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Urban heat risk mapping using multiple point patterns in Houston, Texas

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  • Jacob W. Mortensen
  • Matthew J. Heaton
  • Olga V. Wilhelmi

Abstract

Extreme heat, or persistently high temperatures in the form of heatwaves, adversely impacts human health. To study such effects, risk maps are a common epidemiological tool that is used to identify regions and populations that are more susceptible to these negative outcomes; however, the negative health effects of high temperatures are manifested differently between different segments of the population. We propose a novel, hierarchical marked point process model that merges multiple health outcomes into an overall heat risk map. Specifically, we consider health outcomes of heat‐stress‐related emergency service calls and mortalities across the city of Houston, Texas. We show that combining multiple health outcomes leads to a broader understanding of the spatial distribution of heat risk than a single health outcome.

Suggested Citation

  • Jacob W. Mortensen & Matthew J. Heaton & Olga V. Wilhelmi, 2018. "Urban heat risk mapping using multiple point patterns in Houston, Texas," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(1), pages 83-102, January.
    • Handle: RePEc:bla:jorssc:v:67:y:2018:i:1:p:83-102
    DOI: 10.1111/rssc.12224
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    Cited by:

    1. Heaton, Matthew J. & Dahl, Benjamin K. & Dayley, Caleb & Warr, Richard L. & White, Philip, 2024. "Integrating machine learning and Bayesian nonparametrics for flexible modeling of point pattern data," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    2. Wei Zhang & Phil McManus & Elizabeth Duncan, 2018. "A Raster-Based Subdividing Indicator to Map Urban Heat Vulnerability: A Case Study in Sydney, Australia," IJERPH, MDPI, vol. 15(11), pages 1-20, November.

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