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<p>Natural hazards such as tropical cyclones (TCs) cause widespread destruction. Historical impact data provides a resource for understanding TC impacts and associated societal vulnerabilities which is essential for building resilience. However, characteristics of impact data such as resolution and coverage can influence its utility for disaster risk reduction (DRR) applications. With this in mind, we present a province-level impact dataset for TCs in the Philippines between 2010 and 2020 for deaths, affected population, housing damage and economic loss curated for DRR applications. Specifically, we evaluate the effect of the dataset’s spatial resolution and its coverage of hazard intensities, impact magnitudes and impact types and discuss the implications for DRR applications. Considering the utility of impact data within the context of DRR is crucial, and a dataset with comprehensive coverage of impact and hazard magnitudes and appropriate spatial resolution is pivotal for DRR applications. The research presents a guide for others using this dataset and data more generally in DRR applications.</p>

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Tropical cyclone impact data in the Philippines: implications for disaster risk research

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月20日

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  • Elizabeth G. Galloway,
  • Jennifer L. Catto,
  • Chunbo Luo,
  • Stefan Siegert

摘要

Natural hazards such as tropical cyclones (TCs) cause widespread destruction. Historical impact data provides a resource for understanding TC impacts and associated societal vulnerabilities which is essential for building resilience. However, characteristics of impact data such as resolution and coverage can influence its utility for disaster risk reduction (DRR) applications. With this in mind, we present a province-level impact dataset for TCs in the Philippines between 2010 and 2020 for deaths, affected population, housing damage and economic loss curated for DRR applications. Specifically, we evaluate the effect of the dataset’s spatial resolution and its coverage of hazard intensities, impact magnitudes and impact types and discuss the implications for DRR applications. Considering the utility of impact data within the context of DRR is crucial, and a dataset with comprehensive coverage of impact and hazard magnitudes and appropriate spatial resolution is pivotal for DRR applications. The research presents a guide for others using this dataset and data more generally in DRR applications.