Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes. In Ethiopia, the rapidly changing of LULC is mainly due to population pressure, resettlement programs, climate change, and other human and nature-induced driving forces. Anthropogenic activities are the most significant factors adversely changing the natural status of the landscape and resources, which exerts unfavourable and adverse impacts on the environment and livelihood. The main goal of the present work is to review previous studies, discussing the spatio-temporal LULC changes in Ethiopian basins, to find out common points and gaps that exist in the current literature, to be eventually addressed in the future. Seventeen articles, published from 2011 to 2020, were selected and reviewed, focusing on LULC classification using ArcGIS and ERDAS imagine software by unsupervised and maximum likelihood supervised classification methods. Key informant interview (KII), focal group discussions (FGDs) and collection of ground truth data using ground positioning systems (GPS) for data validation were the major approaches discussed in most of the studies. All the analysed research showed that, during the last decades, Ethiopian lands changed to agricultural land use, waterbody, commercial farmland and built-up/settlement. Some parts of forest land, grazing land, swamp/wetland, shrubland, rangeland and bare/ rock out cropland cover class were changed to other LULC class types, mainly as a consequence of increasing anthropogenic pressure. In summary, these articles confirmed that LULC changes are a direct result of both natural and human influences. However, most of the study provided details of LULC for the past decades within a specific spatial location, while they did not address the challenge of forecasting future LULC changes at the basin scale.
Land Use Projections Under Alternative Policies: A Transition Matrix Approach