The Wildland-Urban Interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), we integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States from 1990-2020. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a geodatabase and include information such as housing densities for 1990, 2000, 2010, and 2020; wildland vegetation percentages for 1992, 2001, 2011, and 2019; as well as WUI classes in 1990, 2000, 2010, and 2020.This WUI feature class is separate from the WUI datasets maintained by individual forest unites, and it is not the authoritative source data of WUI for forest units. This dataset shows change over time in the WUI data up to 2020.Metadata and Downloads
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Downloads and additional Metadata. A tiled map service depicting wildland urban interface data for 2010. The wildland-urban interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), we integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States for 2010. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a feature class and include information such as housing and population densities for 2010; wildland vegetation percentages for 2011; as well as WUI class in 2010. This WUI feature class is separate from the WUI datasets maintained by individual forest units, and it is not the authoritative source data of WUI for forest units. This map service shows the WUI data for 2010 only.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.
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Downloads and additional Metadata. A tiled map service depicting wildland urban interface data for 2000. The wildland-urban interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), we integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States for 2000. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a feature class and include information such as housing and population densities for 2000; wildland vegetation percentages for 2001; as well as WUI class in 2000. This WUI feature class is separate from the WUI datasets maintained by individual forest units, and it is not the authoritative source data of WUI for forest units. This map service shows the WUI data for 2000 only.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.
OverviewORS 477.490 requires Oregon Sate University (OSU) and the Oregon Department of Forestry (ODF) to develop a statewide wildland-urban interface (WUI) map that will be used in conjunction with the statewide wildfire hazard map (ORS 477.490) by the Oregon State Fire Marshal to determine on which properties defensible space standards apply (ORS 476.392) and by the Building Codes Division to determine to which structures home hardening building codes apply (ORS 455.612).Rules directing development of the WUI are listed in OAR-629-044-1011 and 629-044-1016. A comprehensive description of datasets and geospatial processing is available at https://hazardmap.forestry.oregonstate.edu/understand-map. The official statewide WUI map is available on the Oregon Wildfire Risk Explorer at https://tools.oregonexplorer.info/viewer/wildfire.Following is an overview of the data and methods used develop the statewide WUI map.Wildland-Urban InterfaceCreating a statewide map of the WUI involved two general steps. First, we determined which parts of Oregon met the minimum building density requirements to be classified as WUI. Second, for those areas that met the minimum building density threshold, we evaluated the amount and proximity of wildland or vegetative fuels. Following is a summary of geospatial tasks used to create the WUI.Develop a potential WUI map of all areas that meet the minimum density of structures and other human development - According to OAR 629-044-1011, the boundary of Oregon’s WUI is defined in part as areas with a minimum building density of one building per 40 acres, the same threshold defined in the federal register (Executive Order 13728, 2016), and any area within an Urban Growth Boundary (UGB) regardless of the building density. Step One characterizes all the locations in Oregon that could be considered for inclusion in the WUI on building density and UGB extent alone. The result of Step One was a map of potential WUI which was then further refined into final WUI map based on fuels density and proximity in Step Two.Compile statewide tax lots.Map all eligible structures and other human development.Simplify structure dataset to no more than one structure per tax lotCalculate structure density and identify all areas with greater than one structure per 40 acresAdd urban growth boundaries to all the areas that meet the density requirements from the previous step.Classify WUI based on amount and proximity of fuel. The WUI is also defined by the density and proximity of wildland and vegetative fuels (“fuels”). By including density and proximity of fuels in the definition of the WUI, the urban core is excluded, and the focus is placed on those areas with sufficient building density and sufficient fuels to facilitate a WUI conflagration. Consistent with national standards, we further classified the WUI into three general classes to inform effective risk management strategies. The following describes how we refined the potential WUI output from step one into the fina
Jackson County Community Fire Plan Map 5 showing the Wildland Urban Interface and Public Lands. The map document is 11 inches by 17 inches.
