Assessment of land cover change using normalized difference vegetation index (NDVI) in relation to river morphological dynamics in the Lower Most Omo River sub watershed Ethiopia

Abstract

Hydrology, land cover changes, and societal factors affect flood risk and erosion along riverbanks. Lower Most Omo River-Sub Watershed (LMOR-SW) illustrates this trend over three decades, with back flooding from Lake Turkana currently threatening Dasenech woreda residents. This study employs a non-signature-based classification to assess land cover change using NDVI for LMOR sub-basin, categorizing pixels into water body (NDVI < 0), bare land (0 ≤ NDVI < 0.2), shrub land (0.2 ≤ NDVI < 0.5), and forest (NDVI ≥ 0.5). The study aims to relate changes in land cover (LC) to channel alterations. Classified map overall accuracy was 92.80%, 89.67%, and 92.40% for 1995, 2015, and 2025, with Kappa Coefficients of 91%, 86.40%, and 90%, respectively. The NDVI value range and non-signature based supervised classification effectively modeled land cover changes among water bodies, bare land, shrub land, and forest while adhering to Landsat pre-processing. Over 30 years, water bodies increased by 153.76 km 2 , bare land decreased by 392.59 km 2 , shrub land increased by 529.59 km 2 , and forest cover decreased by 290.77 km 2 . From 1995 to 2025, 27.8 km 2 of bare land, 72.94 km 2 of shrub land, and 62.27 km 2 of forest cover converted to water bodies, increasing it finally from 20.39 to 174.15 km 2 .Analysis report warns that without prompt action, Omorate town might flood totally in about 3.07 years and Omo River bridge in 8.26 years due to 5.125 km 2 /yr flooding rate. Practice sustainable planning; apply Landsat-derived NDVI–MNDWI models integrated with GIS to mitigate environmental hazards in arid regions.