20230713 16031200 1.0 FALSE S_USA.Fire_FireshedReg_Fireshed_Exp S_USA.Fire_FireshedReg_Exp_RC Relationship S_USA.Fire_FireshedReg_Exp_RC Relationship 002 20230130 16194300 20230130 16194300 FGDC CSDGM Metadata 150000000 5000 FGDC USFS Washington Office, Wildfire Risk Reduction Infrastructure Team Please send an e-mail to the address below. Washington DC 20250 michael.scanlon@usda.gov 20230130 ArcGIS Metadata 1.0 USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 US SM.FS.data@usda.gov None GDB see Format Specification ArcGIS Geodatabase file Files zipped with 7-Zip 19.0 https://doi.org/10.2737/RDS-2020-0054 RDS-2020-0054 http://data.fs.usda.gov/geodata/edw/datasets.php Table S_USA.Fire_FireshedReg_Fireshed_Exp 2022-05-06T11:40:05 Bunzel, Ken Evers, Cody R. Day, Michelle A. Ringo, Chris D. Alcasena Urdíroz, Fermin J. Ager, Alan A. tabular digital data <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>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 exposure rather than mapping the value at risk across all lands in the conterminous United States. Risk is composed of three components: (1) ignition likelihood, (2) expected fire intensity, and (3) effects related to expected fire intensity. Wildfire exposure, by contrast, only concerns the juxtaposition of threatened values in relation to predicted fire occurrence and intensity without estimating potential loss. Exposure is the measure of structures that are exposed to fires that originate within the Fireshed or Project Area. The annual average measure is constructed by averaging potential exposure from the "FSIM" fire simulation database. Fire simulations are based on fuel conditions in 2014. Structures are based on Microsoft Building Footprints identified using a computer vision algorithm on imagery from 2012 - 2016. Exposure measures are adjusted where wildfire or management activities have changed the fuel conditions since 2014. 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. The fireshed and project area boundaries are designed to delineate hotspots of fire transmission to adjacent or nearby communities to facilitate cohesive cross-boundary risk mitigation planning.</SPAN></P></DIV></DIV></DIV> The Project Area exposure data are designed to be joined to the Fireshed Registry Project Areas, matching on the PA_ID field. Each exposure measure can also be summarized and joined to the Fireshed polygons by summing Project Area exposure by Fireshed ID. Exposure metrics are designed to be used for strategic allocation. Tactical operations should incorporate additional local knowledge. This project was funded by the USDA Forest Service, State & Private Forestry and the USDA Forest Service, Rocky Mountain Research Station. Additional acknowledgments are extended to Portland State University, Oregon State University, USDA Forest Service International Visitor Program, and Kingbird Software. Michelle Day Rocky Mountain Research Station Biological Scientist 541-758-7768 3200 SW Jefferson Way Corvallis OR 97331 US michelle.day@usda.gov United States wildfire management wildfire exposure wildfire transmission wildfire ISO 19115 Topic Category geoscientificInformation National Research & Development Taxonomy Natural Resource Management & Use Fire effects on environment Forest management Fire Wildland/urban interface Natural Resource Management & Use Fire effects on environment geoscientificInformation Forest management Fire wildfire management Wildland/urban interface wildfire exposure United States wildfire transmission wildfire The U.S. Forest Service makes no warranty, express or implied, nor assumes any liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data or for the improper or incorrect use of those data. The data are dynamic and may change over time. The user is responsible for verifying the limitations of the geospatial data and for using the data accordingly. 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 these 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. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>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: Evers, Cody R.; Ringo, Chris D.; Ager, Alan A.; Day, Michelle A.; Alcasena Urdíroz, Fermin J.; Bunzel, Ken. 2020. The Fireshed Registry: Fireshed and project area boundaries for the continental United States. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2020-0054 The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.