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NCCOS Assessment: Community Vulnerability Assessment to Flood Hazard in the United States Virgin Islands, 2023-01-01 to 2024-08-30

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NIAID Data Ecosystem2026-05-02 收录
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https://doi.org/10.7910/DVN/CZTITY
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资源简介:
This dataset includes estate level component scores of various indices from the National Centers for Coastal Ocean Science (NCCOS) Community Assessment to Flood Hazard in the United States Virgin Islands (USVI). Indices include social vulnerability, structural vulnerability (and sub-indices), structural exposure (and sub-indices), nearshore environment protection benefits, compounded flood hazard, waterborne toxins and contaminants, vegetation, and potential walkability. Each component score is aggregated to the estate level geography provided by the U.S. Census Bureau. Additionally, intermediary raster-based datasets on stormwater flooding potential, compounded flooding (both near-term-moderate and projected-high), orbital velocity data, a Shannon land use diversity index, and a Visible Atmospherically Resistant Index (VARI) are included. This assessment used a geospatial, indicator-driven approach to integrate data from a variety of sources related to community vulnerability in the USVI. These data included measures of social and structural vulnerability and exposure, the nearshore environment, flood hazards, waterborne toxins and contaminants, vegetation, and potential walkability. These indicators were based on territorial needs, existing research, local stakeholder feedback, and data feasibility checks. Each component was analyzed using publicly available data, renormalized using a min-max normalization method, and aggregated to estate-level geographies. These were then categorized into statistical quantile breaks to show relative rankings across the territory. This integrative approach supports bivariate choropleth mapping for highlighting areas of co-occurrence and prioritization and also highlights estate-level hazard and vulnerability. Additionally, several raster based indices were created in this assessment. For full dataset methods please see the NOAA Technical Memorandum NOS NCCOS 334 at https://repository.library.noaa.gov/view/noaa/66566.
创建时间:
2025-04-21
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