Abstract
Rainfed (lalmi) arable lands in arid and semi-arid territories represent crucial yet vulnerable agricultural zones that are highly sensitive to climatic variations, soil degradation, and drought. This conference thesis presents a methodological and empirical framework for monitoring rainfed lands across the Kashkadarya region utilizing multi-temporal satellite Earth observation data (Sentinel-2, Landsat-8/9) integrated into Geographic Information Systems (GIS). By computing multi-spectral vegetation indices—primarily Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI)—alongside digital elevation models (SRTM DEM), spatial degradation patterns and biomass fluctuations were evaluated over critical phenological phases. The results demonstrate that geospatial technologies allow continuous, cost-effective, and highly accurate territorial assessments, facilitating data-driven decision-making for sustainable land management.
References
This work is licensed under a Creative Commons Attribution 4.0 International License.