Future Modeling of Urban Growth Using Geographical Information Systems and SLEUTH Method: The Case of Sanliurfa

Songül Naryaprağı Gülalan, Fred Barış Ernst and Abdullah İzzeddin Karabulut ()
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Songül Naryaprağı Gülalan: Department of Geomatics Engineering, Faculty of Engineering, Harran University, Sanliurfa 63050, Türkiye
Fred Barış Ernst: Department of Geomatics Engineering, Faculty of Engineering, Harran University, Sanliurfa 63050, Türkiye
Abdullah İzzeddin Karabulut: Remote Sensing and Geographic Information Systems, Harran University, Sanliurfa 63050, Türkiye

Sustainability, 2025, vol. 17, issue 15, 1-20

Abstract: This study was conducted using Geographic Information Systems (GISs), Remote Sensing (RS) techniques, and the SLEUTH model based on Cellular Automata (CA) to analyze the spatial and temporal dynamics of urban growth in Sanliurfa Province and to create future projections. The model in question simulates urban sprawl by using Slope, Land Use/Land Cover (LULC), Excluded Areas, urban areas, transportation, and hill shade layers as inputs. In addition, disaster risk areas and public policies that will affect the urbanization of the city were used as input layers. In the study, the spatial pattern of urbanization in Sanliurfa was determined by using Landsat satellite images of six different periods covering the years 1985–2025. The Analytical Hierarchy Process (AHP) method was applied within the scope of Multi-Criteria Decision Analysis (MCDA). Weighting was made for each parameter. Spatial analysis was performed by combining these values with data in raster format. The results show that the SLEUTH model successfully reflects past growth trends when calibrated at different spatial resolutions and can provide reliable predictions for the future. Thus, the proposed model can be used as an effective decision support tool in the evaluation of alternative urbanization scenarios in urban planning. The findings contribute to the sustainability of land management policies.

Keywords: SLEUTH Model; urban growth; analytical hierarchy process; geographic information systems; remote sensing; Sanliurfa (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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