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A Spatial Framework to Map Heat Health Risks at Multiple Scales.

Hung Chak Ho1,2, Anders Knudby3, Wei Huang4

  • 1Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. hohungh@sfu.ca.

International Journal of Environmental Research and Public Health
|December 24, 2015
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Summary

Extreme heat events cause excess mortality. A new raster-based model effectively maps heat risk hotspots, overcoming spatial scale issues to identify vulnerable areas for mitigation.

Keywords:
extremely hot weather eventheat riskheat vulnerabilitymodifiable areal unit problem

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Area of Science:

  • Environmental science
  • Public health
  • Geographic information systems

Background:

  • Extreme heat events have caused significant excess mortality globally.
  • Climate change is projected to increase the frequency and severity of heatwaves.
  • Mapping heat risk is crucial for effective mitigation strategies.

Purpose of the Study:

  • To develop and evaluate a raster-based model for integrating heat exposure and vulnerability data.
  • To address spatial scale issues, such as the Modifiable Areal Unit Problem (MAUP), in heat risk mapping.
  • To generate spatially smoothed heat risk hotspot maps at various scales.

Main Methods:

  • A raster-based multi-criteria decision analysis model was developed to integrate heat exposure and vulnerability data.
  • The Getis-Ord G(i) index was used for spatial smoothing and hotspot identification.
  • The raster-based model was compared against a traditional vector-based approach.

Main Results:

  • The raster-based model produced higher-resolution heat risk maps, revealing local-scale variability.
  • It identified heat-risk areas missed by the vector-based method.
  • Spatially smoothed maps effectively identified heat risk hotspots from local to regional scales.

Conclusions:

  • The raster-based approach effectively reduces spatial scale issues in heat risk mapping.
  • This framework enables the identification of heat risk hotspots at granular levels (block to municipality).
  • The methodology provides a robust tool for targeted public health interventions during extreme heat events.