Due to the mixed distribution of buildings and vegetation, wildland-urban interface (WUI) areas are characterized by complex fuel distributions and geographical environments. The behavior of wildfires occurring in the WUI often leads to severe hazards and significant damage to man-made structures. Therefore, WUI areas warrant more attention during the wildfire season. Due to the ever-changing dynamic nature of California’s population and housing, the update frequency and resolution of WUI maps that are currently used can no longer meet the needs and challenges of wildfire management and resource allocation for suppression and mitigation efforts. Recent developments in remote sensing technology and data analysis algorithms pose new opportunities for improving WUI mapping methods. WUI areas in California were directly mapped using building footprints extracted from remote sensing data by Microsoft along with the fuel vegetation cover from the LANDFIRE dataset in this study. To accommodate...
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This is a polygon data set depicting the areas designated by the City of Boise as Wildland-Urban Interface (WUI). WUI is defined as the area where structures and other human development meet or intermingle with undeveloped wildland. These areas have an increased likelihood that wildfires will threaten structures and people. The purpose of the dataset is to define areas with higher wildfire risk and subject those areas to increased FIREWISE standards for development.As a result of the Oregon Trail Heights fire in the late summer of 2008, the City Council passed Ordinance # 0-7A-10 adopting the new regulations for the WUI into the City’s fire code in early 2010. The ordinance establishes a range of responses including new fire code standards for construction, fuels mitigation and education in WUI areas.
Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information
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A Wildland Urban Interface (WUI) Location Project to locate WUI areas and estimate some characteristics about the interface area. Originated but Utah Division of Forestry, Fire and State Lands in 1999.
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This dataset provides global wildland-urban interface (WUI) maps at a spatial resolution of 30 meters for the years 2000, 2010, and 2020. The WUI is defined as areas where the 200-meter buffers of urban areas (characterized by artificial surfaces) intersect with the 400-meter buffers of wildland areas, including forests, shrublands, and grasslands. These maps are produced based on land cover classification results from the GlobeLand30 datasets.
Projection Information:
The projection information aligns with GlobeLand30 standards:
Naming Convention:
The file naming convention is as follows:
Where:
Example File Name:
For instance, the file named WUI_n15_45_2020lc030.tif can be interpreted as follows:
This page allows for the download of data regarding the WUI, including non-WUI vegetated areas and non-vegetated or agriculture. The wildland-urban interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), the USFS integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States from 1990-2010. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a geodatabase and include information such as housing and population densities for 1990, 2000, and 2010; wildland vegetation percentages for 1992, 2001, and 2011; as well as WUI classes in 1990, 2000, and 2010.
A map highlighting the drainage basins defined by Napa County in their modeling efforts. The Napa County Watersheds were generated from two elevation datasets. The Napa River Watershed was generated from LIDAR data processed by NCALM at UC Berkeley (https://calm.geo.berkeley.edu/ncalm/index.html). The eastern side of the county was delineated from DTM data which was generated from aerial photography (2002). The watersheds are intended to be used for hydrologic modeling and planning.Ridgelines are also from Napa County and depict major and minor ridgelines.Other topographic features important to wildfire planning may in added in the future.
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The Wildland-Urban Interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), we integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States from 1990-2020. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a geodatabase and include information such as housing densities for 1990, 2000, 2010, and 2020; wildland vegetation percentages for 1992, 2001, 2011, and 2019; as well as WUI classes in 1990, 2000, 2010, and 2020.To provide a spatially detailed national assessment of the wildland-urban interface (WUI) and WUI change between 1990 and 2020 across the coterminous U.S. to support wildland fire research, policy and management, and inquiries into the effects of housing growth on the environment.This data publication, published on 08/09/2023 is a fourth edition. The first edition (https://doi.org/10.2737/RDS-2015-0012) contained data representing the 2010 WUI of the conterminous United States. The second edition (https://doi.org/10.2737/RDS-2015-0012-2) contained data that represented the 1990-2010 WUI. The third edition (https://doi.org/10.2737/RDS-2015-0012-3) contains data that represent the 1990-2020 WUI.
