Abstract
Based on remote sensing (RS) data, spatiotemporal changes in vegetation cover and degradation hotspots in the Kazaly district were identified for the growing seasons between 2000 and 2025. Statistical analysis was conducted using the Mann-Kendall test and the Getis-Ord Gi local association method. According to the Mann-Kendall test results, despite the absence of a pronounced general trend across the entire district, the application of the Getis-Ord Gi method revealed hidden local hotspots of change. Overall, degradation zones with a 99 % confidence level covered 39,3 % of the district's territory. These areas are predominantly concentrated in the southern and southwestern parts of the region, encompassing natural pastures and territories characterized by high anthropogenic pressure. Furthermore, the identified areas of growth and degradation were correlated with regional productivity indicators. The results established that 38,9 % of the areas showing positive growth dynamics correspond to sections of increased productivity within irrigated croplands.