3Professor, Department of Agronomy, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, West Bengal, India. *E-mail: [email protected] . Land suitability of sub-tropical vegetables and flowers for sustainable agricultural planning around the Kolaghat Thermal Power Plant (KTPP) in the district Purba Medinipur, West Bengal, India, has been assessed by using Geographic information system (GIS) based Analytical Hierarchy Process (AHP) model. Pair- wise comparisons among the influential factors in AHP have shown the superiority of the soil chemical properties with the highest relative weight of soil pH (0.186) followed by organic carbon (0.158) and cation exchange capacity (0.139) for determination of sub-tropical vegetables suitability. For
172 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______evaluation of sub-tropical flowers suitability through AHP the highest influencing factor is organic carbon (0.229) followed by soil pH (0.162) and cation exchange capacity (0.136). The Consistency Ratio (CR) is less than 0.1 which validated the pair- wise matrix. Growing of vegetable crops is suitable in 53.11% of total cultivable land. Moderate suitability of vegetables (7259.449 ha) is due to limitations of climate, soil pH and soil organic carbon. Out of total acreage, 88.74 % area is moderately suitable for flower cultivation due to soil chemical properties. Flowers are suitable in 10.39 % of area including the affected areas. With little amelioration flowers can be grown in 88.74 % area around the thermal power plant. This evaluation of crop suitability increases the cropping intensity (CI) more than 300% under any suitable combination throughout the year while at present CI of the study area is only 177.95 %.This estimated potential of land with suitable crops will consequently check soil erosion and suggest proper utilization of natural resources available in the areas which will lead to sustainable agriculture.
Keywords: GIS, AHP model, Land Suitability, Agricultural Sustainability
173 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-099 Spatial and Temporal Variability in Physico- Chemical properties of Vineyard Soil Without and With Application of Fertilizers
D. Vijaya* and G. Ram Reddy Grape Research Station, AICRP on Fruits, SKLTSHU, Rajendranagar, Hyderabad *E-mail: [email protected]
The spatial and temporal variability in soil pH, EC, N, P and K was recorded in a vineyard by comparing with the initial soil variation (2009-10) with the variation resulting from fertilization for 5 years (2014-15). Ten fertilizer treatments were imposed for 5 years, viz through fertigation (80, 50 and 30% RDF) as two different fertigation schedules and conventional soil application replicated four times. The experiment was initiated in the soil with no earlier history of fertilizer application. Initial soil samples were collected from pits dug out for planting vines. Soil was collected from 30 pits and from each pit soil was collected separately from three different depths viz 0 to 30 (top layer), 30 to 60 (middle layer), 60 to 90 cm (Last layer). It was observed that there was spatial variability in the initial soil pH which varied between 5.5 - 6.5 in the top layer in 60 % of the samples, in the middle layer in 40% of the samples and in the last layer in 29 % of the samples. Remaining samples recorded pH > 6.5. With increase in depth the percentage of samples with higher pH (> 7.5) increased from 3 to 15%. Similarly there was variability in EC with 22% of the
174 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______samples in top layer recording > 0.1 dS/m and which increased to 56 % with depth while the remaining samples recorded < 0.1dS/m. The available N also varied from low to medium in top layer with 57 % of the top layer and 100 % of the last layer recording low N status. There was no variation in available P status with depth. Irrespective of the depth Av. P was low in around 54 % of the samples while the remaining samples recorded medium status. The Av K varied from low to medium, with 27 % of the top layer and 52 % of the lower layer samples recording low and remaining medium. After 5 years of imposing fertilizer the treatments, soil samples were collected at two distances viz below the dripper and 30 cm away from the dripper from three depths viz 0 to 15, 15 to 30 cm and 30 to 60 cm. Irrespective of the initial soil pH there was an increase in the soil pH with addition of fertilizers (7.0 - 7.6). The increase was more with fertigation (7.3 - 7.6) as compared to soil application (7.0 - 7.1). The lower rates of fertilizer application (RDF) recorded higher pH (7.5 - 7.6). There was an increase in EC (0.23 – 0.36 dS/m) with addition of fertilizers and the increase was more with higher fertilizer dose (0.32 – 0.36 dS/m) more so with soil application. However, no significant variation in pH and EC was recorded with depth. Very less increase in Av. N was recorded with fertilizer application. Though the increase was less it was significant with higher level of N dose. All treatments recorded high Av.P and K status in the top layer irrespective of fertilizer dose with a steep increase from 10.5 to 178 kg/ha (mean) in case of Av. P and from 139 kg/ha (initial value) to 414 kg/ha (mean) in case of Av K at the end of 5 years fertilization. In case of Av. N and P there was no significant change along the dripper line in the wetting zone however a decrease was recorded with
175 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______increase in depth. While with respect to Av K there was an increase along the dripper line as well as with depth.
