Author: Hessah Abdulaziz Al Mubarak
Vol. (15): No.(1), 1443AH/2022AD
pp.29-55

:Abstract
Urbanization is a serious and dynamic issue at present because rapid urbanization can result in the haphazard and unplanned growth of cities. The pressure of an ever-growing population places a burden on limited public facilities, which are often on the verge of collapse. There is consequently a need to balance present land requirements with the available resources, while also considering future needs. Saudi Arabia has witnessed dramatic urban growth over the last 40 years and is considered to be one of the world’s most rapidly urbanizing countries. The increase in its population, speed of its urban expansion, and pace of its urban development have impacted the environment and resulted in changes to land cover. This study, therefore, aims to monitor and predict future land use, land cover, and urban expansion in the Ammariyyah and Uyaynah centers within Diriyah Governorate in Saudi Arabia. Four Landsat satellite images, captured in 1990, 2000, 2013, and 2020, were utilized. Supervised image classification, using the maximum likelihood algorithm, a post-classification technique, and the Markov and CA-Markov prediction models were the main methods adopted to achieve the study objectives. Supervised image classification was accomplished utilizing training data obtained from field visits, Google Earth, and topographic maps (scale 1:50,000, sourced from the General Authority for Survey and Geospatial Information in the Kingdom of Saudi Arabia). Four land cover types were identified in the study area, including green land, open spaces, dry Wadis, and urban and built-up areas. The results revealed that the total area of green land, dry Wadis, and urban development had increased from 1990 to 2020.
Keywords: Prediction model; CA-Markov; land cover; change detection; The open spaces appeared to have fluctuated in growth and reduction during the above-mentioned time period. Moreover, land cover in the study area was projected to change in 2030, predicting an increase in the total area of green land, dry Wadis, and urban development, while open spaces were expected to decrease. The results obtained in this study are assumed to be of potential benefit to the authorities responsible for establishing optimal strategies in effective future land use planning, management, and development. Diriyah Governorate; Saudi Arabia.
Keywords: Prediction model; CA-Markov; land cover; change detection; The open spaces appeared to have fluctuated in growth and reduction during the above-mentioned time period. Moreover, land cover in the study area was projected to change in 2030, predicting an increase in the total area of green land, dry Wadis, and urban development, while open spaces were expected to decrease. The results obtained in this study are assumed to be of potential benefit to the authorities responsible for establishing optimal strategies in effective future land use planning, management, and development. Diriyah Governorate; Saudi Arabia.

*Dept. of Geography, King Saud University.