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BLM GRSG BER: Burn Probability - High (polygon)


Identification Information:
Citation:
Citation Information:
Publication Date: 20120301
Title: BLM GRSG BER: Burn Probability - High (polygon)
Geospatial Data Presentation Form: remote-sensing image
Originator: Bureau of Land Management (BLM), United States Forest Service (USFS) Missoula Fire Sciences Laboratory
Online Linkage: https://gis.blm.gov/BER_LayerPackages/BurnProb_2cat_High_Dissolve_for_CEA.lpk
Description:
Abstract: National burn probability (BP) and fire intensity level (FIL) raster datasets for the United States were generated for the 2012 Fire Program Analysis (FPA) System submissions 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 data presented here are the burn probabilities for the conterminous US at a 270-meter grid spatial resolution. Data for Alaska, Hawaii, and Puerto Rico are available separately, as are the six FIL datasets. The six FILs correspond to flame-length classes as follows: FIL1 = http://www.landfire.gov/) fuel and terrain data, historical fire occurrence data, surface weather records, and fire danger rating information. (LANDFIRE data were resampled to 270-meter resolution, except in the case of Alaska, which was resampled to 1-kilometer resolution.) To obtain stable estimates of BP and FIL across each landscape, fire ignition and growth was simulated for 20,000 to 50,000 potential annual weather scenarios. Potential contemporary weather scenarios were generated for each FPU 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 the large sample of "years" to estimate static wildfire risk. FSim is NOT projecting 20,000-50,000 years into the future, but drawing a large sample of years from the statistical descriptions of the past. 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 FPU, etc., and thus contribute the greatest to the probability (i.e., risk) of a wildland fire burning a given parcel of land therein. Fire occurrence in FSim is stochastically modeled based on historical relationships between large fires (top ~3-5% for each FPU) 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. 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 FPU. This evaluation is part of the FSim calibration process for each FPU, 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). Values in the Burn Probability (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 2008 dataset (as resampled by FPA), 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). 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 =
Purpose: A burn probability feature class created for use with the Greater Sage-grouse baseline rangewide cumulative effects analysis. The source raster was reclassified using Nominal Classifications to create two categories of data, plus a zero category: Non-burnable = 0, Low probability = 0.00002 - 0.0043, and High Probability = 0.0043 - 0.0732. Reclassification of this two category dataset was based on a separate three category dataset. The three category dataset had the zero values removed from the data and the binning was distributed based on equal numbers of cells to create the three categories. The two categories dataset was then created by using the High category from the three category classification as the high value, and everything else except zero was classified as the low value. The resampled raster data were then exported to a vector polygon file and dissolved based on category. This dataset represents the High probability category of data.These data are the best available which integrates ignition locations, ignition frequency, fire spread patterns, and fuel type into a single coverage. This is a subset of the FSIM Burn Probability, bp_20110915.img, file clipped to BLM states created for the GRSG Baseline analysis. FPA uses fire modeling systems to help Budget Planners gain national-level insights into tradeoffs related to the funding of prevention/preparedness and hazardous fuel activities within Fire Planning Units (FPUs). Modeling occurs in the FPA Initial Response Simulator Module (IRS) and in the Large Fire Module (LFM). The IRS models the effectiveness of fire containment constrained by simulation limits of time, size, and resource availability. The LFM models the outcomes of fires that exceed those simulation limits (ESL) set in the IRS module. Together, these modules provide a statistical means to predict large-fire occurrence, intensity, burned area, and expected suppression cost for the different investment alternatives developed by each FPU according to FPA Interagency Guidance. Results are compared to historical data to assess their validity, or reasonableness. FSim is used in the initial phase of the LFM to generate data necessary to estimate the outcomes of ESL fires from IRS. FPA requires a set of four FSim runs for each FPU to quantify the relative influences of location (i.e., fuel and terrain), weather, and percentage area treated (for hazardous fuel reduction) on fire spread and intensity in the statistical modeling phase of the LFM. Before initiating the four simulations needed for statistical model development, FSim is carefully calibrated to ensure that it generates burn probability and intensity data that are reasonable when compared to nearly two decades of observed fire activity in each FPU. The data presented here are the results from that calibration process.
