Spatial dataset of probabilistic wildfire risk components for the conterminous United States

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Short, Karen C.
Originator: Finney, Mark A.
Originator: Scott, Joe H.
Originator: Gilbertson-Day, Julie W.
Originator: Grenfell, Isaac C.
Publication_Date: 2016
Title:
Spatial dataset of probabilistic wildfire risk components for the conterminous United States
Edition: 1st
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2016-0034
Description:
Abstract:
National burn probability (BP) and conditional fire intensity level (FIL) data were generated for the conterminous United States (US) using a geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. [2011]). The FSim system includes modules for weather generation, wildfire occurrence, fire growth, and fire suppression. FSim is designed to simulate the occurrence and growth of wildfires under tens of thousands of hypothetical contemporary fire seasons in order to estimate the probability of a given area (i.e., pixel) burning under current landscape conditions and fire management practices. The data presented here represent modeled BP and FIL for the conterminous US at a 270-meter grid spatial resolution. The six FILs correspond to flame-length classes as follows: FIL1 = < 2 feet (ft); FIL2 = 2 < 4 ft.; FIL3 = 4 < 6 ft.; FIL4 = 6 < 8 ft.; FIL5 = 8 < 12 ft.; FIL6 = 12+ ft. Because they indicate conditional probabilities (i.e., representing the likelihood of burning at a certain intensity level, given that a fire occurs), the FIL*_20160830 data must be used in conjunction with the BP_20160830 data for risk assessment.
Purpose:
National-scale assessment of wildfire risk offers a consistent means of understanding and comparing threats to valued resources and predicting and prioritizing investments in management activities that mitigate those risks. We used a simulation system to estimate the probabilistic components of wildfire risk for 128 distinct regions of contemporary wildfire activity (pyromes) across the conterminous US (CONUS). The system, called FSim, consists of modules for weather generation, and for modeling of large-fire occurrence, growth, and suppression. FSim is designed to simulate the occurrence and growth of fires under tens of thousands of hypothetical contemporary fire seasons in order to estimate burn probabilities and conditional flame lengths at multiple spatial scales, given current landscape conditions and fire management policies. These outputs have been generated for the CONUS to support a number of national planning and risk assessment efforts.
Supplemental_Information:
Original metadata date was 11/30/2016. Minor metadata updates were made on 06/30/17 and 08/15/2017. This edition of these data are available as a map service: https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_Wildfire/ProbabilisticWildfireRisk/MapServer.

** NOTE: On 03/23/2020 a second edition of these data became available (Short et al. 2020; https://doi.org/10.2737/RDS-2016-0034-2) and we recommend the use of this newer edition. It is based on circa 2014 landscape data, which were the most current LANDFIRE products available at the time of production. It is also expanded to include Alaska and Hawaii at 270-meter resolution.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2012
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Description_of_Geographic_Extent:
Conterminous United States (CONUS)
Bounding_Coordinates:
West_Bounding_Coordinate: -127.972202
East_Bounding_Coordinate: -65.258792
North_Bounding_Coordinate: 51.632799
South_Bounding_Coordinate: 22.765684
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: geoscientificInformation
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Fire
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: burn probability
Theme_Keyword: flame length
Theme_Keyword: fire intensity
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: conterminous United States
Place_Keyword: CONUS
Access_Constraints: None
Use_Constraints:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Short, Karen C.; Finney, Mark A.; Scott, Joe H.; Gilbertson-Day, Julie W.; Grenfell, Isaac C. 2016. Spatial dataset of probabilistic wildfire risk components for the conterminous United States. 1st Edition. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2016-0034

