A Historical–Projected Analysis in Land Use/Land Cover in Developing Arid Region Using Spatial Differences and Its Relation to the Climate

Land resources are under relentless pressure from metropolitan regions, pollution, and climate shifts. The urge to monitor Use/Land Cover (LULC) changes based on technology sustainable management addressed. This study analyzes the historical land cover maps calculate growth patterns for years 1985–2022 uses Logistic Regression (LR) Artificial Neural Networks (ANN) project future dynamics forecasts 2030–2040 in Amman-Zarqa Basin (AZB). state of extreme indices projections CMIP5 RCP8.5 linked corrected LULC assessed. Given greater dry covering large surface runoff, little rainfall, high evapotranspiration rates, across AZB notably showed instability key climatic a major exacerbation warmth drier soil basin. Both change use contributing dynamics, but land-use alterations much more dramatic than changes. Since effects mostly identifiable through forms, practices put phase that may be influenced by change. results revealed daily extremes 1992 aligned with corresponding increase barren lands diminished half area forest, cultivated, rainfed, pasture 1995. Rainfed regions were converted agriculture or shrubland an accuracy 0.87, urban encroachment caused acreage woodland, grazing fields decrease almost half. Predicted created using LR 2030 (Kappa = 0.99) 2040 0.90), contrast ANN approach 0.99 0.90 2040). By combining LR, decreasing bare was anticipated between 325 km2 344 km2. As result, 20% total cities’ areas will doubled. More subjective analysis is required predict drought improve resilience various types.