Keywords: Fertilizer Treatment, Vineyard Soil, Micronutrients, Spatial and Temporal Variability
Abstract # NCGTA-PP-100 Geospatial Techniques for Studying Spatial Distribution and Spread of Cotton Mealybug
M. Prabhakar1*, M. Thirupathi1, Y.G. Prasad2 and M. Kalpana1
1ICAR-Central Research Institute for Dryland Agriculture, Hyderabad 2ICAR-Agricultural Technology Application Research Institute, Hyderabad *E-mail: [email protected]
Pest and diseases are major constraints that reduce of crop yields. The mealybugs (Phenacoccus solenopsisTinsley), is a tiny sap- sucking insects causing severe economic damage to cotton. Mealybug outbreaks were recorded at several places across India, of which one of the area severely infected was Shayampet mandal, Warangal district, Telangana. Majority of the study area was under cotton crop and most of the weed plants in that area served as alternate host for mealybug. These weeds were found mostly
176 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______along the bunds, road and fallow fields. In this study, satellite data from IRS-Resourcesat-1, LISS IV was used to map the mealybug damage on cotton fields vis-à-vis weed hosts along the roads and their influence on spread of mealybug. Buffer zones of 30metre wide on either side of the road were demarcated and the damage due to the pest was assessed using NDVI threshold values. The results revealed that the adjacent 15 metre buffer zones on either side of the road were more severely damaged due to the presence of weed hosts. Also spatial distribution of mealy bug on four fields with varying severity levels was studied. Intensive sampling of each plant at fortnightly intervals was taken by grading each plant according to severity on a scale of 0-4 (0 is healthy and 4 is very severe). Virtual maps depicting pest severity were generated with latitudes and longitudes corresponding to each plant using ArcGIS10.1. The temporal changes in pest distribution were evaluated using Spatial Analysis by Distance Indices (SADIE) and generated cluster index values for different periods of observation. Contour maps were prepared based on cluster index values in ArcGIS10.1 using interpolation technique. Results showed that cluster index values for cotton mealybug at three different dates was in the range of -6 to 3. Index values of more than 1.5 indicate clustering and -1.5 to 1.5 indicating random distribution. This study demonstrated feasibility of space-borne data and GIS tools to understand real time pest distribution and their population dynamics. Such advanced techniques if deployed might be of great use in future to plan appropriate site specific control measures. Keywords: Pest, Weed, Remote Sensing, Distance Indices and Spatial Analysis
177 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-101 Evaluation of spatial variability of soil nutrients for drought mitigation in arid zone of Deccan Plateau of India using geostatistics and GIS
*R. Srinivasan, Rajendra Hegde, S. Srinivas, B. Kalaiselvi, Amar Suputhra and P.Chandran1
ICAR- National Bureau of Soil Survey & Land Use Planning, Regional Centre, Hebbal, Bangalore 1ICAR -National Bureau of Soil Survey & Land Use Planning, Nagpur * E-mail: [email protected] In arid and semi-arid regions of the world, certain agriculture practices and land management have resulted in poor soils fertility. Distribution of nutrients and quantity are deciding factor of crop productivity in dry soils. A case study was attempted in part of Kadiri, Anantapur distinct of Andhra Pradesh to know the distribution of soil properties, especially plant available nutrients spatially, site‐specific management of nutrients by delineating rating zones to effective strategy for precision agriculture. Altogether, 172 representative soil samples (with geographical coordinates) from surface (0-0.15 m depth) layers were obtained from study area. After processing, soil samples were analysed for pH, electrical conductivity, soil organic carbon, available phosphorus, potassium, sulphur, boron, zinc, copper, iron, and manganese. Soil pH, electrical conductivity, and soil organic
178 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______carbon content had mean values of 7.05, 0.12 dS/m and 0.58%, respectively. Whereas, the mean values of available phosphorus, potassium, sulphur, boron zinc, iron, copper, and manganese concentrations were 14.8 kg/ha, 121.9 kg/ha, 11.54, 0.39, 0.35, 7.38. 0.60 and 6.76 mg/kg, respectively. Geostatistical analysis divulged different distribution pattern of soil properties and available nutrients with strong to moderate spatial dependency. Soil properties showed large variability with greatest variation was observed in pH, EC, B, Cu, Zn. The Stable semivariogram for all soil properties were best fitted by exponential models. The nugget/sill ratio indicates a strong dependence for EC and Zn, moderate spatial dependence for available copper. Soil properties exhibited different distribution pattern. It was observed that the use of geostatistical method could accurately generate the spatial variability maps of soil nutrients in arid zone of Andhra Pradesh.
Keywords: Spatial variability, plant nutrients, Accuracy assessment, Soil properties, arid soils
179 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-102 Plant Leaf Disease Detection Using Deep Learning Methods
Minkesh Gupta* Vikash Magar U. Srinivasulu Reddy
Machine Learning and Data Analytics Lab Department of Computer Applications National Institute of Technology, Tiruchirappalli, Tamil Nadu, India *E-mail: [email protected]
Agriculture plays an important role in the country's economy. In India, 70 percent of the economy is dependent on products based on agriculture and agriculture. In the agricultural product, plant diseases cause major losses. The plant's growth is affected by a number of diseases. It is therefore very important to continue monitoring the plants. In order to avoid such diseases, plants need to be monitored from a very early stage of their life cycle. It is very difficult for a farmer to do manual monitoring on a long field with naked eyes, and it is also difficult to identify different diseases. The task has become easier in the modern era. We can use drones to monitor, and we can use machine learning and deep learning methods to identify and classify plant disease. So, we used an effective method on image data set (Plant Village Dataset) to identify the plant disease. Identifying the plant disease and providing the solution at the right time in the current context can help to save resources and contribute to good crop productivity.
180 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______This work proposes an efficient and flexible solution based on Resnet50 Deep Learning that can extract layer by layer features and finally classify the image. The Resnet model uses the skip connection that also uses original input into the output in each layer that helps solve the problem of gradient vanishing. We use transfer learning with fine tuning in this proposed work, remove the last predicting layer of the pre-trained model and replace it with our own predicting layer While testing, the model showed better results with 97 percent accuracy.
Keywords: Plant Leaf Disease; Agriculture; Deep Learning; Resnet; Machine Learning
Abstract # NCGTA-PP-103
Tomato Plant Diseases Recognition using CNN U. Shailam Kumar* and Srinivasulu Reddy
Machine Learning and Data Analytics Lab National institute of Technology, Tiruchirappalli, Tamil Nadu *E-mail: [email protected] [email protected]
The prevention and control of plant disease have always been widely discussed because plants are exposed to outer environment and are highly prone to diseases. There are several ways to detect plant pathologies. Some diseases do not have any visible
181 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______symptoms associated and farmers can’t recognize it easily. In those cases, normally some kind of sophisticated analysis, usually by means of powerful microscopes is necessary, Farmers use eye observation method to detect the diseases with their experience but it is very hard to detect disease at early stage. Crop diseases are a key danger for food security, but their speedy identification still difficult in many portions of the world because of the lack of the essential infrastructure. The mixture of increasing worldwide smartphone dispersion and advances in computer vision made conceivable by deep learning has paved the way for smartphone- assisted disease identification. Using plant village dataset which is a public dataset of 6355 images of infected and healthy Tomato leaves collected under controlled conditions obtained from, we trained a deep convolutional neural network to identify 5 diseases. The trained model achieved an accuracy of 98.6 % on preliminary model, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path toward crop disease diagnosis on a massive global scale.