</SPAN></P></DIV></DIV></DIV> Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388 Ground condition 2022-01-01 -127.881563 -65.329158 22.932504 51.595025 Rocky Mountain Research Station developed the protocol for measuring structure exposure which is used in multiple research publications. The US Forest Service Washington Office Fire and Aviation Management (WO-FAM) staff is responsible for managing and delivering those data for authoritative management interpretation. No consistency evaluation was performed. Fireshed and project area boundaries reflect the resolution of the original building exposure raster of 270 meters. These boundaries can be considered complete, but note that boundaries representing features such as national boundaries and coastlines will be greatly generalized and, in the case of islands, they may be omitted entirely. The fuels data used in this prediction are not current, due to the data vintage of fuel conditions used in the available FSim simulations. Thus our predictions in areas that have had disturbance and management since 2014 should be used with caution, with consideration of finer scaled data. As with all risk products there is substantial uncertainty associated with these estimates. This assessment concerns exposure and not risk as we make no predictions about loss. The boundaries among adjacent firesheds are the product of the SLIC algorithm, which is dependent on the initial placement of points from which the image segments (i.e., clusters) are derived. This means that the boundaries between adjacent firesheds, particularly those in areas with homogenous exposure, may vary over successive runs. These data represent one such solution. Achanta, R.; Shaji, A.; Smith, K.; Lucchi, A.; Fua, P.; Süsstrunk, S. 2012. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(11): 2274-2282. https://doi.org/10.1109/tpami.2012.120 See Measure Description Fireshed and project area boundaries reflect the resolution of the original building exposure raster of 270 meters. These boundaries can be considered complete, but note that boundaries representing features such as national boundaries and coastlines will be greatly generalized and, in the case of islands, they may be omitted entirely. See Measure Description Vector spatial wildfire perimeter data were obtained for the years 2015-2020. Wildland Fire Decision Support System (WFDSS) WFDSS 2022-05-06T11:40:05 National Wildfire Coordination Group National Wildfire Coordination Group USA vector digital data https://wfdss.usgs.gov/wfdss/WFDSS_Data_Downloads.shtml Publication Date 2015-01-01 2020-01-01 Records of prescribed fire and mechanical fuels treatment data. Forest Service Activity Tracking System (FACTS) FACTS 2022-05-06T11:40:05 USDA Forest Service National Resource Manager, USDA Forest Service Washington, D.C. vector digital data Accessed 27 August 2020 https://www.fs.usda.gov/managing-land/natural-resource-manager#facts Publication Date 2015-01-01 2018-01-01 Vector spatial wildfire and prescribed burning data for the years 2015-2018. California Wildfire Perimeters, (1950+) CalFire 2022-05-06T11:40:05 CalFire (California Department of Forestry and Fire Protection) California Department of Forestry and Fire Protection (CalFire) Sacramento, California vector digital data Accessed 16 March 2020 https://hub.arcgis.com/datasets/653647b20bc74480b335e31d6d81a52f?geometry=-150.648%2C31.426%2C-88.114%2C43.578 Publication Date 2015-01-01 2018-01-01 Vector spatial wildfire perimeter data were obtained for the years 2015-2018. Monitoring Trends in Burn Severity (MTBS) MTBS 2022-05-06T11:40:05 U.S. Department of Agriculture Forest Service and U.S. Geological Survey U.S. Department of Agriculture Forest Service and U.S. Department of the Interior USA vector digital data Accessed 6 November 2019 https://www.mtbs.gov/index.php/direct-download Publication Date 2015-01-01 2018-01-01 Vector spatial data for the years 2015-2018 for wildfire perimeters and for various forest management activities, including prescribed burning, canopy thinning, and mastication. LANDFIRE Public Events Geodatabase LANDFIRE 2022-05-06T11:40:05 U.S. Department of Agriculture Forest Service and U.S. Department of the Interior USA LANDFIRE vector digital data Accessed 13 November 2019 https://www.landfire.gov/publicevents.php Publication Date 2015-01-01 2018-01-01 Building exposure for the entire U.S. was first calculated using FSim ignition points and fire perimeters (using a range of historical fire weather and fuels data from LANDFIRE 2014) and intersecting perimeters with Microsoft Building Footprints (ca. 2015) (https://github.com/microsoft/USBuildingFootprints) and attributing annual exposure to those ignitions. This means that values reflect the source of exposure, as opposed to where buildings are actually located. 2019-11-14 “Firesheds” and "Project Areas" within the Fireshed Registry are nested accounting units that are delineated based on a smoothed building exposure map of the conterminous U.S. These boundaries were created by dividing up the landscape into comparably-sized units that represent similar source levels of community exposure to wildfire risk. The size of firesheds was specified to contain 99% of the large fires, with fire sizes generally smaller than 250,000 acres, although the largest extreme event fires can span multiple firesheds. 