Spatial–temporal analysis of land cover dynamics in the Southern Aral Sea region using remote sensing and GIS (2004–2024)

¹ Samarkand State Pedagogical Institute, 140044 Samarkand, Uzbekistan
² Karakalpak State University, 230100 Nukus, Uzbekistan
³ Samarkand State University, 230100 Samarkand, Uzbekistan

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

The Southern Aral Sea region has undergone profound environmental transformations over the past several decades due to severe reduction of inflowing water and intensified evaporation processes. The purpose of this study is to use remote sensing and GIS tools to examine the spatiotemporal changes in land cover in the Southern Aral Sea region during the past 20 years. Changes in important land cover types, such as water bodies, vegetation, mudflats, pure sand, and sandy salt surfaces, were evaluated using multi-temporal Landsat ETM+ and Landsat 8 OLI satellite photos obtained between 2004 and 2024. A hybrid method based on the Normalized Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI) was used to classify land cover. The findings show that the lake’s surface area has significantly decreased while saline and sandy land cover has rapidly expanded, creating and intensifying the Aral-Kum Desert. Water-covered regions significantly decreased annually, according to quantitative study, whereas saline and sandy surfaces increased proportionately. Strong correlations between land cover change, lake shrinkage, and important climate variables, especially wind speed and air temperature, are shown using correlation analysis. These results demonstrate how important land cover dynamics are in hastening the creation of dust storms and desertification processes in the Southern Aral Sea region. In dry areas, the used remote sensing and GIS-based method supports sustainable land and ecosystem management and offers an efficient framework for long-term environmental monitoring.