Assessment of Land Use Land Cover Classification Through Geospatial Approach: a Case Study of Mysuru Taluk of Karnataka State, India
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Journal of Environment and Waste Management Vol. 7(1), pp. 326-338, June, 2020. © www.premierpublishers.org, ISSN: 0274-6999 Research Article Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India *Manjunatha M.C.1, Basavarajappa H.T.2 1Department of Civil Engineering, Maharaja Institute of Technology, Thandavapura, Mysuru-571 302, India 2Department of Studies in Earth Science, Centre for Advanced Studies in Precambrian Geology, University of Mysore, Mysuru-570 006, India Earth's land use/land cover (LC/LU) classification provides valuable information particularly on natural resources, mapping and its monitoring. There is a significant change on LC/LU across the globe due to the climatic changes, rapid increase in population and over demand of economic natural resources. Remote Sensing (RS) satellite data with its synoptic view and multispectral data provides essential information in proper planning of LU/LC conditions of larger areas. The study aims to map and monitor the existing LU/LC classification scientifically using geospatial tools in database generation, analyses and information extraction. Thematic maps of the study area are prepared using satellite images in conjunction with collateral data Survey of India (SoI) toposheets, forest and wasteland maps. An attempt have been made to delineate the Level-I, Level-II and Level-III LU/LC classification system through NRSC guidelines (2011) using both Digital Image Processing (DIP) and Visual Image Interpretation Techniques (VIIT) by GIS software’s with limited Ground Truth Check (GTC). More accurate classification is observed in case of digital technique as compared to that of visual technique in terms of area statistics. The final results highlight the potentiality of geospatial technique in optimal and sustainable land use planning of natural resource and its management. Keywords: Geospatial technology; LU/LC Classification; IRS-1D, LISS-III Image;Mysuru taluk. INTRODUCTION LULC classification provides vital inputs required for al., 1996). LU/LC exposes considerable influence on the socio-ecological concerns and optimal use of land various hydrological aspects such as interception, resources for the developing countries like India (Sharma infiltration, catchment area, evaporation and surface flow et al, 2018). The main resource controlling primary (Sreenivasalu and Vijay Kumar, 2000). productivity for terrestrial ecosystems can be defined in terms of land: the area of land available, land quality, Indian Remote Sensing (IRS) has been extensively moisture regime and edaphic character (Sharma et al, utilized for Satellite data acquisition at periodic intervals to 2018). Changes in LU/LC affect global systems or occur monitor the land resources and to evaluate the land use/ in a localized fashion in enough places to have a land cover classification & its impact on natural land significant effect (Meyer and Turner, 1992).LU/LC resources (NRSA, 1995). The spatial information of agro provides a better understanding on the cropping pattern ecosystem modeling (Lenz-Wiedemann et al, 2010) yields and spatial distribution of fallow lands, forests, grazing estimation (Vibhute and Gawali, 2013) subsidy control lands, wastelands and surface water bodies, which is vital for urban developmental planning and management *Corresponding Author: Manjunatha M.C, Department (Philip and Gupta, 1990). Despite successful substitution of Civil Engineering, Maharaja Institute of Technology, of land-based resources with fossil fuels and mineral Thandavapura, Mysuru-571 302, India. resources, land remains of prime importance (Darwin et Email: [email protected] Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India Manjunatha and Basavarajappa 327 (Schmedtmann and Campagnolo, 2015) and retrieval of scheme today, consists of multiple levels of classification biophysical plant parameters on regional scales is not designed to be compatible with different levels of details sufficient (Zhao et al, 2015). For numerous agricultural (Tammy and James, 2015). It is comprised of a hierarchal applications and differentiate crops is a demanding task, grouping of three levels, allowing for applicability at as different crop types have similar reflection properties in multiple resolutions. Level-I can be used when finer remote sensing images for some periods of the year details are not needed, such as for national or regional (Waldhoff et al, 2012). Increasing human interventions scales, and is more appropriate for land cover and unfavorable bio-climatic environment has led to identification. Yet, Level-II