Advancing geospatial insights in Afghanistan: Annual land cover mapping and landscape metrics analysis for rural landscape planning and restoration

The takeaway message from the study: • This study presents the first consistent annual land cover dataset for Afghanistan (2000–2018), revealing trends such as rapid urban expansion, minimal forest recovery, and highly fragmented rangeland systems. • Google Earth Engine (GEE) and remote sensing effectively addressed a crucial information gap. • Analysis of spatial and temporal changes in diverse land cover categories offered insights into Afghanistan's dynamic landscape. • Through the use of key landscape metrics, such as Greatest Patch Index and Splitting Index, the study offers a detailed understanding of ecosystem structure across the landscape. The openly shared land cover data enhances transparency and is designed to support evidence-based planning and sustainability efforts. Desertification, conflict-driven degradation, and climate change increasingly threaten Afghanistan's landscapes, shaped by both natural processes and long-standing human-environment interactions. There is an urgent need to analyze land cover dynamics and methodological insights in the Hindu Kush Himalaya (HKH) region, particularly in Afghanistan, to guide landscape restoration and regeneration efforts. Addressing this gap, this study produces the first consistent, harmonized annual land cover dataset for Afghanistan from 2000 to 2018, using Google Earth Engine (GEE), the Random Forest algorithm, remote sensing techniques, and 30-meter resolution satellite images. Despite historical data constraints, the cloud-based approach enabled comprehensive national-scale mapping. In 2018, rangeland was the dominant land cover type (45.66%), followed by barren land (31.03%) and sand (7.71%). Over the 19-year period, Rangeland expanded by 1.08%, with notable expansions in built-up areas and sand-covered zones. Spatial patterns and fragmentation were assessed using five landscape metrics: greatest patch area, number of patches, overall core area, splitting index and, largest patch index. These analyses identified critical trends in urban expansion and rangeland fragmentation. The resulting annual land cover database and landscape metrics offer a robust evidence base to inform rural landscape planning, zoning, and restoration initiatives aligned with national and global sustainability goals.