CAREER: Addressing Flood Justice and Equity Impacts of Adaptation and Urban Expansion with Satellite Observations

洪水比任何其他自然灾害影响的人都多。为了扩大城市开发，保护物业价值，并避免支付洪水保险，美国的房地产开发商要求从联邦紧急事务管理署(FEMA)监管的泛滥平原移除房产，通常是通过堤坝和排水等防洪基础设施。然而，这类基础设施经常将洪水分流到下游其他地区，这一影响尚未得到很好的研究。服务不足的社区受到的影响最大，但可能没有工具来挑战他们在洪水地图或分区变化中的代表性不足。该学院早期职业发展计划(CALEAR)奖支持旨在通过生成观测洪水数据来提高基础知识的研究，以衡量防洪基础设施是否以及在哪里改变了洪水模式以及谁受到了影响。该项目建设了使用基于卫星的地图来对抗洪水地图上的不公正行为的能力，并倡导更公平地分配缓解资金。这个项目审查了过去导致服务不足的社区面临更多洪灾的政策，并揭示了他们长期存在的不公正。随着洪灾在不断变化的气候中影响更多的人和财产，公共政策必须演变以应对这种日益增长的风险，并优先保护最脆弱的人。目前监管的泛滥平原地图低估了洪水风险，部分原因是通过地图修订信使(LOMR)政策减少了洪水风险。为了评估重新绘制的地图的准确性，该项目记录了由于LOMR政策而导致洪水平原减少的地方，并建立了2001至2023年间来自多个卫星来源的洪水事件的空间数据库。这项工作将通过将普查数据与卫星观测和统计模型结合起来，评估洪水风险的负担是否在不同人口和社区之间转移，解决防洪基础设施在多大程度上放大了洪水风险暴露的不平等问题。该项目培训来自环境正义组织的学生和工作人员共同制作基于卫星的人工智能工具来绘制洪水地图。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Floods affect more people than any other natural hazard. To expand urban development, preserve property values, and avoid paying for flood insurance, real estate developers in the US request to remove properties from the Federal Emergency Management Agency (FEMA) regulatory floodplain, often through flood protection infrastructures such as levees and drainage. However, such infrastructures frequently divert floodwaters to others downstream, an effect that has not been well studied. Underserved communities are the most exposed but may not have the tools to challenge their underrepresentation in flood maps or zoning changes. This Faculty Early Career Development Program (CAREER) award supports research which aims to advance foundational knowledge by generating observed flood data to measure if and where flood protection infrastructures change flooding patterns as well as who is affected. The project builds capacity for using satellite-based maps to counter unjust actions from flood maps and advocate for more equitable allocation of mitigation funding. This project examines past policies that have contributed to increased flood exposure of underserved communities and sheds light on their long-standing injustice.As floods impact more people and properties in a changing climate, public policies must evolve to address this growing risk and prioritize protection for the most vulnerable. Current regulatory floodplain maps underrepresent flood risk in part due to reductions though the Letters of Map Revision (LOMR) policy. To evaluate the accuracy of redrawn maps, this project documents where floodplains have been reduced because of LOMR policies and builds a spatial database of flood events from multiple satellite sources between 2001 and 2023. The work will address the question of the extent to which flood protection infrastructures are responsible for amplifying inequality in flood exposure by combining census data with satellite observations and statistical models to assess if the burden of flood risk has shifted among different demographics and communities. The project trains students and staff from environmental justice organizations to co-produce satellite-based AI tools for flood mapping.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.