Keywords: Tomato Plant; Diseases; Convolution Neural Network; Crop Diseases; Deep Learning
182 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-104 Spatial Variability of Soil micronutrients in Semi- arid Tropics of Tamilnadu Uplands using Geo- Statistics
B. Kalaiselvi*, S. Dharumarajan, M. Lalitha, R. Srinivasan and Rajendra Hegde ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, Bangalore *E-mail: [email protected] Knowing the status of the soil macro and micro nutrients and applying the fertilizer according to the crop need and availability is need of the hour to maintain soil sustainability. Extensive application of high analysis fertilizers without soil testing leads to deficiency of micronutrients and imbalance in soil fertility. In the present paper, an attempt was made to assess the spatial variability of micronutrients (Cu, Fe, Mn and Zn) of Tamil Nadu Upland soils of Palani block, Dindigul district through interpolation technique using measured point observations. Total of 127 surface soil samples (0–25 cm depth from surface) were collected based on land physiography variation, land form and land uses etc. The samples were analyzed for soil reaction (pH), organic carbon content (OC %) and DTPA extractable available micronutrients Iron (Fe), Copper (Cu), Manganese (Mn) and Zinc (Zn). The available copper (Cu) varied between 0.18-7.5 ppm with mean of 1.57 ppm, Iron (Fe) (0.84-169 ppm with mean of 26 ppm), Manganese (Mn- 1.58 to 30.8 ppm with mean of 9.5 ppm) and Zinc (Zn- 0.08-1.56 with mean of 0.42) values showed variations
183 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______with soil cultivation and land use. Soil reaction (pH) registered the lowest Co-efficient of variation (17%), whereas, micronutrients were registered highest co-efficient of variation ranged between 67 and 91 per cent. Experimental semi-variograms were fitted for different models like circular, spherical, exponential and guassian using weighted least square. The model which performed with minimal RMSE and ASE values was interrogated to as best model. Spatial dependence of these nutrients was derived by calculating the nugget-sill ratio. Exponential model was found to be the best fit for pH, OC, Fe and Mn contents, while Guassian model was the best fit for Cu and Zn. The nugget/sill ratio indicates that spatial autocorrelation dependency of soil nutrients. Copper and Manganese showed high spatial dependence (<25%) followed by Iron (Fe) showed moderately dependency (25–57%) whereas, Zinc has shown weak spatial dependence (>57%). Spatial distribution map of soil micronutrients were generated using Ordinary Kriging Interpolation technique under geo-statistical analysis. The generated spatial variability maps will provide idea about the fertility status of unsampled location and will help in selection of appropriate soil management practices to enhance the soil and crop productivity.
Keywords: Spatial variability, Interpolation, Micronutrients, Ordinary kriging, Semi-variogram and Spatial dependence
184 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-105 Application of Remote Sensing & Geospatial Technology in Real Time Monitoring of Crop Growth, Yield Estimation and Precision Agriculture
Himanshu Kumar1*, Magan Singh1, Sateesh Kumar Karwariya1, Sujay Dutta2 and Sanjeev Kumar1
1Forage Research and Management Centre, ICAR-National Dairy Research Institute, Karnal 2ISRO, Space Application Centre, Ambavadi, Ahmedabad *E-mail: [email protected]
Agriculture has great economic importance, particularly in India where real-time reliable information on crop development is necessary to support precision agriculture. Precision agricultural studies aim to implement Decision Support Systems (DSS) for the management of the entire agricultural system with the goal of increasing returns on inputs while conserving resources. Real-time monitoring of agricultural growth and estimation of crop yields is an important practice especially in countries that are the main source of their economy on agriculture. The real-time data is directly related to crop growth and yield estimation. This types of predictions apprised about probable increase-decrease in crop yields and allow the decision-makers to take suitable export and import decision. It will be also helpful for the formulation of better management strategies and agricultural policies. There are two methods for yield estimation: Traditional methods and Remote
185 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Sensing/ Geospatial methods. Traditional methods are often expensive, complex and time-consuming. Hence, it cannot be used on an expanded scale. Therefore, it is required to use cheaper and faster methods for crop growth monitoring and yield estimation. Remote sensing and geospatial technology is playing an important role in providing spatial information on an almost real-time basis, globally. Geospatial technology has the capability to provide not only crop classes but also crop yield estimation. Optical imagery will be used for crop growth monitoring and yield estimation but it is unable in cloud cover condition. In that case, SAR data can be useful for monitoring crop growth and yield estimation in any weather conditions. Therefore, Sentinel-1 (SAR data) satellite imagery is freely available in any cloudy conditions ensures the reliability of data to meet reliable mapping, crop growth monitoring and crop yield estimation. Sentinel-1 SAR data is capable to achieve high accuracy in crop classification and yield estimation. Keywords: Crop yield estimation, Sentinel-1, Remote Sensing, Geospatial, Precision agriculture.
