The National All-Lands Wildfire Risk Assessment (NaWRA) is a quantitative analysis of how resources and assets may be impacted by wildfire based on: 1) the intensity of a wildfire if one should occur, 2) the exposure of resources and assets based on their locations, and 3) the susceptibility of those resources and assets to wildfire. Data users are encouraged to access the companion report (NaWRA 2025 Methods) for the full details of the assessment.Wildfire hazard was modeled using 2026 capable fuels data. Potential wildfire intensity was estimated at 30-m resolution in the form of conditional probabilities of burning in six different flame length bins (0-2, 2-4, 4-6, 6-8, 8-12, and 12+ ft) using the Pyrologix WildEST Model (Scott et al. 2024). WildEST is a deterministic wildfire modeling tool that integrates spatially continuous weather inputs weighted based on how likely they are to be realized on the landscape. Potential wildfire burn probability was estimated for the 11 Western States by running the USDA Forest Service FSim Model (Finney et al. 2011) at 120-m resolution with post-processing to upsample results to 30-m resolution and estimate burn probability in non-burnable areas adjacent to wildland fuels. Wildfire burn probability for the remainder of CONUS came from the Wildfire Risk to Communities Project (Scott et al. 2024) or the Southern Wildfire Risk Assessment (SouthWRA 2024) modeled with FSim using similar methods.The People and Property, Critical Infrastructure, and Historic Structures and Buildings layer represents the potential combined impact to human assets.The People and Property Highly Valued Resource and Asset (HVRA) Theme represents the spatial distribution and density of housing units. Wildfire has the potential to damage or destroy homes, apartments, other housing units, outbuildings, and their contents. In extreme cases, housing unit exposure to wildfire also results in human injuries or deaths. The People and Property HVRA was mapped using the housing unit density raster from the USDA Forest Service Wildfire Risk to Communities Project, which estimates housing unit density with 2020 census housing unit data and a comprehensive building footprint dataset (Jaffe et al. 2024). Fuel type was used as a covariate for the response functions to reflect the expectation for higher losses with increasing fire intensities, fire residence times, and resistance to control across the grass-shrub-tree fuel type gradient.The Critical Infrastructure Highly Valued Resource and Asset (HVRA) Theme represents important healthcare, emergency service, communication, and energy infrastructure. Wildfire has potential to temporarily disrupt the use of or permanently damage infrastructure. Critical Infrastructure was mapped using Homeland Infrastructure Foundation Level Data (HIFLD; ) accessed in early 2024 to represent Hospitals, Emergency Services, Communication Devices, Electric transmission lines, Power Plants, Substations, Natural Gas Pipelines, and Oil & Natural Gas Wells. The HIFLD program provides consistent spatial data for homeland security analysis and planning.The Historic Structures and Buildings Highly Valued Resource and Asset (HVRA) Theme represents features that society has deemed culturally significant and worthy of preservation. Historic Structures and Buildings were mapped using the National Register of Historic Places (NRHP; ) accessed in early 2024. The Historic Structures and Historic Building point layers were extracted from the NRHP database and merged into a single layer. Each point feature was buffered by 60-m to represent the approximate zone in which wildfire could impact the feature. Fuel type was used as a covariate for the response functions to reflect the expectation for higher losses with increasing fire intensities, fire residence times, and resistance to control across the grass-shrub-tree fuel type gradient.
Name: Fire_Aviation/USFS_QWRA_PeopleInfraHistcNVC_CONUS
Description: The National All-Lands Wildfire Risk Assessment (NaWRA) is a quantitative analysis of how resources and assets may be impacted by wildfire based on: 1) the intensity of a wildfire if one should occur, 2) the exposure of resources and assets based on their locations, and 3) the susceptibility of those resources and assets to wildfire. Data users are encouraged to access the companion report (NaWRA 2025 Methods) for the full details of the assessment.Wildfire hazard was modeled using 2026 capable fuels data. Potential wildfire intensity was estimated at 30-m resolution in the form of conditional probabilities of burning in six different flame length bins (0-2, 2-4, 4-6, 6-8, 8-12, and 12+ ft) using the Pyrologix WildEST Model (Scott et al. 2024). WildEST is a deterministic wildfire modeling tool that integrates spatially continuous weather inputs weighted based on how likely they are to be realized on the landscape. Potential wildfire burn probability was estimated for the 11 Western States by running the USDA Forest Service FSim Model (Finney et al. 2011) at 120-m resolution with post-processing to upsample results to 30-m resolution and estimate burn probability in non-burnable areas adjacent to wildland fuels. Wildfire burn probability for the remainder of CONUS came from the Wildfire Risk to Communities Project (Scott et al. 2024) or the Southern Wildfire Risk Assessment (SouthWRA 2024) modeled with FSim using similar methods.The People and Property, Critical Infrastructure, and Historic Structures and Buildings layer represents the potential combined impact to human assets.The People and Property Highly Valued Resource and Asset (HVRA) Theme represents the spatial distribution and density of housing units. Wildfire has the potential to damage or destroy homes, apartments, other housing units, outbuildings, and their contents. In extreme cases, housing unit exposure to wildfire also results in human injuries or deaths. The People and Property HVRA was mapped using the housing unit density raster from the USDA Forest Service Wildfire Risk to Communities Project, which estimates housing unit density with 2020 census housing unit data and a comprehensive building footprint dataset (Jaffe et al. 2024). Fuel type was used as a covariate for the response functions to reflect the expectation for higher losses with increasing fire intensities, fire residence times, and resistance to control across the grass-shrub-tree fuel type gradient.The Critical Infrastructure Highly Valued Resource and Asset (HVRA) Theme represents important healthcare, emergency service, communication, and energy infrastructure. Wildfire has potential to temporarily disrupt the use of or permanently damage infrastructure. Critical Infrastructure was mapped using Homeland Infrastructure Foundation Level Data (HIFLD; ) accessed in early 2024 to represent Hospitals, Emergency Services, Communication Devices, Electric transmission lines, Power Plants, Substations, Natural Gas Pipelines, and Oil & Natural Gas Wells. The HIFLD program provides consistent spatial data for homeland security analysis and planning.The Historic Structures and Buildings Highly Valued Resource and Asset (HVRA) Theme represents features that society has deemed culturally significant and worthy of preservation. Historic Structures and Buildings were mapped using the National Register of Historic Places (NRHP; ) accessed in early 2024. The Historic Structures and Historic Building point layers were extracted from the NRHP database and merged into a single layer. Each point feature was buffered by 60-m to represent the approximate zone in which wildfire could impact the feature. Fuel type was used as a covariate for the response functions to reflect the expectation for higher losses with increasing fire intensities, fire residence times, and resistance to control across the grass-shrub-tree fuel type gradient.
