MONITORING LAND USE / LAND COVER CHANGES USING REMOTE SENSING AND GIS: A CASE STUDY ON KANCHRAPARA MUNICIPALITY AND ITS ADJOINING AREA, WEST BENGAL, INDIA

Somnath DAS

Cartographer (Contractual), Department of Geography, University of Kalyani, Kalyani, Nadia-741235, West Bengal, India.

somu8969@gmail.com

Abhay Sankar SAHU

Assistant Professor, Department of Geography, University of Kalyani, Kalyani, Nadia-741235, West Bengal, India.

sahu.abhaysankar@gmail.com

Abstract

Changes in land use are a very important issue. Through the discussion of land use change it is easy to know the relationship of a person living in that place with that place. This paper demonstrates the land use changes of Kanchrapara Municipality and its adjoining area through the use of some techniques of remote sensing and GIS (Geographical Information System). Two Landsat satellite images with a range of twenty years have been used to apply these techniques. These images were of the Landsat-7 ETM+ (Year 2000) and Landsat-8 OLI-TIRS (Year 2019). ArcGIS 10.5 software has been used for pre-processing of these images. Then the supervised classification method has been used for the classification of those images using QGIS 3.4 software using the maximum likelihood algorithm. Four types of land use categories have been identified by image classification based on satellite images and Google maps. These were water bodies, vegetation coverage area, bare soil and built up area. Of these, only the amount of bare soil has increased (+17.22%) and the rest of land use categories decreased comparatively. The reasons for the increase and decrease of this level were also discussed here. Accuracy assessment has been also done to determine the accuracy of image classification. Where the overall accuracy of two decades was 82.39 % and 83 % respectively, with the Kappa coefficient was 0.75 and 0.76 respectively. Finally, there is a comparative discussion of two decades of land use using change detection techniques.

Keywords: Land use/ land cover changes, Image processing, Accuracy assessment, Kappa Coefficient, Change detection technique

JEL classification: C00, C89, R14, R52

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