Land Use Land Cover Prediction Using Cellular Automata-Markov Model in Kulfo River Watershed

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Addis Ababa University


Land use land cover change is created principally by human activities, activities manipulating the Earth’s surface for some purpose such as agricultural, industrial and residential etc. Mapping and predicting of LULC is important to identify and evaluate the magnitude and the change within the watershed to ensure best future planning and management. This study was mainly focusing on predicting land use cover change in kulfo river watershed through remote sensing, geographic information system integrated with IDRISI selva software and CA-Markov chain model. Cellular automata coupling with Markova model was used to predicting and modeling land use cover change for the year 2036 and 2051. Land use map of 2000, 2011 and 2021 were generated from Landsat satellite images. Analyzing the pixel based image classification method. The land use cover maps were computed using Maximum Likelihood algorithm of supervised classification technique, in ENVI 5.3 and GIS 10.8. Predicted LULC is developed using IDRISI Selva Software, and calibrated and validated using classified 2021 LULC maps. Hence the quality and location coefficient were calculated based on compassion of the predicted LULC for 2021 with the actual 2021 for first scenarios. The outcome demonstrate that bare land that was 14.5 % in 2021 decrease to 13.3% and change to 12.5% in 2051, forest land will decline from 18.3 % in 2021 to 17.7% in 2036 and also 18.5 % in 2051, water body that was 0.9% in 2021 to 0.6% in 2031 and change to 0.4 % in 2051.In general, the forecast result shows that except for built up area and cultivated land all land use type decreased per year respectively. Hence the observed LULC changes were generated by the increase of population, this lead to the demand for cultivated land, rural settlement and the extraction of forest for fuel and other construction materials.