Status:
Progress: Complete
Maintenance and Update Frequency: As needed
Spatial Domain:
Bounding Coordinates:
West Bounding Coordinate: -127.440161
East Bounding Coordinate: -92.860425
North Bounding Coordinate: 51.040211
South Bounding Coordinate: 23.925126
Keywords:
Theme:
Theme Keyword Thesaurus: ISO 19115 Topic Category
Theme Keyword: biota
Theme Keyword: environment
Place:
Place Keyword: Arizona
Place Keyword: California
Place Keyword: Colorado
Place Keyword: Idaho
Place Keyword: Kansas
Place Keyword: Montana
Place Keyword: Nebraska
Place Keyword: Nevada
Place Keyword: New Mexico
Place Keyword: North Dakota
Place Keyword: Oklahoma
Place Keyword: Oregon
Place Keyword: South Dakota
Place Keyword: Texas
Place Keyword: Utah
Place Keyword: Washington
Place Keyword: Wyoming
Place Keyword Thesaurus: BLM-STATE
Theme:
Theme Keyword: Fire
Theme Keyword: Vegetation
Theme Keyword Thesaurus: BLM-THEME
Theme Keyword: Wildlife
Theme:
Theme Keyword: Bureau of Land Management
Theme Keyword: BLM
Theme Keyword: Baseline Environmental Report
Theme Keyword: BER
Theme Keyword: Greater Sage-Grouse
Theme Keyword: GRSG
Theme Keyword: Burn Probability
Theme Keyword: Fire Simulation
Theme Keyword Thesaurus: BLM-GRSG
Theme Keyword: FSIM
Access Constraints: None, these data are considered public domain.
Use Constraints: These data are provided by Bureau of Land Management (BLM) “as is” and might contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User’s intended use. The information contained in these data is dynamic and may change over time. The data are not better than the sources from which they were derived, and both scale and accuracy may vary across the data set. These data might not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. These data are neither legal documents nor land surveys, and must not be used as such. Official records may be referenced at most BLM offices. Please report any errors in the data to the BLM office from which it was obtained. The BLM should be cited as the data source in any products derived from these data. Any Users wishing to modify the data should describe the types of modifications they have performed. The User should not misrepresent the data, nor imply that changes made were approved or endorsed by BLM. This data may be updated by the BLM without notification.
Point of Contact:
Contact Information:
Contact Organization Primary:
Contact Organization: Bureau of Land Management, National Operations Center
Contact Person: Wildlife Habitat Spatial Analysis Lab
Contact Position: GIS Analyst
Contact Address:
Address Type: physical address
Address: Denver Federal Center, Building 40
City: Lakewood
State or Province: Colorado
Postal Code: 80225
Country: US
Contact Voice Telephone: (303) 236-0446
Time Period of Content:
Time Period Information:
Single Date/Time:
Calendar Date: 20110915
Currentness Reference: ground condition
Data Set Credit: Bureau of Land Management (BLM), United States Forest Service (USFS) Missoula Fire Sciences Laboratory
Data Quality Information:
Attribute Value Accuracy Information:
Attribute Accuracy Report: Basic checks were performed to ensure data integrity and consistency.
Quantitative Attribute Accuracy Assessment:
Attribute Accuracy Explanation: Basic checks were performed to ensure data integrity and consistency.
Logical Consistency Report: Basic checks were performed to ensure data integrity and consistency.
Completeness Report: No selection criteria applied.
Positional Accuracy:
Horizontal Positional Accuracy:
Horizontal Positional Accuracy Report: A formal accuracy assessment of the horizontal positional information in the data set has not been conducted.
Quantitative Horizontal Positional Accuracy Assessment:
Horizontal Positional Accuracy Explanation: Unknown
Vertical Positional Accuracy:
Vertical Positional Accuracy Report: A formal accuracy assessment of the vertical positional information in the data set has not been conducted.
Quantitative Vertical Positional Accuracy Assessment:
Vertical Positional Accuracy Explanation: Unknown
Lineage:
Process Step:
Process Description: FSIM Burn Probability, bp_20110915.img, file clipped to BLM states created for the GRSG Baseline analysis. Raster was reclassified using Nominal Classifications to create two categories of data, plus a zero category: Non-burnable = 0, Low probability = 0.00002 - 0.0043, and High Probability = 0.0043 - 0.0732. Reclassification of this two category dataset was based on a separate three category dataset. The three category dataset had the zero values removed from the data and the binning was distributed based on equal numbers of cells to create the three categories. The two categories dataset was then created by using the High category from the three category classification as the high value, and everything else except zero was classified as the low value. The resampled raster data were then exported to a vector polygon file and dissolved based on category.
