Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/19480
Title: Spatiotemporal Modeling of Urban Growth Predictions Based on Driving Force Factors in Five Saudi Arabian Cities
Contributor(s): Alqurashi, Abdullah (author); Kumar, Lalit  (author)orcid ; Al-Ghamdi, Khalid (author)
Publication Date: 2016
Open Access: Yes
DOI: 10.3390/ijgi5080139Open Access Link
Handle Link: https://hdl.handle.net/1959.11/19480
Abstract: This paper investigates the effect of four driving forces, including elevation, slope, distance to drainage and distance to major roads, on urban expansion in five Saudi Arabian cities: Riyadh, Jeddah, Makkah, Al-Taif and Eastern Area. The prediction of urban probabilities in the selected cities based on the four driving forces is generated using a logistic regression model for two time periods of urban change in 1985 and 2014. The validation of the model was tested using two approaches. The first approach was a quantitative analysis by using the Relative Operating Characteristic (ROC) method. The second approach was a qualitative analysis in which the probable urban growth maps based on urban changes in 1985 is used to test the performance of the model to predict the probable urban growth after 2014 by comparing the probable maps of 1985 and the actual urban growth of 2014. The results indicate that the prediction model of 2014 provides a reliable and consistent prediction based on the performance of 1985. The analysis of driving forces shows variable effects over time. Variables such as elevation, slope and road distance had significant effects on the selected cities. However, distance to major roads was the factor with the most impact to determine the urban form in all five cites in both 1985 and 2014.
Publication Type: Journal Article
Source of Publication: ISPRS International Journal of Geo-Information, 5(8), p. 1-19
Publisher: MDPIAG
Place of Publication: Switzerland
ISSN: 2220-9964
Field of Research (FOR): 090903 Geospatial Information Systems
090905 Photogrammetry and Remote Sensing
Socio-Economic Outcome Codes: 960610 Urban Land Evaluation
960911 Urban and Industrial Land Management
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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