Users are strongly encouraged to read and fully comprehend the metadata prior to data use. Users should acknowledge the Originator when using this dataset as a source. Users should share data products developed using the source dataset with the Originator. No warranty is made by the Originator as to the accuracy, reliability, or completeness of these data for individual use or aggregate use with other data, or for purposes not intended by the Originator. This dataset is intended to estimate probabilistic wildfire risk components that can support national strategic planning. The applicability of the data to support fire and land management planning on smaller areas will vary by location and specific intended use. Further investigation by local and regional experts should be conducted to inform decisions regarding local applicability. It is the sole responsibility of the local user, using this metadata document and local knowledge, to determine if and/or how these data can be used for particular areas of interest. National FSim products are not intended to replace local products where they exist, but rather serve as a back-up by providing wall-to-wall cross-boundary data coverage. It is the responsibility of the user to be familiar with the value, assumptions, and limitations of these national data publications. Managers and planners must evaluate these data according to the scale and requirements specific to their needs. Spatial information may not meet National Map Accuracy Standards. This information may be updated without notification.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory
Contact_Person: Karen Short
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: Missoula Fire Sciences Laboratory
Address: 5775 US Hwy 10 W
City: Missoula
State_or_Province: MT
Postal_Code: 59808
Country: USA
Contact_Voice_Telephone: 406-329-4800
Contact_Electronic_Mail_Address: karen.c.short@usda.gov
Browse_Graphic:
Browse_Graphic_File_Name: \Supplements\FSIM_20160720.png
Browse_Graphic_File_Description:
Portable Network Graphics file displaying the national burn probabilities generated for the conterminous United States.
Browse_Graphic_File_Type: PNG
Data_Set_Credit:
Funding for this project provided by USDA Forest Service, Rocky Mountain Research Station and the USDA Forest Service, Fire and Aviation Management.
Cross_Reference:
Citation_Information:
Originator: Short, Karen C.
Originator: Finney, Mark A.
Originator: Vogler, Kevin C.
Originator: Scott, Joe H.
Originator: Gilbertson-Day, Julie W.
Originator: Grenfell, Isaac C.
Publication_Date: 2020
Title:
Spatial datasets of probabilistic wildfire risk components for the United States (270m)
Edition: 2nd
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2016-0034-2
Analytical_Tool:
Analytical_Tool_Description:
FSim is often referred to as a "large fire simulator" because it attempts to model the ignition and growth of only those wildfires with a propensity to spread. Relatively large and generally fast moving fires are the focus of this system designed to estimate BP and FIL because they account for the majority (~80-97%) of total area burned per simulation unit, etc., and thus contribute the greatest to the probability of a wildland fire burning a given parcel of land therein (i.e., wildfire hazard). Fire occurrence in FSim is stochastically modeled based on historical relationships between large fires (largest ~3-5% for each simulation unit) and ERC. Because its objective is to simulate the behavior of large, spreading fires, FSim restricts fire growth to days on which ERC reaches or exceeds the 80th percentile condition. On those days, the length of the simulated burning period is set at 1 hour, 3 hours, and 5 hours for the 80th, 90th, and 97th percentile ERC conditions, respectively. Fire growth and behavior is calculated using standard FlamMap routines and a minimum travel time (MTT) algorithm. Suppression influences on growth are accounted for by a statistical model that indicates probability of containment (cessation) based on spread rates and fuel types throughout each fire simulation. A ‘perimeter trimming’ function, which better reflects the influence of suppression activities on fire spread and improves modeled fire size distributions, is also included in the fire suppression module.

The fire growth simulations, when run repeatedly with different ignition locations and weather streams, generate burn probabilities and fire behavior distributions at each landscape location (i.e., cell or pixel). Results are objectively evaluated through comparison with historical fire patterns and statistics, including the mean annual burn probability and fire size distribution, for each simulation unit. This evaluation is part of the FSim calibration process, whereby simulation inputs are adjusted until the slopes of the historical and modeled fire size distributions are similar and the modeled average burn probability falls within an acceptable range of the historical reference value (i.e., the 95% confidence interval for the mean).

For a technical overview of the Fire Simulation (FSim) system developed by the USDA Forest Service, Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk, see Finney et al. (2011).
Tool_Access_Information:
Tool_Access_Instructions:
Please send requests to: Fire Modeling Institute, USFS Missoula Fire Sciences Laboratory, 5775 US Highway 10 West, Missoula, Montana, 59808; fmi@fs.fed.us
Tool_Citation:
Citation_Information:
Originator: Finney, Mark A.
Originator: McHugh, Charles W.
Originator: Greenfell, Isaac C.
Originator: Riley, Karin L.
Originator: Short, Karen C.
Publication_Date: 2011
Title:
A simulation of probabilistic wildfire risk components for the continental United States
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Stochastic Environmental Research and Risk Assessment
Issue_Identification: 25(7):973-1000
Online_Linkage: https://doi.org/10.1007/s00477-011-0462-z
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Model results are objectively evaluated through comparison with historical fire patterns and statistics, including the mean annual burn probability and fire size distribution, for each simulation unit. This evaluation is part of the FSim calibration process, whereby simulation inputs are adjusted until the slopes of the historical and modeled fire size distributions are similar and the modeled average burn probability falls within an acceptable range of the historical reference value (i.e., the 95% confidence interval for the mean).

