5 datasets found
  1. Data from: Improving public safety through spatial synthesis, mapping,...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Dec 25, 2024
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    Miguel Jaller; James Thorne; Jason Whitney; Daniel Rivera-Royero (2024). Improving public safety through spatial synthesis, mapping, modeling, and performance analysis of emergency evacuation routes in California localities [Dataset]. http://doi.org/10.5061/dryad.w9ghx3g0j
    Explore at:
    zipAvailable download formats
    Dataset updated
    Dec 25, 2024
    Dataset provided by
    University of California, Davis
    Authors
    Miguel Jaller; James Thorne; Jason Whitney; Daniel Rivera-Royero
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    California
    Description

    The risk of natural disasters, many of which are amplified by climate change, requires the protection of emergency evacuation routes to permit evacuees safe passage. California has recognized the need through the AB 747 Planning and Zoning Law, which requires each county and city in California to update their - general plans to include safety elements from unreasonable risks associated with various hazards, specifically evacuation routes and their capacity, safety, and viability under a range of emergency scenarios. These routes must be identified in advance and maintained so they can support evacuations. Today, there is a lack of a centralized database of the identified routes or their general assessment. Consequently, this proposal responds to Caltrans’ research priority for “GIS Mapping of Emergency Evacuation Routes.” Specifically, the project objectives are: 1) create a centralized GIS database, by collecting and compiling available evacuation route GIS layers, and the safety element of the evacuation routes from different jurisdictions as well as their use in various types of evacuation scenarios such as wildfire, flooding, or landslides. 2) Perform network analyses and modeling based on the team’s experience with road network performance, access restoration, and critical infrastructure modeling, for a set of case studies, as well as, assessing their performance considering the latest evacuation research. 3) Analyze how well current bus and rail routes align with evacuation routes; and for a series of case studies, using data from previous evacuations, evaluate how well aligned the safety elements of the emerging plans are, relative to previous evacuation routes. And 4) analyze different metrics about the performance of the evacuation routes for different segments of the population (e.g., elderly, mobility constrained, non-vehicle households, and disadvantaged communities). The database and assessments will help inform infrastructure investment decisions and to develop recommendations on how best to maintain State transportation assets and secure safe evacuation routes, as they will identify the road segments with the largest impact on the evacuation route/network performance. The project will deliver a GIS of the compiled plans, a report summarizing the creation of the database and the analyses and will make a final presentation of the study results. Methods The project used the following public datasets: • Open Street Map. The team collected the road network arcs and nodes of the selected localities and the team will make public the graph used for each locality. • National Risk Index (NRI): The team used the NRI obtained publicly from FEMA at the census tract level. • American Community Survey (ACS): The team used ACS data to estimate the Social Vulnerability Index at the census block level. Then the author developed a measurement to estimate the road network performance risk at the node level, by estimating the Hansen accessibility index, betweenness centrality and the NRI. Create a set of CSV files with the risk for more than 450 localities in California, on around 18 natural hazards. I also have graphs of the RNP risk at the regional level showing the directionality of the risk.

  2. c

    Tsunami Evacuation Travel Time Map for Del Norte County, CA, 2010, for...

    • s.cnmilf.com
    • dataone.org
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Tsunami Evacuation Travel Time Map for Del Norte County, CA, 2010, for Bridges Removed and a Fast Walking Speed [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tsunami-evacuation-travel-time-map-for-del-norte-county-ca-2010-for-bridges-removed-and-a--0b2f5
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Del Norte County, California
    Description

    The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. The travel time analysis uses ESRI's Path Distance tool to find the shortest distance across a cost surface from any point in the hazard zone to a safe zone. This cost analysis considers the direction of movement and assigns a higher cost to steeper slopes, based on a table contained within the model. The analysis also adds in the energy costs of crossing different types of land cover, assuming that less energy is expended walking along a road than walking across a sandy beach. To produce the time map, the evacuation surface output from the model is grouped into 1-minute increments for easier visualization. The times in the attribute table represent the estimated time to travel on foot to the nearest safe zone at the speed designated in the map title. The bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed prior to modeling to estimate the impact on travel times from earthquake-damaged bridges.

  3. Operations - Evacuation - Static - Polygon - CA / Historic Evacuation Zones...

    • 2025-la-fires-calema.hub.arcgis.com
    Updated Jan 23, 2025
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    FEMA (2025). Operations - Evacuation - Static - Polygon - CA / Historic Evacuation Zones (CalOES/R9) [Dataset]. https://2025-la-fires-calema.hub.arcgis.com/items/732dfda3f6dc45418a9d29f559d28943
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    Dataset updated
    Jan 23, 2025
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    FEMA
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Source Item: https://calema.maps.arcgis.com/home/item.html?id=15fb71971c7246338440d39b9f158bd7The data for this feature service is derived from the CalOES feed indicated at the source item above, which compiles evacuation zone data from multiple local services into a single feed. Since the CalOES feed is a live service showing currently active evacuation orders and warnings, this historic feature service was developed by merging the backups of the live service run daily at 3AM Pacific Time. This database maintains all field headings, field values, and feature polygons of the original CalOES service while adding an EFFECTIVE_DATE_R9 date field to indicate the day and hour that the backup script was run. In order to isolate a specific period of active evacuations, apply a filter to the EFFECTIVE_DATE_R9 field.This service is currently in development. At this time it consists of evacuation data starting January 7th 2025 and is updated daily with the most recent daily backup.

  4. d

    Tsunami Evacuation Travel Time Map for Humboldt County, CA, 2010, for...