186 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-106 Smart Agriculture based on IoT use Machine Learning P. Mukesh1*, Ms. Nazia Tabassum2, M. Shanmukhi3 1ARIS Cell, ICAR-Indian Institute of Agriculture, Rajendranagar, Hyderabad 2,3Department of IT, Mahatma Gandhi Institute of Technology, Gandipet, Hyderabad *E-mail: [email protected]
The objective of this paper is to boost the performance of the farming sector. In India, farming plays an important duty for development in food manufacturing. Internet of Things (IoT) is a milestone in evolution of modern technology. IoT aids us in many areas among which agriculture is just one of the key ones. With the help of IoT together with Machine Learning in the field of farming, we can raise the efficiency of crop production. Different weather condition specifications are thought about with which the most effective suitable plant to be grown are predicted with the help of supervised discovering like Choice Tree Classifier, Regression. With assistance of different sensing units, the dirt as well as atmospheric conditions are figured out as well as transferred with multi-hop communication to the server in which monitoring of plants' wellness as well as control of irrigation system happens. MAC Schemes are used for the purpose of communication. Keywords: IoT, Machine Learning Algorithms, Weather Condition, Crop Production
187 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-107 Integrated wireless sensor technologies for agriculture crop monitoring
Mamidi Kiran Kumar1*, Perumala Mukesh2 1Dept of CSE, JNTUHCEH, Telangana, India, 2ARIS Cell, ICAR-Indian Institute of Agriculture, Rajendranagar, Hyderabad-30, *E-mail: [email protected],
Human beings depend on agriculture to make their comfortable food in daily life so that agriculture is the primary industry in every country. Nowadays, the technologies emerging to make the planet better and smarter. This is technology based Information age, in which various technologies are there to collect data and explore to identify good recommendations. The majority of the farmers in countries like India are doing agriculture making use of traditional approaches. The traditional approaches always depend on manpower and time to monitoring the crops. While monitoring the crops, some plants may be identified as diseased. The type disease occurred to the plants need to be analyzed instantly and also treated as soon as possible to stop spreading the disease. These traditional approaches may be good in case of small scale agriculture fields, but not at all good for large scale agriculture. Making use of technologies in large scale agriculture fields may create another dimension to reduce manpower, time as well as protect the environment as much as possible. We proposed a new
188 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______concept to monitor the large scale agriculture fields entitled “Integrated IoT based Technologies for agriculture crop monitoring”. This concept may reduce manpower, time, save the environment and provide treatment instantly diseased plants and also stops the spreading of disease in the field which will result in increasing the crop production. This proposal can be implemented by integrating various available IoT based WSN technologies, software applications, drone technologies. Keywords: Agriculture Crop Monitoring, IoT, Wireless Sensors, Drone Technology
Abstract # NCGTA-PP-108 Crop stress monitoring with drones is a new generation technology for Indian agriculture
B.B Nayak* Assistant Professor Agronomy, SBVR Agricultural College, Badvel (ANGRAU) and student of PGD in Geospatial technology –NIRD, Hyderabad
*E-mail: [email protected] The world population has increasing day by day and projected to reach 9 billion people by 2050, so that the agricultural consumption will also increase. There is extreme need to fulfil the food demand of increasing population. Agriculture sector is the most promising sector, dealing with the lot of problems now a
189 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______day’s among that problems inadequate and untimely application of inputs is one of the major problem. The only feasible answer for this urgent call for increased agricultural production must come from technology sector (Techno green revolution). Integration of Emerging technologies such IoT devices such as Unmanned Aerial Vehicles (UAVs), Geographical information system (GIS), Geographical position system (GPS) and spatial decision support system (SDSS), can provide significant potential in Smart Farming and Precision Agriculture applications. By capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield. Such decisions enable the effective application of farm inputs, supporting the four pillars of precision agriculture, i.e., apply the right practice, at the right place, at the right time and with the right quantity. Crop health is a very important factor that needs to be monitored, because significant economic loss of yield and the reduction of quality due to biotic and biotic stress. Timely management of crop stress needs regular field scouting by agronomist and technical knowhow of the deferent crop management practices, However, it is very difficult due to shortage of technical manpower and this can be very time consuming. To overcome this problem acquisition of data from geo tagged fields through drone equipped with multi spectral / hyper spectral cameras and its integration with GIS, GPS and SDSS further it leads to variable rate of application. Drone equipped with multi spectral cameras (RGB+INR+ Red edge) can enable the development of Normalized Difference Vegetation Index (NDVI). The NDVI-
190 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______view of a certain area enables the analysis of the intensity of solar radiation absorption and therefore the condition of the monitored plants. Drone technology as a platform for image data acquisition has brought the NDVI mapping capabilities to a completely new level of accuracy making it possible to monitor the condition of not only plants, but also specific parts of plants. This level of information enables the early identification of early identification of pests, diseases and pests. The precisely mapped and identified issues within a certain area can be addressed with precise and timely applications of fertilizers, pesticides or herbicides. UAV- based data processing technologies use crop imaging information to identify biophysical and biochemical changes in plant biomass and their health. Therefore, stress can be detected in their early stages enabling farmers to intervene in order to reduce losses. Key words: NDVI, Drone, Crop Stress, IOT, GIS
Abstract # NCGTA-PP-109 ‘Internet of Things’ in Agriculture
Shilpa Karat1*, K.C. Anirudh2, Smitha Baby3
1,2MSc Agricultural Extension, Kerala Agricultural University, Vellanikara, Thrissur. 3Asst.Professor, CTI, Kerala Agricultural University, Vellanikara, Thrissur *E-mail:[email protected]
191 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Internet has become inevitable in the modern world. The world had 5 billion connected devices in 2016, which is expected to rise to 50 billion by 2020.The progress in use and access to internet worldwide could be put to productive purposes, especially in the field of agriculture which demands a technological push. Precision farming techniques have been introduced in the last decade to optimize and improve agricultural production. Intelligent use of precision farming can be done through Internet of Things (IoT). The technology of IoT is one of the most innovative tools in synergizing agriculture with technology. The set of physical objects which contain embedded systems that can interact with internal or external environment is referred to as IoT. The structure and functioning of IoT is based on three layers. The perception layer for identification and sensing, networking layer for data transfer and application layer for data manipulation. IoT can be used to connect objects in both a sensory and intelligent manner through combining technological developments in item identification (“tagging things”), sensors and wireless sensor networks (“feeling things”), embedded systems (“thinking things”) and nanotechnology (“shrinking things”).One of the most promising IoT application scenario is precision agriculture. Drones attached with video and global positioning systems are employed in precision agriculture to monitor fertilizer use. IoT enabled water management systems employ Wireless Sensor Networks (WSN) to schedule irrigation. The Radio Frequency Identifiers (RFID) aid in identification and tracking in food supply chain management. Farmers can use IoT solutions to monitor livestock reproductive cycles and the calving process to promote safer and more successful outcomes. Crop diseases can be
192 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______detected in the early stage by using embedded IoT systems. The KISAN (C(K)rop Insurance using Space Technology and Geo- iNformatics) project launched by central government integrates IoT systems in crop insurance projects to avoid delay in insurance claims. Moreover, IoT ensures resource use efficiency and energy conservation through high end technology. IoT based system in agriculture, although proven successful in developed countries, is in a very primitive stage of implementation in India. The major challenge is to spread knowledge and awareness about such systems to various stakeholders, particularly the farmers. Further, the cost of infrastructure modernization and maintenance is another challenge. Limited internet availability and connectivity in India is an impediment for IoT to forge ahead. However, mobile networks, internet and smart phones have already started their penetration towards villages in India building I-ways (ICT infrastructure). This is the right time to seed IoT knowledge in the agricultural sector for realizing the vision of technology driven precision agriculture.