This fourth edition uses an improved PLA housing density dataset to classify WUI from 1990-2020. This involved updating the public land adjustment (PLA) process (step 1) by correcting topological errors and removing erroneous sliver polygons generated during the PLA process.
On 09/16/2024, minor metadata updates were made, which included updating URLs for associated articles.
Information about WUI can also be found here: http://silvis.forest.wisc.edu/data/wui-change as well as https://www.fs.usda.gov/research/nrs/projects/wuigrowth.
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Human encroachment into wildlands has resulted in a rapid increase in wildland–urban interface (WUI) expansion, exposing more buildings and population to wildfire risks. More frequent mapping of structures and WUIs at a finer spatial resolution is needed for WUI characterization and hazard assessment. However, most approaches rely on high-resolution commercial satellite data with a particular focus on urban areas. We developed a deep learning framework tailored for building footprint detection in the transitional wildland–urban areas. We leveraged meter scale aerial imageries publicly available from the National Agriculture Imagery Program (NAIP) every 2 years. Our approach integrated Mobile-UNet and generative adversarial network. The deep learning models trained over three counties in California performed well in detecting building footprints across diverse landscapes, with an F1 score of 0.62, 0.67, and 0.75 in the interface WUI, intermix WUI, and rural regions, respectively. The bi-annual mapping captured both housing expansion and wildfire-caused building damages. The 30 m WUI maps generated from these finer footprints showed more granularity than the existing census tract-based maps and captured the transition of WUI dynamics well. More frequent updates of building footprint and improved WUI mapping will improve our understanding of WUI dynamics and provide guidance for adaptive strategies on community planning and wildfire hazard reduction.
Wildland-urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated due to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex making it challenging for end-users, such as those who use or create WUI maps, to apply. We identified buildings pre- and post-wildfire and estimated building destruction for three California wildfires: Camp, Tubbs, and Woolsey. We used a CNN model from Esri to detect buildings from high-resolution imagery. This dataset represents the state-of-the-art of what is readily available for potential WUI mapping.
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The dataset contains three (1860s, 1970s, 2013) detailed Wildland-Urban Interface (WUI) maps of the Polish Carpathians, including information on building density. The maps, available in the form of 10m raster GeoTIFF files, are based on the WUI definition of US Federal Register (USDA and USDI, 2001) as operationalized by (Radeloff et al., 2005), which distinguishes two kinds of WUI: intermix, where housing intermingle with wildland vegetation, and interface, where settlement abuts the wildland areas. Either WUI type requires a housing density higher than 6.17 houses/km2 (1 house/40 acres in the US context). In intermix WUI, there has to be also > 50% wildland vegetation, while the interface WUI, has < 50% wildland vegetation but is within 2.4 km of a wildland vegetation patch larger > 5 km2. Given the ecological context of the Polish Carpathians, we defined wildland vegetation as forests, because forests are the climax vegetation type below the treeline. To assess settlements, we analysed all buildings locations (residential and non-residential), because all buildings reflect human activities. The building density and forest cover share were calculated by using a 500m circular moving window algorithm.
Acknowledgements
The study was supported by the National Science Centre, Poland, contract no. UMO-2019/35/D/HS4/00117 and by the NASA Land Use and Land Cover Change Program.
The DNRC Interactive Wildland Fire Map provides up-to-date resources and information related to present and past wildfire incidents in the State of Montana. Leveraging the Esri Web AppBuilder platform, a variety of tools/widgets allow the user to interact with application to better understand forest fires and their impact to the landscape and residents of Montana.
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The Wildland-Urban Interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), we integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001). These data are useful within a GIS for mapping and analysis at national, state, and local levels.
