Application of geoinformatics to classify the landcover from satellite imagery using NDVI – A case of peri-urban regions of Southern Chennai

Abstract The peri-urban regions of the Indian cities are growing at a rapid rate, engulfing all available lands in their vicinity. It is vital to map changes that occur green areas plan for sustainable urban environments and ecosystems. Normalized Difference Vegetation Index (NDVI) graphical indicator utilizes multispectral remote sensing techniques classification land cover. aim current study use Geographic Information Systems (GIS) tools its indices classify cover interest. For this study, primary data collection includes identification area, toposheets from Survey India satellite images United States Geological (USGS) year 2021. methodology acquisition data, image processing, application NDVI technique, accuracy assessment presentation results. exercise, has been classified under three categories namely, water, vegetation. analytical outcomes segregated 30.06 sq.km (3%) area as water bodies, 152.85 (15%) land/barren 821.97 (82%) covered with vegetation, out total 1004.88 sq. km. obtained results were validated through field visits ground truthing method. produced an overall 91% kappa coefficient value 0.87. Since constant transformation, it challenging time-consuming physically landcover, especially lack on definite boundaries. Hence, recommends can be used effective technique Landsat imagery constantly-evolving regions.