Abstract

Land use and land cover within subriver basins greatly affect hydrological processes, making accurate assessment and monitoring of past and present land use/cover changes essential for effective watershed development, management, and understanding of ecological and hydrological dynamics. In this study, we have to adopt supervised classification with maximum likelihood algorithm in ERDAS imagine 9.2, to notice land use/cover changes (LU/LCC) analyzed in Tiggaleru sub river basin, YSR Kadapa District, Andhra Pradesh, India using multispectral satellite data gained from Landsat Satellite-8 OLI series for the years 2014 and 2023. These satellite data is intended for land use/cover through supervised classification in ERDAS 2015, 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, Scrubland and water bodies. The results shown that during the 2014 and 2023, built-up land and Agriculture land and have been increased about 2.31% (such as 6.84 km2) and 6.66% (19.76 km2), respectively, whereas the area under other land categories such as forest land, and scrubland have decreased about 0.99% (2.93 km2) and 10.07% (29.88 km2) and remaining fallow land and water bodies are increased about 0.12 (0.36 km2) and 1.97% (5.85 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.

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