For more information on the calibration process see Thompson et al. (2016).

Thompson, Matthew P.; Bowden, Phil; Brough, April; Scott, Joe H.; Gilbertson-Day, Julie; Taylor, Alan; Anderson, Jennifer; Haas, Jessica R. 2016. Application of wildfire risk assessment results to wildfire response planning in the Southern Sierra Nevada, California, USA. Forests 7(3):1-22. https://doi.org/10.3390/f7030064
Logical_Consistency_Report:
Pixels with nonzero values for BP also have nonzero sum-total values in the FIL*_20160830 layers. Pixels with values of zero ("0") for BP have corresponding sum-total zero ("0") values in the FIL*_20160830 layers.
Completeness_Report:
Cells with a zero ("0") value for burn probability were either (1) characterized as a non-burnable fuel type in the 270-meter LANDFIRE dataset, or (2) burnable, but not burned within the simulation limits (10,000-100,000 annual weather scenarios modeled, depending on the simulation unit). While, for the latter case, it should be possible to obtain nonzero values (i.e., extremely imprecise estimates of some value less than 0.00001) with additional years in simulation, such efforts were beyond the scope and interest of this work.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Department of Agriculture, Forest Service
Originator: U.S. Department of the Interior
Publication_Date: 2012
Title:
LANDFIRE 2012
Geospatial_Data_Presentation_Form: database
Online_Linkage: https://www.landfire.gov/
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2012
Source_Currentness_Reference:
ground condition
Source_Citation_Abbreviation:
LANDFIRE
Source_Contribution:
LANDFIRE Refresh 2012 (LF 2012 - LF_1.3.0) fuel and terrain data
Source_Information:
Source_Citation:
Citation_Information:
Originator: Short, Karen C.
Publication_Date: 2015
Title:
Spatial wildfire occurrence data for the United States, 1992-2013 [FPA_FOD_20150323]
Edition: 3rd Edition
Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2013-0009.3
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1992
Ending_Date: 2013
Source_Currentness_Reference:
ground condition
Source_Citation_Abbreviation:
[FPA_FOD_20150323]
Source_Contribution:
This historical wildfire dataset was used in development of the FSim products.

The development of the historical fire-occurrence data is described in a companion paper:

Short, Karen C. 2014. A spatial database of wildfires in the United States, 1992-2011. Earth System Science Data 6:1-27. https://doi.org/10.5194/essd-6-1-2014
Process_Step:
Process_Description:
Spatial burn probabilities and conditional intensities were modeled using LANDFIRE Refresh 2012 fuel and terrain data (lf_1.3.0; https://www.landfire.gov/), historical fire occurrence and weather data, and fire danger rating information. LANDFIRE data were resampled to 270-meter resolution due to computational limitations. To obtain stable estimates of BP and FIL across each landscape, fire ignition and growth was simulated for 10,000 to 100,000 potential annual weather scenarios. Potential contemporary weather scenarios were generated for each simulation unit using: (1) a fire danger rating index known as the Energy Release Component (ERC), which is a proxy for fuel moisture, (2) a time-series analysis of ERC to represent daily and seasonal trends and variability, and (3) distributions of wind speed and direction from surface weather records. The resulting modeled annual weather scenarios are independent realizations of the historical fire climatology (ignitions, weather patterns), and because large fires are so rare, FSim needs a very large sample of potential scenarios to estimate static wildfire hazard across each landscape. In other words, FSim is NOT projecting 10,000-100,000 years into the future, but is simply generating a necessarily large sample of (hypothetical) contemporary fire seasons from statistical characterizations of the past.

The generation of modeled fire seasons and ignition probabilities was based on analyses of a national gridded weather dataset, which is described in the following paper:

Abatzoglou, John T. 2011. Development of gridded surface meteorological data for ecological applications and modeling. International Journal of Climatology 33:121-131. https://doi.org/10.1002/joc.3413
Process_Date: 2012
Process_Step:
Process_Description:
For this work, the conterminous US comprised 128 simulation units based on customized ecoregional boundaries, and each was modeled separately to generate this CONUS dataset. The landscape used in each simulation extended 15-kilometers beyond the simulation unit boundary, which allowed fires ignited in that buffer to affect the overall outcomes, helping to dampen the edge effects associated with regional-level simulations. The buffers were removed and 128 datasets mosaicked to create the CONUS grid presented here.
Process_Date: 2016
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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 10803
Column_Count: 17133
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Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.5
Standard_Parallel: 45.5
Longitude_of_Central_Meridian: -96.0
Latitude_of_Projection_Origin: 23.0
False_Easting: 0.0
False_Northing: 0.0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: coordinate pair
Coordinate_Representation:
Abscissa_Resolution: 0.00000000375279807229845
Ordinate_Resolution: 0.00000000375279807229845
Geodetic_Model:
Horizontal_Datum_Name: D North American 1983
Ellipsoid_Name: GRS 1980
Semi-major_Axis: 6378137
Denominator_of_Flattening_Ratio: 298.257222101
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Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
This data publication includes a geodatabase (\Data\NationalFSim_2016.gdb) containing modeled national burn probability (BP) and conditional fire intensity level (FIL) data for the conterminous United States (US) at a 270-meter grid spatial resolution.