2019-11-14 Exposure values were aggregated by projecting points onto a 270-m grid. To emphasize the general geographic patterns of risk and account for the stochasticity of extreme fire events, the exposure grid was first log10-transformed and then smoothed using focal statistics using a moving circular window with a 10-kilometer (km) radius using the focal function in the R Raster package. The entire grid was then normalized (0-1). Hijmans, Robert J.; van Etten, Jacob. 2012. raster: Geographic analysis and modeling with raster data. R package version 2.0-12. http://CRAN.R-project.org/package=raster 2019-11-14 The exposure grid was divided into roughly equal-sized spatial units at two different scales: the project area (~25,000 acres) and the fireshed (~250,000 acres). Both units were defined using image segmentation (SLIC) based on both geographic distance and magnitude of exposure. The approach is based on a modified form of K-means clustering that includes an additional parameter to account for the cluster shape. In order to ensure the units of both scales were nested, we adjusted the boundary of the fireshed to match underlying project areas boundaries using a majority rule. Thus, when a project area spanned two firesheds, the overlapping area was added to the majority fireshed (and subtracted from the minority fireshed). 2019-11-14 To account for the fact that wildfire risk and risk mitigation efforts occur at multiple scales, we assessed risk exposure at stand-, project-, and fireshed-level scales. We created these layers in such a way that a finer-scale is nested within a coarser-scale, in much the same way as a drainage is nested within a larger watershed. This dataset includes the project- and fireshed-scale boundaries, together with estimates of the annual number of buildings exposed from ignitions within these boundaries. 2019-11-14 Pixel values from the original 270-m grid (i.e., prior to being log10-transformed and smoothed) were summed to estimate exposure at the project- and fireshed-levels. Note that since simulated fires from Fsim were modeled based on 2014 fuels, the exposure summaries here do not include exposure from stands that have been disturbed by wildfire or management activities since 2014. Records of prescribed fire and mechanical fuels treatment data from the USDA Forest Service Activity Tracking System (FACTS 2021), wildfire area burned data from MTBS (2021), and prescribed fire data from CalFire (2021) nor present in FACTS or MTBS were used to adjust exposure with the assumption that areas recently treated (2015-2020) or burned would not contribute to wildfire exposure to communities. 2020-08-31 Researchers generate new activity filters each year and summarize detailed exposure numbers for each Project Area. Data sets for eastern US and western US are compiled separately. 2022-02-23 Temporal data set construction: The '2019-2020' and '2021' data sets were each summarized to create unique fireshed data sets for each disturbance version. Start_Date of '1/1/2020' and End_Date of '1/1/2022' were applied to all records in the '2019-2020' data set. Start_Date of '1/1/2022' and End_Date of '1/1/999' were applied to all records in the '2021' data set, before the records were appended together. 2022-02-24 Temporal data set construction: East and West Project Area data were combined into a CONUS data set for the '2019-2020' disturbance version. The process was repeated for disturbance version '2021'. Start_Date of '1/1/2020' and End_Date of '1/1/9999' were applied to all records in the '2019-2020' data set. Changes between versions were identified by finding changes in Exp_Total for each Project Area between the '2019-2020' data set and the '2021' data set. Changed Planning Area records were added and dates were reset to reflect the transition as of '1/1/2022'. 2022-02-24 S_USA.Fire_FireshedReg_Fireshed_Exp Tabular: These building exposure data are designed to join with Fireshed Registry Fireshed vector polygons. They are filtered to a set of land bases (e.g., non-USFS lands vs. USFS lands) and corrected for disturbances (e.g., stands were excluded if they were recently burned in a wildfire or experienced thinning or mastication). Exposure is a measure of the annual average number of exposures that might be 'exposed' to fires that originate within the Fireshed. Exposure is assigned to the origin of the fire and not the location of the structure, thus exposed structures occur both within and outside of the Fireshed. None Table 15376 Regional_All_Land_Rank For each FS Region, rank all firesheds from highest to lowest by the sum of Exp_USFS_ManagedForest plus Exp_NonUSFS_ManagedForest. USFS Integer positive values. Regional_All_Land_Rank SmallInteger 2 