Single Fused Map Cache: false
Extent:
XMin: -1.42919667048E7
YMin: 2563037.3960999995
XMax: -7130456.7048
YMax: 6886967.3961
Spatial Reference: 102100
(3857)
LatestVCSWkid(0)
Initial Extent:
XMin: -1.42919667048E7
YMin: 2563037.3960999995
XMax: -7130456.7048
YMax: 6886967.3961
Spatial Reference: 102100
(3857)
LatestVCSWkid(0)
Full Extent:
XMin: -1.42919667048E7
YMin: 2563037.3960999995
XMax: -7130456.7048
YMax: 6886967.3961
Spatial Reference: 102100
(3857)
LatestVCSWkid(0)
Pixel Size X: 30.0
Pixel Size Y: 30.0
Band Count: 1
Pixel Type: U8
RasterFunction Infos: {"rasterFunctionInfos": [
{
"help": "",
"name": "PEOPLE_INFRA_HIST_cNVC",
"description": "PEOPLE_INFRA_HIST_cNVC 2024"
},
{
"help": "",
"name": "None",
"description": "Make a Raster or Raster Dataset into a Function Raster Dataset."
}
]}
Mensuration Capabilities: Basic
Inspection Capabilities:
Has Histograms: true
Has Colormap: false
Has Multi Dimensions : false
Rendering Rule:
Min Scale: 0
Max Scale: 0
Copyright Text: USDA - GEO; USDA - USFS – GTAC
Service Data Type: esriImageServiceDataTypeGeneric
Min Values: 0
Max Values: 6
Mean Values: 3.9123149633605561
Standard Deviation Values: 1.3354673466471545
Object ID Field: objectid
Fields:
-
objectid
(
alias: objectid
, type: esriFieldTypeOID
)
-
name
(
length: 200
, alias: name
, type: esriFieldTypeString
)
-
minps
(
alias: minps
, type: esriFieldTypeDouble
)
-
maxps
(
alias: maxps
, type: esriFieldTypeDouble
)
-
lowps
(
alias: lowps
, type: esriFieldTypeDouble
)
-
highps
(
alias: highps
, type: esriFieldTypeDouble
)
-
category
(
alias: category
, type: esriFieldTypeInteger
, Coded Values:
[0: Unknown]
, [1: Primary]
, [2: Overview]
, ...6 more...
)
-
tag
(
length: 100
, alias: tag
, type: esriFieldTypeString
)
-
groupname
(
length: 100
, alias: groupname
, type: esriFieldTypeString
)
-
productname
(
length: 100
, alias: productname
, type: esriFieldTypeString
)
-
centerx
(
alias: centerx
, type: esriFieldTypeDouble
)
-
centery
(
alias: centery
, type: esriFieldTypeDouble
)
-
zorder
(
alias: zorder
, type: esriFieldTypeInteger
)
-
shape
(
alias: shape
, type: esriFieldTypeGeometry
)
Default Mosaic Method: Northwest
Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None
SortField:
SortValue: N/A
Mosaic Operator: First
Default Compression Quality: 75
Default Resampling Method: Nearest
Max Record Count: 1000
Max Image Height: 100000
Max Image Width: 100000
Max Download Image Count: 20
Max Mosaic Image Count: 20
Allow Raster Function: true
Allow Copy: true
Allow Analysis: true
Allow Compute TiePoints: false
Supports Statistics: true
Supports Advanced Queries: true
Use StandardizedQueries: true
Raster Type Infos:
Name: Raster Dataset
Description: Supports all ArcGIS Raster Datasets
Help:
Has Raster Attribute Table: false
Edit Fields Info: N/A
Ownership Based AccessControl For Rasters: N/A
Child Resources:
Info
Histograms
Statistics
Key Properties
Legend
Raster Function Infos
Supported Operations:
Export Image
Query
Identify
Measure
Compute Histograms
Compute Statistics Histograms
Get Samples
Compute Class Statistics
Query GPS Info
Find Images
Image to Map
Map to Image
Measure from Image
Image to Map Multiray
Query Boundary
Compute Pixel Location
Compute Angles
Validate
Project