Land Use/Land Cover Change Detection Analysis Using Supervised Classification, Remote Sensing and GIS In Mandavi River Basin, YSR Kadapa District, Andhra Pradesh, India

R. Siddi Raju; G Sudarsana Raju; M Rajasekhar

doi:10.37591/.v9i3.249

Abstract

Assessment, development, and management of watershed strategy require exact calculations reports of present and past land use/cover data and its change determine the ecological and hydrological process taking place in a watershed. In this study, we have to adopt supervised classification with maximum likelihood algorithm in ERDAS imagine to notice land use/cover changes (LU/LCC) analyzed in Mandavi river basin, Kadapa district, Andhra Pradesh, India using multispectral satellite data gained from Landsat satellite series for the years 2006 and 2018. These satellite data is intended for land use/cover through supervised classification in ERDAS 2014, software. In the result, we could identify six land use/land cover (LU/LC) classes, namely agricultural land, built-up land, fallow land, forest land, river and water bodies. The results shown that during the 2006 and 2018, built-up land fallow land have been increased about 0.84% (such as 12.30 km2) and 2.92% (42.82 km2), respectively, whereas the area under other land categories such as agricultural land, forest land, river and water bodies have decreased about 1.86% (27.30 km2), 1.34 (19.66 km2), 0.26 (3.87 km2) and 0.29 (4.28 km2), respectively. Finally, accuracy assessment has been carried out and their result shows that overall accuracy of classified images of the year 2006 and 2018 are 86.62% and 91.85% respectively. The overall Kappa coefficient values of classified images of the year 2006 and 2018 are 0.8343 and 0.8987. Hence, these values indicate that acceptable accuracy of the classified LU/LC features.Keywords: Supervised classification, land use/cover, change detection, accuracy assessment, RS and GISCite this ArticleR. Siddi Raju, G. Sudarsana Raju, M. Rajasekhar. Land Use/Land Cover Change Detection Analysis Using Supervised Classification, Remote Sensing and GIS In Mandavi River Basin, YSR Kadapa District, Andhra Pradesh, India. Journal of Remote Sensing & GIS. 2018; 9(3): 46–54p.