Parcels affected by the adoption of the 2015 International Wildland Urban-Interface Code (WUIC), which was adopted by Austin City Council April9, 2020, and implementation beginning January 1st, 2021. Parcels that are within 1.5 miles of a wildland area greater than 750 acres and parcels within 150 feet of a wildland area greater than 40 acres are wildland_urban_interface_code parcels. Parcels designated as "preserves" have been removed and are not subject to the WUI code.Dataset was created in 2020 by Austin Fire Department Wildfire Division. It was derived from the most recent Travis County Appraisal District (TCAD) Parcels, and queried based upon their planar distance to wildland areas. Wildlands are defined as undeveloped continuous areas,. The wildlands feature class is maintained by the Austin Fire Department and is derived from the City of Austin Planimetric dataset, also known as impervious cover data, and are updated every two years. ArcGIS Pro version 2 software was used to create this dataset. The data is meant to be ingested by a GIS system. Changes to the City of Austin & LTD jurisdiction warrant an update to this dataset. The data is scheduled to be updated every two years.Included in the attributes are parcel condition variables that determine the parcel's "fire hazard severity' class. These include the composite score of three variables: slope score, fuel score, and WUI class (proximity). Slope score was determined by the average degree slope of the area within each parcel and classified as less than 10%, 10% to 25%, or greater then 25%. Fuel score was determined by the average fuel class area within each parcels as defined by the Austin Travis County Community Wildfire Protection Plan (CWPP) and classified as light, medium, or heavy fuels. Proximity class was defined by the proximity of each parcel to wildlands, either as within 1.5 miles of wildlands greater than 750 acres, or within 150 feet of wildlands greater than 40 acres.Description of data fieldsGLOBALID_1 = Used for Global IdentificationOBJECTID = Object IdentificationSLOPE_DEGREE = The average slope of each parcel in degreesFIRE_HAZARD_SEVERITY = The "fire hazard severity" class of each parcelPROXIMITY_CLASS = The proximity class of each parcelSLOPE_CLASS = The slope classification of each parcelFUEL_CLASS = The fuel class of each parcelCREATED_BY = Creators nameCREATED_DATE = Date createdMODIFIED_BY = Modifiers nameMODIFIED_DATE = Date modifiedUNIQUE_ID = Unique Identification number (mirror object id)Shape_Area = Shape areaShape_Length = Shape lengthIteration ID: Parcels_AustinLTD4 2020Contact: Steven Casebeer at Steven.casebeer@austintexas.gov | Austin Fire Department Wildfire Division
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The Fireshed Registry is a geospatial dashboard and decision tool built to organize information about wildfire transmission to communities and monitor progress towards risk reduction for communities from management investments. The concept behind the Fireshed Registry is to identify and map the source of risk rather than what is at risk across all lands in the conterminous United States. While the Fireshed Registry was organized around mapping the source of fire risk to communities, the framework does not preclude the assessment of other resource management priorities and trends such as water, fish and aquatic or wildlife habitat, or recreation. The Fireshed Registry is also a multi-scale decision tool for quantifying, prioritizing, and geospatially displaying wildfire transmission to buildings in adjacent or nearby communities. Fireshed areas in the Fireshed Registry are approximately 250,000 acre accounting units that are delineated based on a smoothed building exposure map of the conterminous United States. These boundaries were created by dividing up the landscape into regular-sized units that represent similar source levels of community exposure to wildfire risk. Project areas are approximately 25,000 acre accounting units nested within firesheds. This data publication includes a geodatabase that contains for both fireshed and project areas: boundaries, size, total annual number of buildings inside and outside of the area exposed by wildfires ignited within the area (based on 2010 housing unit data and 2014 fuels conditions), and percent of the area that has been disturbed since 2014 (2015-2018).Metadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.
The Wildland-Urban Interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), we integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States from 1990-2020. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a geodatabase and include information such as housing densities for 1990, 2000, 2010, and 2020; wildland vegetation percentages for 1992, 2001, 2011, and 2019; as well as WUI classes in 1990, 2000, 2010, and 2020.This WUI feature class is separate from the WUI datasets maintained by individual forest unites, and it is not the authoritative source data of WUI for forest units. This dataset shows change over time in the WUI data up to 2020.Metadata and Downloads