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

Abstract

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