Geospatial and Google Earth Engine-based assessment of land use and land cover dynamics and its impacts on ecosystem health and biodiversity in the Bale Mountains, Ethiopia.

This study examines land use and land cover (LULC) dynamics and their impacts on ecosystem health and biodiversity in the Bale Mountains, Ethiopia, using multi-temporal remote sensing and Google Earth Engine (GEE). Landsat (2000, 2012) and Sentinel-2 (2025) imagery were classified using a random forest (RF) algorithm. Vegetation condition was assessed using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), while biodiversity patterns were analyzed using species occurrence data from the Global Biodiversity Information Facility (GBIF) and iNaturalist. The results reveal substantial landscape transformation over time. Forest, grassland, and Afro-alpine ecosystems declined, whereas farmland, built-up areas, and bare land expanded, reflecting increasing anthropogenic pressure. Vegetation indices indicate reduced dry-season greenness and weakened wet-season recovery, particularly after 2012, suggesting growing ecosystem stress. Landscape metrics further show increased fragmentation, characterized by higher patch density, greater edge effects, and reduced connectivity. Biodiversity records are increasingly concentrated in remnant natural habitats, indicating habitat contraction and heightened vulnerability of endemic species. Overall, the findings demonstrate that combined land-use expansion and climatic variability are driving ecosystem degradation in the Bale Mountains. While strong spatial associations are observed, causal relationships cannot be established due to data limitations. This study highlights the value of integrating remote sensing and biodiversity data for ecosystem monitoring and supports conservation strategies focused on habitat protection, connectivity, and sustainable land management.