Abstract

Human-induced land use land cover changes resulted in adverse impacts on the environment at various spatial and temporal scales. The Highland regions of Ethiopia are typical examples of these phenomena. The objective of this study was to analyze spatiotemporal changes in land use/ land cover and their impacts on land surface temperature in the suha watershed, northwestern highlands of Ethiopia. Multi-temporal Landsat images (1985–2019) were used to analyze LU/LC changes and LST using GIS and remote sensing techniques. Image preprocessing, supervised classification, accuracy assessment, and change detection were conducted to identify LU/LC classes, area coverage, and their transitions. Thermal bands of these satellite images were also used to extract LST.Significant changes in land use/land cover (spatial and temporal) were observed in the suha watershed during the study periods. Agricultural land has got the largest proportion in all study periods. The barren land and built area also expanded greatly in 35 years period. Agricultural land has increased by 15417.6 ha (34.8%) and bare land has expanded by 5297.2 ha (373.6%). However, grazing and shrub lands were reduced by18568.4 ha (72.1%) and 3544.2 ha (47.6%), respectively. Spatial and temporal variation of LST was also observed in the same period. The highest mean values were found on impervious surfaces (built-up areas and bare land), and the lowest values were recorded on forest land. A negative correlation was found between LST and NDVI. Undesirable land use and land cover changes put greater pressure on environmental resources, resulting in an adverse effect on them. Therefore, to reverse this situation and create a balanced ecosystem, management strategies should be applied that mainly focus on soil conservation technologies in steep slope areas, improve afforestation and apply proper land-use policies. The outcomes of this research are useful in designing and implementing appropriate strategies that can address critical social and environmental problems. It also provides new knowledge that helps us better understand the spatiotemporal land use land cover changes and their impacts on LST.

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