Spatiotemporal Analysis of Land Use and Land Cover Change over 25 Years Using Landsat Image in Case of Ura District (Assosa), Ethiopia

Land use/ Land cover (LULC) classification plays a vital role in understanding environmental changes and for supporting sustainable land management in Ura District (Assosa town). This study aims to analyse the spatial distribution and patterns of LULC in study area using remote sensing and GIS techniques. Multispectral satellite imagery’s (Landsat 7, Landsat 8 and Landsat 9) was classified using supervised image classification method into major classes including agricultural land, forest, built-up, grassland and bare land. Accuracy assessment was performed using Confusion matrix, resulting overall accuracy (88.00%, 92.00% and 96.00%) and a Kappa Coefficient of (0.8507, 0.8355 and 0.9232) in 2001, 2013 and 2025 respectively. The result indicates that the dominant class forest cover the large portion of the study area 48.934451%, followed by Grassland (25.297372%) and agriculture (13.247733%) in 2001. Built-up, bare land and agricultural areas have increased by 12.970652%, 22.792803% and 2.390367% respectively while forest cover and grassland has decreased by 20.805041% and 17.348774 in past 25 years (2001 – 2025). The study highlights significant land use changes and their environmental implications. These findings provide valuable information for land use planning and sustainable resource management. The integration of advanced approaches such as GIS, Remote sensing and Machin learning technologies are recommended for improving future LULC analysis.