LALMI YER MAYDONLARINI KOSMIK SURATLAR YORDAMIDA MONITORING QILISH

This article discusses modern approaches to monitoring rainfed agricultural lands using remote sensing (satellite imagery), artificial intelligence (AI), and the RUSLE model. The effectiveness of NDVI vegetation indices and GIS technologies in maintaining productivity, assessing erosion, and ensuring sustainable agricultural practices is emphasized. Land management practices tailored for the foothill regions of Uzbekistan are proposed to mitigate land degradation. The paper highlights the advantages of integrating satellite data from Landsat-8, Sentinel-2, Sentinel-1, and deep learning algorithms to improve monitoring accuracy and efficiency.