Land cover change and vegetation trends in South Darfur Sudan using dynamic world

Land use and land cover change (LULCC) in semi-arid regions provides important insights into environmental dynamics under climate variability and socio-political disturbance. This study investigated the spatiotemporal dynamics of land cover, vegetation greenness, and climate variability in Buram Locality, South Darfur, Sudan, using Dynamic World land-cover data (10 m; 2016–2025), Sentinel-2 Normalized Difference Vegetation Index (NDVI), Landsat-derived Land Surface Temperature (LST), and long-term meteorological observations (1980–2025). Trend analysis was performed using the Mann–Kendall test and Sen’s slope estimator within Google Earth Engine and R. Tree cover increased from 12.95% in 2016 to 18.03% in 2025, while shrub–grass–scrub vegetation and bare ground declined, with bare ground decreasing from 4.55 to 1.96%. Cropland fluctuated, increasing until 2020 before declining in 2025. Annual NDVI showed a significant increasing trend (Sen’s slope = 0.002 year⁻ 1 , p = 0.032), with the strongest increase occurring during the dry season (0.005 year⁻ 1 , p = 0.004), whereas rainy-season NDVI remained stable. Long-term rainfall increased significantly (3.92 mm year⁻ 1 , p < 0.01), accompanied by a significant warming trend (0.01 °C year⁻ 1 , p = 0.01). Pearson correlation analysis showed the largest observed association between dry-season NDVI and dry-season LST (r = − 0.581, p = 0.079), but none of the examined NDVI–climate correlations was statistically significant at p < 0.05. These findings indicate increasing vegetation greenness and changes in mapped land cover during 2016–2025 alongside long-term climatic changes. However, the observed patterns cannot be attributed to specific climatic or socio-economic drivers based on the available data. The study demonstrates the value of integrating high-resolution Earth observation data with long-term climate records to monitor environmental change in data-scarce and conflict-affected semi-arid regions.