Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks.

Brelsford, Christa; Rosenheim, Nathanael; Wang, Mark

doi:10.15485/3006139

Title: Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks.

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Abstract

These data support the manuscript "Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks." These data are generated to allow water managers to reason about optimal locations to expand a flood observation system from multiple perspectives, specifically focusing on flood hazards, and population exposure to flooding. The data included are a) a shapefile of individual sensor locations b) a shapefile of river reach catchments, c) raster of FEMA flood likelihood layers d) shapefile of population locations and population socioeconomic characteristics. The code is written in R and includes all files necessary to generate the figures for the associated manuscript. Interactive maps of the final calculated maps of hazard, vulnerability, exposure, and risk are also included as html files.

Authors:

;

Analytics, Information and Technology Division, Los Alamos National Laboratory, Los Alamos, NM
Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX
Fariborz Maseeh Dept. of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX

Publication Date:: Wed Jan 01 00:00:00 UTC 2025

DOE Contract Number:: AC02-05CH11231

Research Org.:: Southeast Texas Urban Integrated Field Laboratory (SETx UIFL) – Equitable solutions for communities caught between floods and air pollution

Sponsoring Org.:: ESS-DIVE; U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > HUMAN DIMENSIONS > INFRASTRUCTURE; EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS; EARTH SCIENCE > HUMAN DIMENSIONS > POPULATION; EARTH SCIENCE > HUMAN DIMENSIONS > POPULATION > POPULATION DENSITY; EARTH SCIENCE > HUMAN DIMENSIONS > SOCIAL BEHAVIOR > VULNERABILITY LEVELS/INDEX; EARTH SCIENCE > LAND SURFACE > GEOMORPHIC LANDFORMS/PROCESSES > COASTAL PROCESSES > FLOODING; Flood; Risk

OSTI Identifier:: 3006139

DOI:: https://doi.org/10.15485/3006139

Citation Formats


                    Brelsford, Christa, Rosenheim, Nathanael, and Wang, Mark. Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks..  United States: N. p., 2025. 
        Web.  doi:10.15485/3006139.

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                    Brelsford, Christa, Rosenheim, Nathanael, & Wang, Mark. Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks..  United States.  doi:https://doi.org/10.15485/3006139

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                    Brelsford, Christa, Rosenheim, Nathanael, and Wang, Mark. 2025.  
"Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks.".  United States.  doi:https://doi.org/10.15485/3006139.  https://www.osti.gov/servlets/purl/3006139. Pub date:Wed Jan 01 00:00:00 UTC 2025

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@article{osti_3006139,

  title        = {Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks.},

  author       = {Brelsford, Christa and Rosenheim, Nathanael and Wang, Mark},

  abstractNote = {These data support the manuscript "Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks." These data are generated to allow water managers to reason about optimal locations to expand a flood observation system from multiple perspectives, specifically focusing on flood hazards, and population exposure to flooding. The data included are a) a shapefile of individual sensor locations b) a shapefile of river reach catchments, c) raster of FEMA flood likelihood layers d) shapefile of population locations and population socioeconomic characteristics. The code is written in R and includes all files necessary to generate the figures for the associated manuscript. Interactive maps of the final calculated maps of hazard, vulnerability, exposure, and risk are also included as html files.},

  doi          = {10.15485/3006139},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jan 01 00:00:00 UTC 2025},

  month        = {Wed Jan 01 00:00:00 UTC 2025}

}

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DOI: https://doi.org/10.15485/3006139

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