Identifying Cooler and Flood-Safer Urban Zones on Riyadh's Fringe Using a Digital Elevation Model (DEM) and the National Geoid Model KSA-Geoid21

dc.contributor.advisorDewan, Ashraf
dc.contributor.authorAljebreen, Suliman
dc.date.accessioned2026-07-29T13:10:37Z
dc.date.issued2026
dc.description.abstractThis thesis develops a GIS-based suitability framework to identify relatively cooler and flood-safer zones for urban fringe planning in Riyadh, Saudi Arabia. The study integrates two physical indicators: (i) seasonal Land Surface Temperature (LST) derived from Landsat data, and (ii) DEM-derived hydrological indicators including D-Infinity flow routing, wadi channel delineation, flood-exposure modelling, and terrain slope. These indicators were standardised and combined using Weighted Linear Combination (WLC) under three weighting scenarios. A ±15% sensitivity analysis using Spearman’s rank correlation was used to assess the stability of the resulting suitability patterns. The results show that most of Riyadh’s fringe remains constrained by high thermal stress and/or flood-related exposure, while comparatively more suitable zones are concentrated mainly in the western and south-western fringe. The identified spatial pattern remained reasonably stable under different weighting scenarios, suggesting that the framework can support comparative planning decisions. All analyses were undertaken in UTM Zone 38N (EPSG:32638). The outputs include suitability maps, extracted priority zones, and summary statistics relevant to physically informed urban fringe planning in Riyadh.
dc.format.extent36
dc.identifier.urihttps://hdl.handle.net/20.500.14154/79688
dc.language.isoen
dc.publisherSaudi Digital Library
dc.subjectGIS
dc.subjectRemote Sensing
dc.subjectLand Surface Temperature
dc.subjectDigital Elevation Model
dc.subjectFlood Susceptibility
dc.subjectUrban Planning
dc.subjectRiyadh
dc.subjectKSA-Geoid21
dc.titleIdentifying Cooler and Flood-Safer Urban Zones on Riyadh's Fringe Using a Digital Elevation Model (DEM) and the National Geoid Model KSA-Geoid21
dc.typeThesis
sdl.degree.departmentSchool of Earth and Planetary Science – Spatial Sciences
sdl.degree.disciplineGeospatial Science
sdl.degree.grantorCurtin University
sdl.degree.nameMaster of Geospatial Intelligence
sdl.thesis.sourceSACM - Australia

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