SCC-PG: Flood Hazard Management & Practitioner Information Network for Florida Coastal Communities
SCC-PG: Flood Hazard Management & Practitioner Information Network for Florida Coastal Communities
批准号:
1951997
负责人:
Ravi Srinivasan
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-15 至 2021-06-30
中文摘要
佛罗里达州在估计住宅可能受到飓风风暴潮破坏方面排名全国第一。灾前规划和灾后恢复活动的基础是提供综合数据集,帮助社区更好地了解面临风险的负担得起的住房存量的类型和数量。然而,即使有了这些数据集,这些数据集往往也可能过时、不完整、没有在地方部门管辖范围内共享,或者需要大量处理才能对规划和恢复活动更加有用。从业者迫切需要能够利用彼此的信息、技能和经验来制定前瞻性战略,以创建更具弹性的负担得起的住房体系。这一规划赠款项目为佛罗里达沿海社区创建了洪水灾害管理和从业者信息网,为未来的灾前和灾后管理以及加强与沿海社区有关的技术和社会/规划问题奠定了基础。这一项目的重点将是共同对问题和建造更具弹性的负担得起的住房的挑战进行更全面的描述,以及共同制定一个过程,以制定对社区既有效又有用的解决方案。为了建立这个新的从业者信息网络,佛罗里达大学将与佛罗里达州的一个县和一个地区规划委员会合作,该委员会可以在更广泛的地区范围内进行扩展。这一智能互联社区规划赠款项目为佛罗里达沿海社区创建了洪水灾害管理和从业者信息网络,为未来的灾前和灾后管理以及加强与沿海社区相关的技术和社会/规划问题奠定了基础。该项目在三个研究信托下应对综合研究挑战:(1)数据和信息:创建邻里洪水灾害类型;(2)增加信息获取-智能和互联信息基础设施;以及(3)连接社区-洪水灾害管理和从业者信息网络。其中,该项目开发和测试了新的可扩展方法,以无缝地获取、验证和传输与县住宅建筑最低楼层高度和其他相关特征中的三个试点社区相关的数据,这些特征决定了住房信息系统的洪水风险。可扩展的方法包括通过公共可用的街道视图和通过群众来源收集的数据进行基于图像的处理。通过两个以社区为基础的参与性研讨会,该项目共同对问题和创建更具弹性的负担得起的住房的挑战进行了更全面的描述,并制定了一个既有效又对社区有用的解决方案的过程。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。
英文摘要
Florida ranks first in the nation for estimated potential residential exposure to hurricane storm surge damage. Fundamental to pre-disaster planning and post-disaster recovery activities is the availability of integrated datasets that can help communities better understand the type and quantity of affordable housing stock at risk. However, oftentimes, even when available, these datasets may be outdated, incomplete, not shared across local departmental jurisdictions, or need significant processing to become more useful for planning and recovery activities. There is an urgent need for practitioners to be able to leverage each other’s information, skills, and experience to develop forward-looking strategies to create a more resilient affordable housing system. This Planning Grant project creates a Flood Hazard Management and Practitioner Information Network for Florida Coastal Communities to establish the foundation for future pre- and post-disaster management as well as strengthening technological and social/planning issues related to coastal communities. This project will focus on co-producing a more comprehensive description of the problem and the challenges to creating more resilient affordable housing, as well as co-producing a process to develop solutions that are both effective and useful to the community. To seed this new Practitioner Information Network, University of Florida will collaborate with a county and a Regional Planning Council in Florida which can be scaled across broader regions. This Smart & Connected Communities Planning Grant project creates a Flood Hazard Management and Practitioner Information Network for Florida Coastal Communities to establish the foundation for future pre- and post-disaster management as well as strengthening technological and social/planning issues related to coastal communities. This project answers integrative research challenges under three Research Trusts: (1) Data and Information: Creating a Neighborhood Flood Hazard typologies; (2) Increasing Information Access - Smart and Connected Information Infrastructure; and (3) Connecting Communities - Flood Hazard Management and Practitioner Information Network. Among others, this project develops and tests novel scalable methods to seamlessly acquire, validate, and transfer data related to three pilot communities in a county’s residential structures’ Lowest Floor Elevation and other pertinent characteristics that determines flood hazard to a Housing Information System. Scalable methods include image-based processing via publicly available street views and data gathered via crowd source. Through two community-based participatory workshops, this project co-produces a more comprehensive description of the problem and the challenges to creating more resilient affordable housing as well as a process to develop solutions that are both effective and useful to the community.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.
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资助金额:$2.98万
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财政年份:2016
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负责人:Ravi Srinivasan
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依托单位:
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