systemwide_header_logoalttext

Mapping Vermont Flooding and Vulnerable Communities in Preparation for Future Events: RoadClosures2023

Download Metadata
View Metadata in XML Format

dataset_eml_metadataproviderheader

  • Forest Ecosystem Monitoring Cooperative

    • Address:
      705 Spear Street
      South Burlington, Vermont 05403
      United States of America

      Phone: (802) 391-4135
      Email: femc@uvm.edu
      Website: www.uvm.edu/femc

dataset_eml_abstractheader

    Vermont is expected to experience more frequent and more intense flooding. Often, groups who are socially vulnerable are more prone to flood hazard. This project identified “Vulnerable Frontline Vermont Communities” (VFVCs), towns who are both at risk for flooding, and experience high social vulnerability in Vermont. Flood risk was mapped with the Rapid Infrastructure Flooding Tool (PNNL, 2023), drone imagery, and E911 building footprints (VT E911, 2025). Towns with high social vulnerability were identified by mapping the agreement between environmental justice screening tools; EJScreen (EPA, 2024), the Climate Economic Justice Screening Tool (White House, 2024), the VT Environmental Disparities Index (Ren, 2023), and Municipal Climate Change Vulnerability Indicators List (VT ANR, 2025). Hot-spot analysis was performed to identify the towns that met the criteria to be a VFVC. An advisory board that included stakeholders in flood resiliency in Vermont were consulted throughout the project, and participated in a validation activity to ground-truth the VFVCs. In addition, a case study was held in Barre City, to evaluate the results at the community level. These data can be used to inform stakeholders in flood mitigation of strong candidates for equitable flood hazard mitigation in Vermont. This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G21AP10630-00 to the Vermont Water Resources and Lake Studies Center.

dataset_eml_peopleheader

  • Kristine Stepenuck: dataset_eml_peopleprincipleinvestigator

  • Samantha Grant: dataset_eml_peopleprincipleinvestigator

Organizations

  • Vermont Water Center Vermont Water Resources & Lake Studies Center: funder

dataset_eml_locationheader

  • dataset_eml_locationcords

    dataset_eml_datatableheader

    • dataset_eml_datatabletitle: RoadClosures2023
    • dataset_eml_datatablestartdate: 2024-09-01
    • dataset_eml_datatableendate: 2025-08-31
    • dataset_eml_datatabledescription: Shapefile that includes road closures documented on July 11th 11:40pm, and July 12th at 9:45am, given the Great Vermont Flood of July 2023. Lines are digitized from Vermont Agency of Transportation Traffic Management Center notifications.

    • dataset_eml_datatablepurpose: This dataset was supplemental to the project objectives.

    • dateset_eml_datatableshortname: 20250529130819_RoadClosures2023.zip

    • dataset_eml_datatablephysicalobjectname: VMC.1830.4049

    • dataset_eml_datatabledatatype: mySQL
    • dataset_eml_datatablecitation: Grant, S. (2025). RoadClosures2023. FEMC. Available online at: https://www.uvm.edu/femc/data/archive/project/mapping-vermont-flooding-and-vulnerable-communities-in-preparation-for-future-events-/dataset/roadclosures2023

    • dataset_eml_datatableonlinedistribution: https://www.uvm.edu/femc/CI4/data/archive/project/mapping-vermont-flooding-and-vulnerable-communities-in-preparation-for-future-events-/dataset/roadclosures2023

    dataset_eml_attributelistheader

      dataset_eml_attributelistname: ObjectID
      • dataset_eml_attributelistlabel: ObjectID
      • dataset_eml_attributelistdescription: Unique spatial identifier for each entry.
      • dataset_eml_attributeliststoragetype: int
      • dataset_eml_attributelistmeasurementtype: nominal
      • dataset_eml_attributelistformatstring: D-M-YY
      • dataset_eml_attributelistnumbertype: -1
      dataset_eml_attributelistname: Shape_
      • dataset_eml_attributelistlabel: Shape
      • dataset_eml_attributelistdescription: Line
      • dataset_eml_attributeliststoragetype: int
      • dataset_eml_attributelistmeasurementtype: nominal
      • dataset_eml_attributelistformatstring: D-M-YY
      • dataset_eml_attributelistnumbertype: -1
      dataset_eml_attributelistname: Shape_Length
      • dataset_eml_attributelistlabel: Shape_Length
      • dataset_eml_attributelistdescription: Length of road segment.
      • dataset_eml_attributeliststoragetype: int
      • dataset_eml_attributelistmeasurementtype: nominal
      • dataset_eml_attributelistformatstring: D-M-YY
      • dataset_eml_attributelistnumbertype: -1
      dataset_eml_attributelistname: Road
      • dataset_eml_attributelistlabel: Road
      • dataset_eml_attributelistdescription: Location of road closure.
      • dataset_eml_attributeliststoragetype: text
      • dataset_eml_attributelistmeasurementtype: nominal
      • dataset_eml_attributelistformatstring: D-M-YY
      • dataset_eml_attributelistnumbertype: -1
      dataset_eml_attributelistname: Cause
      • dataset_eml_attributelistlabel: Cause
      • dataset_eml_attributelistdescription: Identified cause of the road closure (if labelled by Traffic Management Center).
      • dataset_eml_attributeliststoragetype: text
      • dataset_eml_attributelistmeasurementtype: nominal
      • dataset_eml_attributelistformatstring: D-M-YY
      • dataset_eml_attributelistnumbertype: -1
      dataset_eml_attributelistname: FullorPartial
      • dataset_eml_attributelistlabel: Full or Partial
      • dataset_eml_attributelistdescription: Full = Full Road Closure vs. Partial = Partial Road Closure (I.e. One Lane is Closed).
      • dataset_eml_attributeliststoragetype: text
      • dataset_eml_attributelistmeasurementtype: nominal
      • dataset_eml_attributelistformatstring: D-M-YY
      • dataset_eml_attributelistnumbertype: -1

    dataset_eml_methodsheader

    • dataset_eml_noMethods

    dataset_eml_samplingheader

    • dataset_eml_noSamplingEquipment

    dataset_eml_sitecharacteristicsheader

    • dataset_eml_noSiteCharacteristics