Process Date: 20120301
Process Contact:
Contact Information:
Contact Organization Primary:
Contact Organization: Bureau of Land Management, National Operations Center
Contact Person: Wildlife Habitat Spatial Analysis Lab
Contact Position: GIS Analyst
Contact Address:
Address Type: physical address
Address: Denver Federal Center, Building 40
City: Lakewood
State or Province: CO
Postal Code: 80225
Country: US
Contact Voice Telephone: (303) 236-4810
Contact Electronic Mail Address: kmayne@blm.gov
Hours: 9 - 4 pm, MST, Mon-Fri
Contact Instructions: Please Contact through email.
Spatial Data Organization Information:
Direct Spatial Reference Method: Raster
Point and Vector Object Information:
SDTS Terms Description:
SDTS Point and Vector Object Type: GT-polygon composed of chains
Point and Vector Object Count: 1
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: 0.0000000037527980722984474
Ordinate Resolution: 0.0000000037527980722984474
Geodetic Model:
Horizontal Datum Name: D North American 1983
Ellipsoid Name: GRS 1980
Semi-major Axis: 6378137.0
Denominator of Flattening Ratio: 298.257222101
Entity and Attribute Information:
Detailed Description:
Entity Type:
Entity Type Label: BLM BER: Burn Probability - High (polygon)
Entity Type Definition: High burn probability.
Attribute:
Attribute Label: OBJECTID
Attribute Definition: Internal feature number.
Attribute Domain Values:
Unrepresentable Domain: Sequential unique whole numbers that are automatically generated.
Attribute Definition Source: ESRI
Attribute:
Attribute Label: Shape
Attribute Definition: Feature geometry.
Attribute Domain Values:
Unrepresentable Domain: Coordinates defining the features.
Attribute Definition Source: ESRI
Attribute:
Attribute Label: BURNPROB
Attribute Definition: "High" indicates high burn probability.
Attribute:
Attribute Label: Shape.area
Attribute Definition: Feature area.
Attribute:
Attribute Label: Shape.len
Attribute Definition: Feature length.
Overview Description:
Entity and Attribute Overview: This dataset represents the high burn probability category of data.
Distribution Information:
Distributor:
Contact Information:
Contact Organization Primary:
Contact Person: Wildlife Habitat Spatial Analysis Lab
Contact Organization: Bureau of Land Management, National Operations Center
Contact Position: GIS Analyst
Contact Address:
Address Type: physical address
Address: Denver Federal Center, Building 40
City: Lakewood
State or Province: CO
Postal Code: 80225
Country: US
Contact Voice Telephone: (303) 236-0446
Resource Description: Downloadable Data
Distribution Liability: The BLM assumes no responsibility for errors or omissions. No warranty is made by the BLM as to the accuracy, reliability, or completeness of these data for individual use or aggregate use with other data; nor shall the act of distribution to contractors, partners, or beyond, constitute any such warranty for individual or aggregate data use with other data. Although these data have been processed successfully on computers of BLM, no warranty, expressed or implied, is made by BLM regarding the use of these data on any other system, or for general or scientific purposes, nor does the fact of distribution constitute or imply any such warranty. In no event shall the BLM have any liability whatsoever for payment of any consequential, incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of profits arising out of the use or reliance on the geographic data or arising out of the delivery, installation, operation, or support by BLM.
Available Time Period:
Time Period Information:
Single Date/Time:
Calendar Date: 20150914
Metadata Reference Information:
Metadata Date: 20150901
Metadata Review Date: 20150901
Metadata Contact:
Contact Information:
Contact Organization Primary:
Contact Organization: Bureau of Land Management, National Operation Center
Contact Person: Alisa Froistad
Contact Position: Data Administrator
Contact Address:
Address Type: physical address
Address: Denver Federal Center, Building 40
City: Lakewood
State or Province: CO
Postal Code: 80225
Country: US
Contact Voice Telephone: (303) 236-2268
Contact Electronic Mail Address: afroistad@blm.gov
Metadata Standard Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata Standard Version: FGDC-STD-001-1998
Metadata Time Convention: local time
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