and Level-III is available when transformation of large tracts of agricultural land into finer detail is needed at a local scale and can be more wasteland (Basavarajappa et al, 2019). Due to the lack of readily described as land uses (Tammy and James, appropriate land cover data, many assessments have 2015). Without a standard classification framework, it is used models to delimit potential land cover (Alexandratos, difficult to identify changes occurring over time, compare 1995). Information describing current land cover is an between places, and to avoid duplication of efforts. important input for planning and modeling, but the quality of such data defines the reliability of the simulation outputs (Townshend, 1992). Proper land management and STUDY AREA development should be initiated to increase the land productivity, restoration of soil degradation, reclamation of It is located in between 12007’05” to 12027’13” N latitudes wastelands, and increase in environmental qualities and and 76027’12” to 76050’10” E longitudes with the general to meet the needs of rapidly growing population of the elevation of 770 mts above MSL covering an area of country (Manjunatha and Basavarajappa, 2015b). 805.63 km2 (Figure 1). Tourism is the major industry alongside the traditional industries in Mysuru taluk. The Land use classification is the systematic assessment and study area lends its name to various art forms and culture, alternatives for optimal land use to improve socio- such as Mysore Dasara, Mysore Painting; Mysore Pak economic conditions (FAO, 2017). Land-use classification (sweet dish), Mysore Masala Dosa; brands such at appropriate scales increase their productivity, support as Mysore Sandal Soap, Mysore Ink; and styles and sustainable agriculture & food systems, promotes cosmetics such as Mysore Peta (a traditional silk turban) governance over land and water resources and meets the and Mysore Silk sarees. The taluk has four hoblis namely needs of society (FAO, 2017). There are a variety of Kasaba, Ilavala, Varuna and Jayapura. The climate is methods have been introduced for LULC classification semiarid tropical and the average annual rainfall of 798 with the development and advances in remote sensing mm with 55 rainy days (CGWB, 2012). The temperature technology and satellites (Mishra et al., 2014). Anderson ranges from 120 to 350 C. classification system is the most widely used classification Figure1: Location and Survey of India Topomap of Mysuru taluk Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India J. Environ. Waste Manag. 328 METHODOLOGY National Remote Sensing Agency (NRSA), Hyderabad. The methodology adopted consists of meaningful iii. GIS software’s: Erdas Imagine v2011 and Arc GIS information extraction from Remote Sensing Satellite v10. image, data preparation, interpretation (on-screen visual), iv. GPS: Garmin 12 is used to mark exact boundaries Ground Truth Check (GTC), map finalization and and to check the conditions of the land use/land cover database organization (NRSC, 2011). LU/LC maps are patterns during field visits. prepared using satellite image in conjunction with collateral data like SoI topomaps on 1:50,000 scale by Satellite data: Data Collateral considering permanent features such as major roads, IRS-1D, Source data: drainages, power-lines, railways, settlements, co- Pan+LISS-III, i. SoI ordinates and village boundaries (Manjunatha et al, 2 Seasons toposheets 2015a). On‐screen Visual Image Interpretation Geocoded data Base Map ii. Forest Map Techniques (VIIT) are extracted manually and compared with digitally extracted vector layers in delineating land use land cover categories. Multi-temporal Resourcesat-1 of LISS III data of 2002 acquired during kharif (Aug –Nov), Classification Image Image and rabi seasons (Jan- Mar) are acquired to estimate the System Analysis Interpretation spatial distribution variability of cropping pattern (NRSC, 2011). Preliminary interpreted LULC features from satellite images are updated by limited field visits & information and the final thematic details are transferred Preliminary Interpreted onto the base maps. Maps Supervised classification Ground Truth Check Supervised classification analyses are carried out on multispectral IRS-1D, LISS-III FCC with medium scale through ArcGIS v10 (Figure 3). The LU/LC patterns are Post field digitized based on the standard schemes developed by correction/ Modification National Remote Sensing Agency (NRSA, 1995). Maximum Likelihood Classification (MLC) scheme is one of the most widely used image classification technique Final Land Use/Land Cover adopted on LISS-III images for mapping all the land Classification Maps use/cover classes. Before the selection of training Figure 2: Flow