Modelling spatiotemporal trends of land use land cover dynamics in the Abbay River Basin, Ethiopia

Understanding the spatiotemporal patterns of land use land cover (LULC) dynamics is essential for sustainable land resources management. The spatiotemporal analysis of LULC dynamics is a significant preceding stage in the analysis of biodiversity and ecosystem services (ES). This study aimed at modeling the spatiotemporal LULC dynamics of the Abbay River Basin (ARB) between 1994 and 2056. A hybrid image spectral recognition approach was used to identify eight LULC categories: agriculture (AG), bareland (BL), forest (FT), grassland (GL), settlement (ST), shrubland (SH), wetland (WL), and water body (WB). The supervised image classification approach with a maximum likelihood classifier algorithm was used to classify the images into the identified LULC categories. Then, the integration of Multi-Layer Perceptron Neural Network and Markov Chain Model in Land Change Modeler was used to model and analyze LULC dynamics. The findings revealed that ARB has experienced significant LULC dynamics. Between 1994 and 2021, AG, BL, SH, and WL showed decreasing trend by 34.5 km2, 1 km2, 200 km2, and 0.1 km2 annual rate of change while FT, GL, ST, and WB showed an increasing trend with 166 km2, 0.5 km2, 20 km2 and 50 km2 annual rate of change respectively. Between 2021 and 2056, AG and SH will continue to decrease by 161 km2 and 113.6 km2 annual rate of change while FT and ST will increase by 116 km2 and 31 km2 annual rate of change respectively. Evidence likelihood LULC, elevation, proximity to degradation and proximity to urban were found to be the most influential drivers of LULC change whereas slope, aspect and proximity to road were found least influential drivers of LULC change. While increasing FT cover is important in regulatory services for natural processes as well as soil and water conservation, the unprecedented rate of urbanization may endanger biodiversity and ES. The study’s approaches and outcomes will assist environmentalists and shareholders in planning an ecofriendly ecosystem conservation approach and watershed management long-term plan in the study area and other basins with a similar ecological setting.