Urban Heat Island vulnerability mapping using advanced GIS data and tools
- Publisher:
- Springer Nature
- Publication Type:
- Journal Article
- Citation:
- Journal of Earth System Science, 2022, 131, (4), pp. 266
- Issue Date:
- 2022-12-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| s12040-022-02005-w.pdf | Published version | 2.22 MB |
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Urban Heat Island (UHI) is a phenomenon that can cause hotspots in city areas due to dense, impervious infrastructure and minimal vegetation cover. UHI hotspots may become worse in extreme heat events that are already affecting many regions across the globe due to increased frequent hot extremes, human-induced warming in cities, and rapidly growing urbanization, as documented by the latest IPCC report 2021. In seeking to support designers, planners, and decision-makers in developing and implementing adaptation strategies and measures to make our cities sustainable and resilient, reliable projections and modelling are required. In this study, we modelled UHI vulnerability using high-resolution spatial data, advanced geospatial tools, and socio-demographic data. This modified vulnerability approach drew upon UHI index maps and 20 select customized indicators of heat exposure, population sensitivity, and mobility/adaptive capacity. The indicators were Delphi evaluated and weighted, and the methodology was applied against the City of Greater Geelong municipality in Australia. The resulting UHI index maps indicated significant hotspots in areas of high building density, commercial/industrial zones, newly constructed sites, and zones with low urban green infrastructure. These UHI maps, in combination with selected indicators, highlighted the areal concentration of heat risk areas and vulnerable locations for the sensitive human population. The highlighted areas were primarily concentrated in high building density and high population density areas, which was seen through correlation curves. However, the building density showed a weak correlation, and population per meshblock indicated a strong correlation with UHI measurements. This study provides a comprehensive analysis of risk mapping and vulnerability assessment using GIS geospatial data for the advancement of a major local government area and concludes that this methodology has replicability incomparable geographical regions.
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