Comprehensive Land Degradation Assessment Using Geospatial Modeling Approach, the Case of Dega Damot District, Northwestern Ethiopia

Land degradation affects land quality and water resources. This problem is severe in Ethiopia due to its topographic features. The present study aimed to map the land degradation, land‐use and land‐cover (LULC) dynamics, soil erosion, and biodiversity in the Dega Damot District in Ethiopia. Geospatial tools were used to assess changes in LULC patterns in the study area from 1990 to 2020. Landsat images were classified using supervised classification by the maximum likelihood algorithm. They were also classified into different biomass levels by using multicriteria analysis. The major LULC types in the study area were cropland, forest, grassland, shrubland, bare land, waterbody, and settlement areas. The overall accuracy for LULC of the 1990 image classification was 87%, of 2005 was 86%, and of 2020 was 87%. Soil erosion maps were generated using the RUSLE model. Soil loss in the study area was found to be 75%, the highest erosion severity rate. Moreover, the biodiversity degradation hotspot of the study area was computed using the combined proxy factors of road, settlement, slope, LULC. As a result, five classes having very low (0.5%), low (21.2%), moderate (54.3%), high (20.4%), and very high (3.6%) trends were identified. Composite land degradation maps of the study area derived from vegetation, soil erosion, and biodiversity degradation levels have been standardized and normalized with analytical hierarchy and pairwise comparison techniques. The data were assorted into low, moderate, high, and very high levels of land degradation, representing 20%, 44%, 32%, and 4% of areas, respectively. The outcome was found to be extremely useful for management resources in response to sustainable land management practices for the sustainable livelihood of the local people.