The nexus between land use and land cover change, vegetation density, and land surface temperature: a case study of Lake Abaya catchments in the Southern Main Ethiopian Rift

Land use and land cover (LULC) change alters ecosystem processes by modifying vegetation structure, surface energy balance, and land surface temperature (LST). While numerous studies have examined LULC–LST relationships, few have integrated long-term LULC transitions; Normalized Difference Vegetation Index (NDVI) based vegetation dynamics, and seasonal LST responses within semi-arid Rift Valley catchments under consistent phenological conditions. This study addresses this gap by analyzing the spatiotemporal interactions between LULC dynamics, vegetation density, and LST in the Lake Abaya catchments, Southern Main Ethiopian Rift, using multi-temporal Landsat imagery from 1986 (TM), 2003 (ETM+), and 2019 (OLI/TIRS). Supervised maximum likelihood classification was applied and validated using ground control points, while NDVI and LST were derived to quantify vegetation and thermal responses. LULC transition matrices were used to explicitly trace land cover conversions and their thermal consequences, and NDVI–LST relationships were examined using regression analysis. Results reveal substantial landscape transformation, with forest cover declining from 35.1% to 25.7% and agricultural land expanding from 15.6% to 26.2%, primarily at the expense of forest and rangeland. Bare and degraded lands consistently exhibited the highest LST, whereas forest and water bodies showed pronounced cooling effects. A strong and statistically significant inverse NDVI–LST relationship confirms vegetation’s role in regulating surface energy balance. By linking long-term LULC transitions with seasonally comparable thermal responses, this study provides new empirical evidence on how land degradation and agricultural expansion reshape microclimate regulation in Rift Valley catchments. The findings offer actionable insights for climate-adaptive land-use planning, catchments management, and ecological restoration in data-scarce semi-arid regions.