Land Use Land Cover Change Analysis for Urban Growth Prediction Using Landsat Satellite Data and Markov Chain Model for Al Baha Region Saudi Arabia

Land Use Cover Change (LULCC) and urban growth prediction analysis are two of the best methods that can help decision-makers for better sustainable management planning socioeconomic development in countries. In present paper, land use was analyzed predicted all districts El Baha region (Kingdom Saudi Arabia) based on high-resolution Landsat, 5, 7, 8 satellite imagery during period study between 1985–2021. Using remote sensing techniques, LULCC were obtained maximum likelihood classification (MLC), where geographic information system (GIS) had been used mapping classes. Furthermore, Markov cellular automata (MCA) Idrisi TerrSet applied assessing future 2021–2047. The findings MLC indicate great expansion at expense rangeland, forest shrubland, barren sand areas, with contribution each built-up area estimated to be around 9.1% (179.7 km2), 33.4% (656.3 km2) 57.5% (1131.5 respectively. simulation 2021–2047 revealed a loss by 565, 144 105 km2, respectively, rangeland is most influenced, its cover will decrease from 4002 3437 km2. From results MCA, large it 2607 km2 until year 2047 net increase 811 this may provide implement efficient practices use, especially vision 2030.