Abstract
Given that many cities in Saudi Arabia have been observing rapid urbanization since the 1990s, scarce studies on the spatial pattern of urban expansion in Saudi Arabia have been conducted. Therefore, the present study investigates the evidence of land use and land cover (LULC) dynamics and urban sprawl in Abha City of Saudi Arabia, which has been experiencing rapid urbanization, from the past to the future using novel and sophisticated methods. The SVM classifier was used in this study to classify the LULC maps for 1990, 2000, and 2018. The LULC dynamics between 1990-2000, 2000-2018, and 1990-2018 have been analyzed using delta (Delta) change and the Markovian transitional probability matrix. Urban sprawl or urban expansion was modeled using two approaches, such as landscape fragmentation and presence frequency for the first time. The future LULC map for 2028 was predicted using the artificial neural network-cellular automata model (ANN-CA). Future LULC was analyzed using landscape fragmentation and frequency approaches. The results of LULC maps showed that urban areas increased by 334.4% between 1990 and 2018. The Delta change rate showed that 16.34% in urban areas has increased since 1990. While, the transitional probability matrix between 1990 and 2018 reported that the built-up area is the largest stable LULC, having an 83.6% transitional probability value. While 17.9%, 21.8%, 12.4%, and 10.5% of agricultural land, scrubland, exposed rocks, and water bodies were transformed into built-up areas. Urban sprawl models showed that 139 km(2) of new urban areas had been set up in 2018, 49 and 69 km(2) in 1990 and 2000. Furthermore, in 2018, more than 200% of urban areas were stabilized or became core urban areas. The future LULC map (2028) showed that the built-up area would be 343.72 km(2), followed by scrubland (342.98 km(2)) and sparse vegetation (89.96 km(2)). The new urban area in 2028 would be 169 km(2). The authorities and planners should focus more on the sustainable development of urban areas; otherwise, it would harm the natural and urban environment.