    • catalog.data.gov
    • search.dataone.org
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Tsunami Evacuation Travel Time Map for Humboldt County, CA, 2010, for Bridges Removed and a Slow Walking Speed [Dataset]. https://catalog.data.gov/dataset/tsunami-evacuation-travel-time-map-for-humboldt-county-ca-2010-for-bridges-removed-and-a-s
    Explore at:
    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Humboldt County
    Description

    The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. The travel time analysis uses ESRI's Path Distance tool to find the shortest distance across a cost surface from any point in the hazard zone to a safe zone. This cost analysis considers the direction of movement and assigns a higher cost to steeper slopes, based on a table contained within the model. The analysis also adds in the energy costs of crossing different types of land cover, assuming that less energy is expended walking along a road than walking across a sandy beach. To produce the time map, the evacuation surface output from the model is grouped into 1-minute increments for easier visualization. The times in the attribute table represent the estimated time to travel on foot to the nearest safe zone at the speed designated in the map title. The bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed prior to modeling to estimate the impact on travel times from earthquake-damaged bridges.

  5. e

    EMCR: EmergencyMapBC

    • climate.esri.ca
    • climate-change-esricanada.hub.arcgis.com
    Updated Mar 6, 2019
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    B.C.'s Map Hub (2019). EMCR: EmergencyMapBC [Dataset]. https://climate.esri.ca/datasets/governmentofbc::emcr-emergencymapbc
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    Dataset updated
    Mar 6, 2019
    Dataset authored and provided by
    B.C.'s Map Hub
    Description

    EmergencyMapBC is overseen by EmergencyInfoBC and serves as a general reference for current public safety conditions during emergencies. This application displays information related to emergencies in British Columbia from the Ministry of Emergency Management and Climate Readiness. EmergencyMapBC includes Evacuation Alert and Order layers that indicate which areas of BC have been issued an Evacuation Alert or Evacuation Order in response to a potential hazard. In addition, locations of Emergency Support Services Reception Centres are viewable, as well as flood watches and warnings issued by the Province of British Columbia. For more information on emergencies, please visit https://www.emergencyinfobc.gov.bc.ca/ .A GeoBC production in association with Emergency Management and Climate Readiness BC.BC Data Catalogue Metadata: https://catalogue.data.gov.bc.ca/dataset/70bb4164-b353-499f-91c6-7c5d65a73eedCOPYRIGHT | DISCLAIMER | PRIVACY | ACCESSIBILITY

  6. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Click to copy link
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Miguel Jaller; James Thorne; Jason Whitney; Daniel Rivera-Royero (2024). Improving public safety through spatial synthesis, mapping, modeling, and performance analysis of emergency evacuation routes in California localities [Dataset]. http://doi.org/10.5061/dryad.w9ghx3g0j
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Data from: Improving public safety through spatial synthesis, mapping, modeling, and performance analysis of emergency evacuation routes in California localities

Related Article
Explore at:
zipAvailable download formats
Dataset updated
Dec 25, 2024
Dataset provided by
University of California, Davis
Authors
Miguel Jaller; James Thorne; Jason Whitney; Daniel Rivera-Royero
License

https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

Area covered
California
Description

The risk of natural disasters, many of which are amplified by climate change, requires the protection of emergency evacuation routes to permit evacuees safe passage. California has recognized the need through the AB 747 Planning and Zoning Law, which requires each county and city in California to update their - general plans to include safety elements from unreasonable risks associated with various hazards, specifically evacuation routes and their capacity, safety, and viability under a range of emergency scenarios. These routes must be identified in advance and maintained so they can support evacuations. Today, there is a lack of a centralized database of the identified routes or their general assessment. Consequently, this proposal responds to Caltrans’ research priority for “GIS Mapping of Emergency Evacuation Routes.” Specifically, the project objectives are: 1) create a centralized GIS database, by collecting and compiling available evacuation route GIS layers, and the safety element of the evacuation routes from different jurisdictions as well as their use in various types of evacuation scenarios such as wildfire, flooding, or landslides. 2) Perform network analyses and modeling based on the team’s experience with road network performance, access restoration, and critical infrastructure modeling, for a set of case studies, as well as, assessing their performance considering the latest evacuation research. 3) Analyze how well current bus and rail routes align with evacuation routes; and for a series of case studies, using data from previous evacuations, evaluate how well aligned the safety elements of the emerging plans are, relative to previous evacuation routes. And 4) analyze different metrics about the performance of the evacuation routes for different segments of the population (e.g., elderly, mobility constrained, non-vehicle households, and disadvantaged communities). The database and assessments will help inform infrastructure investment decisions and to develop recommendations on how best to maintain State transportation assets and secure safe evacuation routes, as they will identify the road segments with the largest impact on the evacuation route/network performance. The project will deliver a GIS of the compiled plans, a report summarizing the creation of the database and the analyses and will make a final presentation of the study results. Methods The project used the following public datasets: • Open Street Map. The team collected the road network arcs and nodes of the selected localities and the team will make public the graph used for each locality. • National Risk Index (NRI): The team used the NRI obtained publicly from FEMA at the census tract level. • American Community Survey (ACS): The team used ACS data to estimate the Social Vulnerability Index at the census block level. Then the author developed a measurement to estimate the road network performance risk at the node level, by estimating the Hansen accessibility index, betweenness centrality and the NRI. Create a set of CSV files with the risk for more than 450 localities in California, on around 18 natural hazards. I also have graphs of the RNP risk at the regional level showing the directionality of the risk.

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