Keywords: IoT, Agriculture, Wireless Sensor Networks, Crop Insurance, KISAN
193 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-110 Modelling rainfall patterns in Karnataka using Seasonal ARIMA models
B.S. Yashavanth1*, M.P. Sharath Kumar2 and S.K. Soam1 1ICAR-National Academy of Agricultural Research Management, Hyderabad 2Professor Jayshankar Telangana State Agricultural University, Hyderabad *E-mail: [email protected]
Karnataka is divided into three meteorological zones viz., coastal Karnataka, South-interior Karnataka and North-interior Karnataka. Coastal Karnataka is the region that receives heaviest rainfall in the state with an average annual rainfall of 3,456 mm followed by South-interior Karnataka (1286 mm). North-interior Karnataka receives just 731 mm average rainfall annually. This study attempts to model the rainfall in these three regions using Seasonal Autoregressive Integrated Moving Average (SARIMA) time-series models. In recent years, SARIMA models have become popular among researchers because of its statistical properties and applicability of well-known Box-Jenkins methodology in the model building process. The monthly rainfall during January, 2001 to December, 2019 (19 years) in the three regions was used in the study. The first 16-year data was used for model building and last 3-year data is used for validating the developed models. Since the ARIMA models require the data to
194 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______be stationary, augmented Dicky-Fuller test was conducted to test the stationarity of the time-series. The series were found to be non- stationary and hence the differenced series were used, which were found to be stationary based on the augmented Dickey-Fuller test. Visual inspection of the time plots also established the stationarity of the differenced data. After obtaining the stationary series, the candidate ARIMA models were selected based on ACF and PACF values. The candidate models were developed and the best model that suits the data was selected based on Bayesian Information Criteria (BIC). The SARIMA models (0,0,0)(1,1,0)12, (0,0,0)(1,1,0)12 and (0,0,0)(0,1,1)12 were found suitable for rainfall data in coastal Karnataka, South-interior Karnataka and North- interior Karnataka, respectively. The Mean Absolute Percentage Error values for both training and validation data sets were calculated and were found to be <5% for all the three series. Looking at the models it can concluded that the rainfall pattern in these three regions are different. This establishes that the SARIMA models are very useful in modelling and forecasting the rainfall in different regions. Keywords: Autocorrelation, Forecast, Goodness of Fit, Rainfall, SARIMA, Stationarity
195 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-111 Image data analytics for assessing the water coverage area in districts of Telangana using Machine Learning Algorithms
K Nagendra Babu*, P.D. Sreekanth, T Raj Kumar, S.K. Soam ICAR-National Academy of Agricultural Research Management, Hyderabad, Telangana, India *E-mail: [email protected]
India is one of the agricultural economy based country and having more than half of its population dependent on agriculture income. Water is root source for agricultural production. Estimating water coverage area through the conventional methods is tedious and inaccurate. To Harness the potential of available water sources for agriculture and for human needs in our country its need to be estimate its area accurately. Advances in spatial technology with high resolution multispectral sensor images has enable the humans to estimate the features like vegetation, water bodies, forestry etc. accurately. However, with conventional methods that estimated the features earlier, cannot able to met the expected accuracy. Human intelligence with machine learning algorithms has opens the path for classifying and estimating the features accurately. Machine learning and Artificial Intelligence based data analytical algorithms in Agriculture applications, has provided best solutions for analysing, classifying the pixels and estimating its area.
196 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Government missions has been implemented for enhancing the water capacity in lakes and ponds and improving ground waters levels for agricultural use in districts of Telangana. Identifying the available water sources and assessing the improvements with government missions its need to estimates to the water coverage area accurately. Machine learning algorithm of Random Forest and Deep learning algorithm of Convolution Neural Networks (CNN) has been used for analysing and classifying water body pixels from high resolution sentinel imageries. Water body pixels are classified and its area estimated using Sentinel images for districts of Telangana. The estimated water coverage area is validated with both the Random Forest and CNN algorithms’ and its accuracy is evaluated with assessment parameters (RMSE, Confusion matrix, F-Score) and kappa coefficient. The historical trends and improvement in surface water and ground water levels of data are also analyzed and validated with interpolation techniques for the districts under Telangana.
Keywords: Remote Sensing, Water bodies, Sentinel, ML, Deep Learning, Data Analytics
197 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-112 Geo-spatial applications in Land Resource Inventory & Land Use planning- case study Sujala of Karnataka
Rajendra Hegde and Ramesh Kumar
ICAR- National Bureau of Soil Survey and Land Use Planning, RC, Bangalore *E-mail: [email protected]
The challenges posed by the continuing degradation and declining factor productivity of the land resource base in many rainfed areas are very site-specific and can be tackled only by addressing the concerned issues at the farm level by evolving a rational, site- specific and viable land use options suitable for each and every land unit. The required data for farm level planning can be obtained by carrying out Land Resource Inventory (LRI) that describes and characterises the nature of land resources, their constraints, inherent potentials and suitability for various land-based rural enterprises, crops. The advent of GIS and Global Positioning System (GPS) has added a new dimension to resources survey and information integration. Through interfacing Land Resource Inventory data with Remote Sensing, Geographical Information System and Global Positioning System, different management scenarios can be processed allowing the resource manager to analyses various management alternatives and come out with the best alternative that would be most optimal.
