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Land Potentiality Investigation for Agroforestry Purpose Using Remote Sensing and GIS Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1683-1691 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 11 (2020) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2020.911.201 Land Potentiality Investigation for Agroforestry Purpose using Remote Sensing and GIS Firoz Ahmad1, Mohammad Shujauddin Malik1, Shahina Perween1, Nishar Akhtar1*, Nazimur Rahman Talukdar2,3, Prakash Chandra Dash4, Sunil Pratap Kumar5, Laxmi Goparaju5, Firoz Ahmad5 and Abdul Qadir6 1Birsa Agricultural University, Kanke, Ranchi, Jharkhand, India 2Wildlife Conservation Laboratory, Department of Ecology and Environmental Science, Assam University, Silchar, India-788011 3Centre for Biodiversity and Climate Change Research, Udhayan, Hailakandi-788155, Assam 4Xavier Institute of Social Service (XISS), Ranchi, Jharkhand 5Vindhyan Ecology and Natural History Foundation, Mirzapur, Uttar Pradesh, India 6Department of Geography, Punjab University, Chandigarh-160014, Punjab, India *Corresponding author ABSTRACT The study applied the soil, land and topographic data for analyzing the potentiality of land for trees /crops suitability in the Gumla district of Jharkhand, India. The remote sensing, GIS and K e yw or ds GIS modeling techniques were used to achieve the goal. The soil fertility, soil wetness, and slope map are scientifically produced and integrated to find out the landscape suitable Land potentiality, categories for prioritization of trees/crops scaling in the agroforestry domain. Additionally, we Remote sensing & have examined the drift of loss of soil wetness using satellite data from monsoon to post- GIS, Soil fertility, monsoon period up to the village level. The analysis logically revealed the potentially suitable soil wetness, landscape (28%: high; 38%: medium; 25%: low and 9%: very low) for tree/crop farming. The Jharkhand seasonal drift of soil moisture loss after monsoon season was found highest in village Mahugaon followed by Pahladpur, Jalka, Itkiri, Shiwserang, and Gamhariya. Furthermore, 40% Article Info of the total villages of the study area showed soil wetness loss from medium to very high during the same base period which needs intensive soil and water conservation measures at the Accepted: watershed level to conserve seasonal rainwater. These efforts will improve the soil moisture 12 October 2020 and water availability for plants and support significantly in extending agroforestry Available Online: exercise/design/ management locally. Such analysis/results are one of the potential research 10 November 2020 gaps can be harnessed for the betterment of cultivators/farmers in the tribal-dominated region using local knowledge for designing appropriate agroforestry practices/models and can be incorporated in various ongoing and future projects. Introduction practices in which woody perennials are deliberately integrated with crops and/or The ICRAF has defined the agroforestry as animals on the same land management unit.” “the collective name for land-use systems and (Leakey, 1996) 1683 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1683-1691 Why agroforestry is important? 2007; Zomer et al., 2014; Ahmad et al., 2018a). Such analysis /investigation/ results It has the capacity to improve livelihood and have the enormous potential to support mitigate poverty significantly among the rural crucially the agroforestry policy of India people by enhancing the diversified output (NAP, 2014) and building resilient landscapes such as food, fruit, fodder, fuel, fertilizer and for achieving various sustainable fibre by exploring the indigenous traditional development goals (SDGs) set by FAO knowledge. Additionally, it meaningfully (http://www.fao.org/sustainable-development- support rural invention plan by addressing the goals/en/). multifunctional goal of income generation, employment and food security which is the The study area selected is the Gumla district backbone of Indian economy. of Jharkhand state of India because of the adequate dominance of ethnic tribes and the It’s one of the successful environmentally majority of people suffering from diminishing positive alternatives to mitigation strategies to livelihood, poor income, and drought (Ahmad fight with the climate and environmental et al.,2018c) will be greatly benefited from change impact. our research findings if applied at the local level. Agroforestry bringing the resources of the forest onto the farmland thus prevent The objective of the study is to apply the soil, deforestation, enhance the soil quality, land and topographic data using remote ameliorating air/water quality and magnify sensing, GIS and GIS modeling techniques biodiversity. for analyzing the potentiality of land for