Scholarlink

<p>Over 2.4 million properties in the United States, both residential and commercial, could face chronic flooding by the century’s end. Despite FEMA’s role in defining Special Flood Hazard Areas (SFHAs), regulating new developments, and mandating flood insurance for federally backed mortgages, the efficacy of these policies in reducing population risk remains uncertain. This article relies on advancements in urban analytics and causal inference to scrutinize the accuracy of SFHAs in identifying flood-prone structures and evaluates the quality and condition of buildings within and outside these areas. Our study, based on a new database covering over 100,000 flood-prone buildings in Houston, Texas, reveals that 56% of at-risk structures lie outside SFHAs, with a disproportionate concentration in Black and Hispanic neighborhoods. We demonstrate that buildings outside SFHAs are more likely to be of substandard quality, poorly maintained, and uninsured. While SFHA-related policies may mitigate population vulnerability, limitations in flood mapping could also exacerbate disparities across neighborhoods, particularly affecting minority communities. Addressing existing knowledge gaps concerning interactions across different forms of vulnerability, our findings indicate that at-risk socially vulnerable communities also contend with greater structural and financial vulnerability. We conclude that advancements in urban population analytics can enable better planning for future flood events.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Flood risk and the built environment: big property data for environmental justice and social vulnerability analysis

  • 期刊论文

  • 发表日期：

    2025年2月26日

查看全文
  • Yilei Yu,
  • Aaron Flores,
  • Dylan Connor,
  • Sara Meerow,
  • Anna E. Braswell,
  • Stefan Leyk

摘要

Over 2.4 million properties in the United States, both residential and commercial, could face chronic flooding by the century’s end. Despite FEMA’s role in defining Special Flood Hazard Areas (SFHAs), regulating new developments, and mandating flood insurance for federally backed mortgages, the efficacy of these policies in reducing population risk remains uncertain. This article relies on advancements in urban analytics and causal inference to scrutinize the accuracy of SFHAs in identifying flood-prone structures and evaluates the quality and condition of buildings within and outside these areas. Our study, based on a new database covering over 100,000 flood-prone buildings in Houston, Texas, reveals that 56% of at-risk structures lie outside SFHAs, with a disproportionate concentration in Black and Hispanic neighborhoods. We demonstrate that buildings outside SFHAs are more likely to be of substandard quality, poorly maintained, and uninsured. While SFHA-related policies may mitigate population vulnerability, limitations in flood mapping could also exacerbate disparities across neighborhoods, particularly affecting minority communities. Addressing existing knowledge gaps concerning interactions across different forms of vulnerability, our findings indicate that at-risk socially vulnerable communities also contend with greater structural and financial vulnerability. We conclude that advancements in urban population analytics can enable better planning for future flood events.