Abstract
Urban growth is a serious threat and challenge worldwide due to its role in altering ecosystem processes and contributing to negative environmental impacts. The natural environment of Saudi Arabia has been affected by the increased pace of urban and economic development, which has been supported by large oil revenues in recent years. Measuring the spatiotemporal patterns of urban growth is important to better understand the qualitative and quantitative impacts of urban spatial distribution over periods of time. Optical remote sensing can be a reliable data source that provides valuable information regarding the spatial and temporal distributions of urban growth. This research used two sets of Landsat images from 1985 and 2014 to map and monitor the spatial distribution of the urban extent among five Saudi Arabian cities: Riyadh, Jeddah, Makkah, Al-Taif and Eastern Area. A decision tree classifier was applied using object-based image analysis (OBIA) to analyze urban land cover in the five cities. The accuracy assessment of the urban change detection maps indicated a high overall accuracy and Kappa coefficient. The results of this research show a high rate of urbanization and complex dynamics across the five cites. The significant changes were the result of a rapid increase in land development, exhibiting complex patterns in the urbanization process across the five cities. The government's policy and increased oil revenues significantly contributed to increasing the urban cover in the five selected cities.