trees /crops suitability towards agroforestry in Due to advancements in computer science, the Gumla district of Jharkhand, India. The study availability of remote sensing and GIS further investigated the seasonal drift of soil datasets and improvement in various moisture up to the village level. scientific/logical approaches in diversified studies in recent times has magnified the Materials and Methods mapping technique several-fold. The application of computer science can be The study area significantly supported in the agricultural revolution by encouraging farm management The study area Gumla is one of the tribal- by improving production (Paarlberg and dominated districts of state Jharkhand have Paarlberg, 2000). A GIS-based database geographical coordinates with latitude 22 º 42' management approaches are used in the past 02'' N to 23 º 36' 29''N and longitude 84º 01' for agroforestry planning and tree selection 51''E to 85º 00' 56'' E and surrounded by the (Ellis et al., 2000). Successful planning and districts of Latehar and Lohardaga in the design of agroforestry management practices north, by the districts of Ranchi and Khunti link on the ability to pull together very on the east, by the district of Simdega on the diverse and sometimes large sets of several south and by the State of Chhattisgarh on the spatial scales information (Ellis et al., 2004). west. The study area is full of hills and a Such design can be utilized in the decision- hillock with elevation varies from 385 to 1130 making process for modeling agroforestry m from the mean sea level with the highest related study at the local, regional and global land area is Netarhat. The annual mean levels (Ritung et al., 2007; Reisner et al., temperature is about 23 °C whereas annual 1684 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1683-1691 rainfall varies from 1400 to 1600 mm (Kumar Management & Extension Training Institute, et al., 2018). There are three main rivers such Jharkhand. (https://www.sameti.org/Soil_ as South Koyel, the North Koel and the Sankh Inventory/Gumla_Soil_Map.pdf) and rest flow in this area. The majority of land soil is from the portal of the USGS website laterite with low soil fertility. The major (https://earthexplorer.usgs.gov/.). occupation of the people is agriculture, animal rearing, NTFP, and mining activities. Additionally, we have used the village Agriculture activities in the farm are boundary (Meiyappan et al., 2018) and the threatened due to drought/poor soil district boundary of Gumla moisture/climate change impact. The climate (https://www.diva-gis.org/gdata) to carry out changes have a significant impact on tribal our analysis/result. All five types of soil maps people (Minj, 2013) because of their weak were rectified with district boundaries and adaptive capacity. The agriculture activities were brought into to GIS domain (Ahmad et are mainly monsoonal rain based supported al., 2017a). In each soil map, the various soil by poor irrigation facility whereas the categories were digitized and polygon ids availability of fodder to the animal is low to were given (Ahmad and Goparaju, 2017b). very low especially in the villages which are away from the forest area. The migration of The soil fertility map (Figure 6) was people from rural areas to the city is highest generated by integration of all soil layers in this district (Singh et al., 2007) because of (Figure 1 to Figure 5) by giving equal weight the weak socio-economic condition mainly to all. We have used the formula provided by due to industrial backwardness with Baig et al., (2014) mentioned in Ahmad & diminishing livelihood and poor income/ Goparaju (2017a) for deriving the wetness employment source. The approximately one- map (Figure 7). fourth of the areas are surrounded by forest which is gradually degrading due to DEM was used to generate the slope map continuous mining activity and/or conversion (Figure 8). The Erdas imagine and ARC/GIS of the forest land to agriculture purposes. The software was used to bring various datasets to major tree species are sal (Shorearo busta), the right format to execute our objective mahua (Madhuca longifolia), asan meaningfully. (Terminalia tomentosa), gamhar (Gmelina arborea), simal (Bombax ceiba) mango Land potentiality mapping for agroforestry (Mangifera indica), neem (Azadirachta indica), etc. are generally found whereas The potential layers such as soil fertility, soil mahua and sal trees are deeply associated wetness and slope map which play a with the tribal life and their festival. significant role in plant nutrient regulation and their metabolic activity for adequate Data preprocessing and analysis growth are integrated logically in the GIS domain for achieving the final agroforestry The data used for this study were
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