Comparative Evaluation of Operational Land Imager sensor on board Landsat 8 and Landsat 9 for Land use Land Cover Mapping over a Heterogeneous Landscape

Since its advent in 1972, the Landsat satellites have witnessed consistent improvements sensor characteristics, which significantly improved accuracy. In this study, a comparison of accuracy OLI and OLI-2 land use cover (LULC) mapping has been made. For this, image fusion techniques applied to enhance spatial resolution both multispectral images, then support vector machine (SVM) classifier used for LULC mapping. The results show that classification from better (83.4%) than (92.4%). validation classified maps shows data is more accurate distinguishing dense sparse vegetation as well darker lighter objects. relationship between surface biophysical parameters using Local Moran’s I also performance sensor.