BURN PROBABILITY (BP):

Values in the BP data layer indicate, for each pixel, the number of times that cell was burned by an FSim-modeled fire, divided by the total number of annual weather scenarios simulated. The burn probability layer depicts only one component of wildfire risk, indicating the tendency of any given pixel to burn, given the static landscape conditions depicted by the LANDFIRE Refresh 2012 dataset, contemporary weather and ignition patterns, as well as contemporary fire management policies (entailing considerable fire prevention and suppression efforts). The BP data do not, and are not intended to, depict fire-return intervals of any vintage, nor do they indicate likely fire footprints or routes of travel. Nothing about the expected shape or size of any actual fire incident can be interpreted from the burn probabilities. Instead, the BP data, in conjunction with the FIL layers, are intended to support an actuarial approach to quantitative wildfire risk analysis (e.g., see Thompson et al. [2011]).

CONDITIONAL FIRE INTENSITY LEVEL (FIL):

Values in the FIL layers indicate, of all simulated fires that burned a given cell, the proportion in each fire-intensity, or flame-length, category. The six FILs correspond to flame-length classes as follows:
FIL1 = < 2 feet (ft.)
FIL2 = 2 < 4 ft.
FIL3 = 4 < 6 ft.
FIL4 = 6 < 8 ft.
FIL5 = 8 < 12 ft.
FIL6 = 12+ ft.

The utility of the calibrated FSim BP and FIL data for quantitative geospatial wildfire risk assessment is described in Thompson et al. (2011) and Scott et al. (2013).
Entity_and_Attribute_Detail_Citation:
Thompson, Matthew P.; Calkin, David E.; Finney, Mark A.; Ager, Alan A.; Gilbertson-Day, Julie W. 2011. Integrated national-scale assessment of wildfire risk to human and ecological values. Stochastic Environmental Research and Risk Assessment 25:761-780. https://doi.org/10.1007/s00477-011-0461-0

Scott, Joe H.; Thompson, Matthew P.; Calkin, David E. 2013. A wildfire risk assessment framework for land and resource management. Gen. Tech. Rep. RMRS-GTR-315. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 83 p. https://doi.org/10.2737/rmrs-gtr-315
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Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Research and Development
Contact_Position: Research Data Archivist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect Road
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: see Contact Instructions
Contact Instructions: This contact information was current as of March 2020. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2016-0034
Distribution_Liability:
Metadata documents have been reviewed for accuracy and completeness. Unless otherwise stated, all data and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. However, neither the author, the Archive, nor any part of the federal government can assure the reliability or suitability of these data for a particular purpose. The act of distribution shall not constitute any such warranty, and no responsibility is assumed for a user's application of these data or related materials.

The metadata, data, or related materials may be updated without notification. If a user believes errors are present in the metadata, data or related materials, please use the information in (1) Identification Information: Point of Contact, (2) Metadata Reference: Metadata Contact, or (3) Distribution Information: Distributor to notify the author or the Archive of the issues.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: GDB
Format_Version_Number: see Format Specification
Format_Specification:
ESRI file geodatabase
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2016-0034
Digital_Form:
Digital_Transfer_Information:
Format_Name: ArcMap webservice
Format_Version_Number: see Format Specification
Format_Specification:
Enterprise Data Warehouse (EDW) map service
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_Wildfire/ProbabilisticWildfireRisk/MapServer
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20200323
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory
Contact_Person: Karen Short
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: Missoula Fire Sciences Laboratory
Address: 5775 US Hwy 10 W
City: Missoula
State_or_Province: MT
Postal_Code: 59808
Country: USA
Contact_Voice_Telephone: 406-329-4800
Contact_Electronic_Mail_Address: karen.c.short@usda.gov
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
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