198 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______For village or farm level planning, cadastral maps showing all the survey numbers occurring in the village with their boundaries forms the ideal base. Quick bird/IRS imagery were interpreted for physiographic delineations which were used as base for mapping soils. The soils were studied in several transects and soil maps prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundaries. Soil map shows the geographic distribution and extent, characteristics, classification, behavior and use potentials of the soils in the micro-watershed. From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated. Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 320 m grid interval and suggested interventions were recommended for the low medium/ deficient areas. Land suitability for growing major agricultural, horticultural and plantations crops was assessed and maps showing the degree of suitability along with constraints were generated. Sujala was implemented in a consortia mode with 14 national and state departments. Land resource information generated through LRI in conjunction with climate, agro-hydrology and socio-economic data housed in the Digital Library and Land Resources Portal helps immensely in planning and development of watersheds on scientific basis. The various interpretative and thematic maps generated from the master soil map are land capability, soil depth, soil texture, gravelliness/stoniness, AWC, slope, erosion, soil fertility status (macro and micronutrients), soil and water
199 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______conservation including drainage line treatment plans, land suitability for major crops and suggested land use plans. The data base generated at land parcel/survey number on land resources have been digitized and housed in the Digital Library. This database is disseminated and made available to various line departments and other development agencies on a real time basis through a delivery mechanism of Land Resources Portal. Further the data base is used in developing Decision Support Systems (DSS) that gives different management options and alternatives for each of the land management units. Keywords: Geo-spatial applications, Land Resources Inventory, Land Use Planning, LRI-Decision Support System, Land Resources Portal.
Abstract # NCGTA-PP-113 Identification of suitable location for cultivation of medicinal plants in Telangana using Geo-Spatial Tools
N. Sivaramane*, Ranjit Kumar, P.D. Sreekanth and K.V. Kumar
ICAR-National Academy of Agricultural Research Management, Hyderabad *E-mail: [email protected]
Traditional form of health care is still popular in India and a large section of population is dependent on it. This traditional system, which includes Ayurveda, Yoga and Naturopathy, Unani, Siddha
200 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______and Homoeopathy, abbreviated as AYUSH, is also known as alternative system of medicines. The area and production of medicinal and aromatic plants in India is 499 thousand hectares and 926 thousand tonnes, respectively while that of erstwhile Andhra Pradesh (including Telangana) is just 1.88 thousand hectares and 3.5 thousand tonnes, respectively (Govt. of India, 2016). After the bifurgation, a major chunk of land under medicinal plants was left in Andhra Pradesh while very less land left in Telangana. Telangana is a hot bed of medicinal plants with over 2000 species of medicinal plants, of which, many of them have immense commercial value. To usher production of medicinal plants, Telangana State Medicinal Plants Board (TSMPB) has taken several efforts to promote cultivation of these crops. This study was taken up to identify locations suitable for cultivation of commercially important medicinal plants, viz., Aswagandha, Aloe vera, Mucuna, Tulsi, and Vacha. The factors which influence cultivation of suitable for the cultivation medicinal plants, such as rainfall, soil type, temperature and pH were collected from existing literature and used in the study. Map overlay analysis was employed to classify each district into more, moderately and less suitable for the cultivation of each selected medicinal crops. In this approach, forest lands were culled out and using cost of cultivation of medicinal crops, areas where commercially important crops like fruits and vegetable were grown whose profitability was higher than that of medicinal crops, were shown as less suitable. The district wise maps depicting suitability of selected medicinal plants were created. These findings will be useful for administrators and business managers involved in the promotion of medicinal plants in Telangana to
201 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______promote cultivation of these crops in areas which is more suitable for its cultivation. Keywords: Geo-spatial tools, Map Overlay technique, Medicinal plants, Business management.
Abstract # NCGTA-PP-114 GIS based Decision Support Systems for Sustainable Development of Major Fruit Crops in India
Sweety Sharma*, B. Raghupathi, Rupan Raghuvanshi, B. Padmaja, S. Rakesh
ICAR-National Academy of Agricultural Research Management, Hyderabad, Telangana, India *E-mail: [email protected]
An analysis of area and production in India was done to critically analyses the status of horticultural fruit crops in India. India among the foremost countries in horticulture production, just behind China and occupies first position in the production of fruits like mango, banana, papaya, sapota, pomegranate, acid lime and aonla. It was observed that the area and production under horticultural crops increased. It was estimated that the area and production scenario of different fruits in India indicates that all the fruits occupied 6480 thousand ha area with 92846 thousand MT production and 14.3 MT/ha productivity during 2016-17.Andhra Pradesh has emerged as the second largest fruit producing State in
202 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______the country and its share accounts for 11.8% of total production of fruits in the country. The total horticulture production has increased from 211.2 million tonnes in 2007-08 to 311.71 million tonnes in 2018-19. It can be inferred that future area of horticultural crops would be further increased. Within this probable induction in the area & production of the horticultural major fruit crops. Soil condition also affects the production of the fruit crops in India. Most fruit plants like slightly acidic to neutral soil reaction (pH 6-7). Some fruit species can sometimes tolerate little more acidic or alkaline medium but too acidic or too alkaline soil should be avoided. It is also observed that, the geospatial techniques effectiveness for developing decision support systems (DSS)making in horticulture domain can be improved by integrating geospatial information and advanced information technology techniques are also important for: a) Identification of most suitable locations; b) Disease & pest control planning; and c) Supply chain management and rural transport aggregator services. It concluded that, significant progress has been made in area expansion resulting in higher production. Over the last decade, the area under horticulture grew by 2.6% per annum and annual production increased by 4.8%.
