Predictions of Land Use/Land Cover Changes, Drivers, and Their Implications for Dense Forest Degradation in Kunar Province, Eastern Afghanistan

Changes in land use and land cover (LULC) are among the leading contributors to global environmental transformation. Analyzing these dynamics is essential for understanding historical land utilization patterns and identifying the key drivers behind such shifts. This research focuses on LULC changes in the Kunar region of eastern Afghanistan. To classify the LULC types, the study area was divided into nine major classes using the Support Vector Machine (SVM) algorithm, based on Landsat 07 Enhanced Thematic Mapper Plus (ETM+) data for 2004 and Landsat 8 Operational Land Imager (OLI) data for 2014 and 2024. Past and present changes were evaluated using ArcGIS 10.8, while future scenarios for 2034 and 2044 were simulated using the Land Change Modeler (LCM) embedded in the TerrSet platform, combined with the Cellular Automata–Markov Chain (CA-MC) model with 90% kappa agreement validation value. From 2004 to 2024, grassland expanded significantly from 68.93% (3406 km 2 ) to 73.94% (3654 km 2 ). Built-up areas grew from 0.59% (29.10 km 2 ) in 2014 to 1.02% (50.39 km 2 ) in 2024. Conversely, dense forest cover declined from 27.50% (1358.90 km 2 ) to 22.96% (1134.75 km 2 ), a decrease of 224.15 km 2 . Barren land, after a temporary increase, also showed a net decline. Projections for 2034 and 2044 suggest a further reduction in forested areas to 1077 km 2 , while grasslands and urbanized zones are expected to increase to 3690 km 2 and 60.63 km 2 , respectively. These trends emphasize a swift transition in land use patterns, primarily driven by the conversion of forested and barren landscapes into settlements and grasslands. The findings underline the urgent need for implementing sustainable land management strategies to curb environmental degradation and ensure balanced land resource utilization in the future.