MASOFADAN ZONDLASH TEXNOLOGIYALARI ASOSIDA YER RESURSLARIDAN FOYDALANISH MONITORINGINI TAKOMILLASHTIRISH
Keywords:
remote sensing, geographic information systems, land resource monitoring, NDVI, Sentinel-2, Landsat, soil salinization, classification, Random Forest, agricultural landAbstract
This article examines the improvement of land resource use monitoring based on remote sensing technologies. The aim of the study is to develop a comprehensive methodology for the remote identification of agricultural land, irrigated areas, soil salinization, and vegetation cover status using Sentinel-2, Landsat-8/9, and MODIS satellite imagery, and to test it on the example of regions of the Republic of Uzbekistan. Vegetation indices (NDVI, NDWI, SAVI) were calculated across spectral bands, supervised classification methods including the Random Forest algorithm were applied for object classification, and the results were compared with ground-truth data. The analysis showed that the developed methodology allows classifying land cover types with 92-95 percent accuracy, significantly reducing time and financial costs compared to traditional field surveys. The obtained results provide a basis for developing practical recommendations on land resource management, irrigation system planning, and early detection of soil degradation.
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