Keywords: Horticulture, fruit crops, GIS, DSS, Area &Production
203 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-115 GIS & Agricultural Education for Quality Improvement
Rupan Raghuvanshi*, B. Raghupathi and Sweety Sharma
ICAR- National Academy of Agricultural Research Management (NAARM) Hyderabad, India *Email:[email protected]
Geographical Information Systems (GIS) can be used efficaciously at various level of agriculture. The methods of GIS connected with mathematics, physics, geography and earth sciences. GIS is a technological tool for comprehending geography and making intelligent decisions. Currently the need of GIS at university level is increased drastically. Since a decade most of the agricultural universities offering GIS and Geo informatics as informal education. But, after the 5th Deans Committee report of Indian Council of Agriculture Research (ICAR), GIS education at bachelor degree level was made compulsory. The vision beyond the implementation of GIS as a subjects is that to enhance the agricultural student’s ability to think critically and analyzing the data and improving the map literacy among the students to understand the location information. Further, it will lead to successful crop area estimation & monitoring and mapping of resources for effective farm planning. Now National Agricultural Higher Education project was running to strengthen the Indian Agricultural education system by
204 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______providing high quality agricultural education to students. The Four key component of NAHEP is running in various agricultural universities; The first component Institutional Development Plan (IDP) is being implemented in 15 agricultural universities; Second component Centre for Advance Agricultural Science & Technology (CAAST) is implemented in 14 agricultural universities and third Component Innovative Grants (IG) is being implemented in 17 Universities and forth one is Investment in ICAR Leadership in agricultural Higher education. So total 46 Agricultural universities are covered directly under NAHEP out of 73 agricultural universities. GIS can be used to prepare and manage the project data and build geospatial snapshots from these universities and reduce the complexity of management. In agricultural Universities mapping geographical information represents interdisciplinary collaboration. GIS developed Crop- specific maps, created by combining survey data and satellite images, provides the lay of the land for farmers, entrepreneurs and agribusinesses such as seed and fertilizer companies. GIS Application in agriculture education can facilitates the timely management of different courses, teaching materials among the students. With GIS, Agriculture students learn to be strategic and connect spatial strategies to business principles in agriculture. Creating maps for audience demographics, practicing research and analysis, and developing into business information and spatial logistics, these are all essential GIS elements that, when applied in the higher education classroom and carried into a career, help students become strong decision-makers, analyzers, entrepreneurs and leaders. GIS application in agriculture education can start with analyzing demographics, plotting pins and segmenting
205 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______agricultural data. Teachers can use GIS as a tool for classroom projects that require students to work with a local agricultural business on marketing strategies informed by geographic trends. So, NAHEP give a wide platform to promote the use of GIS in agricultural education to increase faculty performance, improve student learning outcomes and raise their prospectus for future employability. Keywords: GIS, Agriculture, Student and NAHEP
Abstract # NCGTA-PP-116 Agricultural drought monitoring using SPI and NDVI in mid hills of Uttarakhand: A study in Mid Himalaya of Uttarakhand, India Utkarsh Kumar*, Sher Singh, J.K. Bisht, A. Pattanayak ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan Almora,Uttarakhand, India *E-mail: [email protected] Agriculture in hill and mountain ecosystem is predominantly rainfed with common occurrence of moisture stress. Due to erratic rainfall and adverse topology in Himalaya region, agricultural drought has become a prime concern. It is a natural disaster which evolves in time and their impacts generally last a long period of time. This condition originates due to inadequacy of rainfall or unavailability of irrigation facilities to fulfil the normal water requirements in the context of the agro-climatic conditions
206 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______prevailing in a particular area. The application of drought index analysis is useful for drought assessment to consider adaptation and mitigation method in order to deal with climate change. The occurrence of drought is mainly derived by climatic condition which cannot be eliminated. Among the several proposed drought monitoring indices, the SPI has found a widespread application for describing and comparing droughts at different time period with varying climatic conditions. In the present study long term rainfall data (1985-2016) were used for monitoring agricultural drought through Standardized Precipitation Index (SPI). Year 2005 and 2011 were found to be worst drought year having least average seasonal Normalized Difference Vegetation Index (NDVI). Monthly SPI values were calculated at the time scale of 1, 3, 6 and 12. The present study attempts to characterize the agricultural drought using SPI of Hawalbagh area of Almora district located in Kumaon region in Uttarakhand state of India using remote sensing and climate variable integrated approach. The study will help in formulating policies and strategies based on local and national level drought analysis. Keywords: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Rainfall Anomaly Index (RAI), Agricultural drought, Himalaya region
207 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-117 Application of Cloud Computing and Web Portals in Agricultural Education Seema Kujur*, K.Akhila and V.V. Sumanth Kumar ICAR- National Academy of Agricultural Research Management, Hyderabad *E-mail: [email protected] Application of the technology in education plays an important role in the teaching learning process. In the changing environment, it’s important to implement the needed technologies which will help the academia with better teaching and learning process. In the present scenario Cloud computing and web portal are the useful technologies which is highly implemented in education. Cloud- based applications can reduce infrastructure and IT costs by which it increases accessibility, enable collaboration and allow organizations more flexibility to both teachers and students. Most of the educational institutions are turning to the use of cloud services, because they are extremely effective alternative for providing the high quality resources and services to all participants in the learning process at an affordable price.
Introducing latest technologies (Cloud computing and Web portals) is an innovative way which may encourage students to develop skills and knowledge necessary for achieving their academic and professional goals. We at the academy have implemented Cloud based individual and independent instances are very useful for enhancing the effectiveness of Teaching – Learning Process, by creating a win-win situation for both the teachers and students. These cloud based independence instances are available 24 X 7 at pjtsaunaarm.com and can be modified at
208 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______the will of the end user and the module is specific to him/her. These cloud based instances have good impact as evidenced in the survey organized with PGDMA students of the academy. The increased adoptability is from batch to batch and year by year need to be underscored. These independent cloud based software instances solved many challenges aroused when single local instances were provided.
Key Words: Cloud Computing, Web Portals, Technology, Agricultural Education
Abstract # NCGTA-PP-118 Geospatial Technology: A Gateway for Precision and Sustainable Agriculture S. Rakesh*, B. Raghupathi, S.B. Khade, R. Raghuvanshi, S. Sharma, B. Padmaja and R.P. Divakar ICAR-National Academy of Agriculture Research Management, Hyderabad, Telangana, India *E-mail: [email protected]
The green revolution during 1960’s has made our country achieve self-sufficiency in food production. As a result, the production has increased two to three folds due to the application of excess fertilizers, pesticides, irrigation, high input responsive crops, increase in cropping intensity and mechanization of agriculture system. Indeed, green revolution has contributed a lot to our country but failed to attain the potential productivity even with this spectacular growth. Since this revolution in agriculture is also
209 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______associated with the environmental consequences. The emission of greenhouse gases (GHGs) like carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbon (HFC) etc. due to the excessive use of chemicals in agriculture increasing the effect of global warming on farming community. Burgeoning population growth, food demand, erratic rainfall patterns, droughts, flash floods, land degradation, drinking water crisis, occurrence of pest and diseases, malnutrition, health impacts etc. are alarming us the critical need of precision and sustainable agriculture. Besides these environmental and health impacts, the prices of cereals (rice, wheat and corn) which are considered as staple food crops for human life are also being doubled. Now the time has come to face the greatest challenge of achieving sustainability in agriculture system without impairing the environmental quality. Sustainable agriculture depends on the judicious management of available resources like soil, water, climate, rainfall, forest, livestock etc. with the acceptable technological approach. Application of technology to improve the effectiveness and efficiency of farming practices has increased tremendously. Geospatial technology is an emerging field that includes remote sensing (RS), geographical information systems (GIS) and global positioning systems (GPS) enables the stakeholders to acquire data and use it for analysis, modelling, simulations and visualization. Discoveries in the field of science and technology have enabled farmers through a guarantee effective and efficient input management that maximize their outputs and profits. Farmers can be able to understand the site-specific needs of their own farm. Assistance of advancements like sophisticated machineries, use of fertilizers, herbicides, and pesticides as well as planting practices in GIS tools further
210 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______enhance their effectiveness. Monitoring the soil moisture levels, crop type, crop stage, crop vigour, pest and disease occurrence, maturity stage etc. are the effective applications of this special tool. Collectively, geospatial technology provides direct information on the indicators of production that aids in managing the available natural resources efficiently. In present modernized life, the success of large-scale farming is depended on geographic information technologies through precision, conservation and climate smart agriculture. If we enable rural farmers to adopt climate-smart practices, it will not only decline the hunger and poverty but also brings sustainability in agriculture system and environment. Keywords: Geospatial Technology, Climate Ch0ange, Precision farming, Sustainable Agriculture.
211 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-119
Application of Geographical Information System in Management of Agrobiodiversity Resources of AP and Telangana
M. Balakrishnan*, S.K. Soam and P.D. Sreekanth
ICAR-National Academy of Agriculture Research Management, Hyderabad, Telangana, India *E-mail: [email protected]
The present study is envisaged to assess Agricultural biodiversity is a broad term that includes all components of biological diversity of relevance to food and agriculture, and all components of biological diversity that constitute the agricultural ecosystems, also named agro-ecosystems: the variety and variability of animals, plants and micro-organisms, at the genetic, species and ecosystem levels, which are necessary to sustain key functions of the agro-ecosystem, its structure and processes. Geographical Information system can play an important role in the management of large and complex agrobiodiversity, design and management datasets. The major areas in which uses of GIS described are inventorisation/mapping, exploration/collection, conservation and crop expansion strategies. GIS technology can be effectively used in planning field explorations for collecting agro-biodiversity resources in AP and Telangana, the participating scientists of this
212 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______project felt it important to catalogue and develop a database of information comprising the available agrobiodiversity information in AP and Telangana. Objectives, historical development, structure, functionality, content, utility and future prospects of the Agro Biodiversity Knowledge Management Portal(ABKMP) are described in the portal. Online portal is designed to cater for the needs of researchers, policy makers, development practitioners, teachers, students and farmers in developing countries for efficient access to available published and grey literature from past and present research results on the origin, distribution, diversity, present use and status of agro biodiversity resources of AP and Telangana. It is currently available, free of charge, on the web. It is argued that information on the extent of existing crop diversity, characteristics and use of ABKMP in developing countries is the basis for their present as well as future sustainable utilization. In developing countries, neglect and lack of accurate information on the diversity and status of the agrobiodiversity resources are believed to exacerbate the alarming rate of irreversible loss of genetic diversity. The database named as ABKMP has been developed and it was published in the NAARM Website. Any one can easily access the database for retrieving the information’s.
Keywords: Agro Biodiversity, GIS, My-SQL, Drupal, Cereals, Minor Millets
213 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______Abstract # NCGTA-PP-120
Consumption of Fertilizer Nutrients in Telangana and its Percentage Variation over Previous Year
Pannala Divakar Reddy*, Padmaja B. and Shrikant Khade
*E-mail:[email protected]
Geospatial technologies play an influential role in the agriculture sector by increasing yields, managing of resources, prediction of outcomes and improving farm practices. GIS-GPS-RS technologies are used in combination for precision farming/site- specific crop management. Precision agriculture (PA) is an approach to farm management that uses information technology (IT) to ensure that the crops and soil receive exactly what they need for optimum health and productivity. The secondary data collected from fertilizer association of India and in that consumption of fertilizer nutrients percentage (N, P2O5 and K2O) and variation was taken into account for Telangana state during 2018-19. In India consumption of nitrogen was 17637 MT, P2O5 consumption was 6910 MT and 2680 MT consumption in case of K2O. The fertilizer consumption percentage over previous year nitrogen and P2O5 was in positive variation i.e. 4.0 per cent and 0.8 per cent. Whereas K2O consumption percentage variation was reduced by 3.6 percent as compared to previous year. In Telangana, the consumption of nitrogen was 888 MT, P2O5 was 343.1 MT and in case K2O it was 114.5MT. The consumption percentage in nitrogen and P2O5 as compare to previous year it was
214 National Conference on Geospatial Technologies in Agriculture 20-21 Feb. 2020 ______reduced by 0.9 and 1.7 percent respectively. Similarly, the variation was 21.6 per cent in case of K2O which was shown significant difference as compared to N & P2O5 fertilizers. Application of sensing with a focus on plant specific information to provide information on crop development, fertilizer equipment, soil moisture, soil structure and nutrient management can be helpful in regulating the fertilizer application. Increased sophistication of agricultural information systems that benefit both farmers and government.
Keywords: Geospatial, resources, nutrients, fertilizer, variation.
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