5 0 Exp_USFS_Managed Predicted building exposure from US Forest Service lands available for mechanical treatment. Attribute Exp_USFS filtered to only inlcude manageable lands. Filter based on the protected areas database (USGS, 2016, 2019) plus USFS wilderness, roadless and nationally designated areas databases. Internal validation: This field combined with Exp_USFS_Protected should equal Exp_USFS. Managed exposure includes both forested and non-forested exposure. Decimal positive values including zero and null. Exp_USFS_Managed Double 8 38 8 Regional_USFS_Rank For each FS Region, rank all firesheds from highest to lowest by Exp_USFS_ManagedForest values. USFS Integer positive values. Regional_USFS_Rank SmallInteger 2 5 0 Exp_USFS_ManagedConifer Predicted building exposure from US Forest Service lands with conifer land cover available for mechanical treatment; not available for eastern US. Attribute Exp_USFS filtered for both conifer lands and manageable landbase. Internal validation: This field should be a less than or equal to both Exp_USFS_Conifer and Exp_USFS_Managed. Decimal positive values including zero and null. Exp_USFS_ManagedConifer Double 8 38 8 Exp_USFS_ManagedForest Predicted building exposure from US Forest Service lands with forested land cover available for mechanical treatment. Attribute Exp_USFS filtered to for both forested lands and manageable landbase. Internal validation: This field should be less than or equal to both Exp_USFS_Managed and Exp_USFS_Forest. Decimal positive values including zero and null. Exp_USFS_ManagedForest Double 8 38 8 Start_Date Time series data management. The beginning date when this row of data was accurate. ESRI Date - Time field type, with Dates only. Calendar dates. Start_Date Date 8 0 0 National_All_Land_Rank Rank all firesheds from highest to lowest based on the sum of Exp_USFS_ManagedForest and Exp_NonUSFS_ManagedForest values. USFS Integer positive values. National_All_Land_Rank SmallInteger 2 5 0 Exp_USFS_Protected Predicted building exposure from US Forest Service lands not available for mechanical treatment. Attribute Exp_USFS filtered to only inlcude protected lands. Filter based on the protected areas database (USGS, 2016, 2019) plus USFS wilderness, roadless and nationally designated areas databases. Internal validation: This field combined with Exp_USFS_Managed should equal Exp_USFS. Decimal positive values including zero and null. Exp_USFS_Protected Double 8 38 8 Exp_NonFS Predicted building exposure from non-Forest Service lands. Attribute Exp_Total filtered to exclude Forest Service lands. Internal validation: This field combined with Exp_FS should equal Exp_Total. Compare NonFS exposure to USFS exposure to understand how NonFS lands contribute to the overall exposure. Decimal positive values including zero and null. Exp_NonFS Double 8 38 8 Exp_USFS_Conifer Predicted building exposure from US Forest Service lands with conifer land cover. Attribute Exp_USFS filtered to only inlcude conifer lands. Filter based on Forest Vegetation Simulator forest types (Crookston and Dixon, 2005). Internal validation: This field should be a less than or equal to Exp_USFS_Forest. Conifer exposure is from both managed and protected lands. Decimal positive values including zero and null. Exp_USFS_Conifer Double 8 38 8 Exp_USFS_NonForest Predicted building exposure from US Forest Service lands without forested land cover. Attribute Exp_USFS filtered to only inlcude non-forested lands. Filter based on the National Landcover Data (USGS, 2011). Internal validation: This field combined with Exp_USFS_Forest should equal Exp_USFS. Non-forested exposure is from both managed and protected lands. Decimal positive values including zero and null. Exp_USFS_NonForest Double 8 38 8 Exp_NonFS_Forest Predicted building exposure from non-Forest Service lands with forested land cover. Attribute Exp_NonFS filtered to only inlcude forested lands. Filter based on the National Landcover Data (USGS, 2011). Internal validation: This field combined with Exp_NonFS_NonForest should equal Exp_NonFS. Forested exposure is from both managed and protected lands. Decimal positive values including zero and null. Exp_NonFS_Forest Double 8 38 8 OBJECTID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. OBJECTID OID 4 10 0 Exp_NonFS_ManagedConifer Predicted building exposure from non-Forest Service lands with conifer land cover available for mechanical treatment; not available for eastern US. Attribute Exp_USFS filtered for both conifer lands and manageable landbase. Internal validation: This field should be a less than or equal to both Exp_USFS_Conifer and Exp_USFS_Managed. This exposure measure (with 2019-2020 disturbance) was used to model action in "Planning for future fire: Scenario analysis of an accelerated fuel reduction plan for the western United States", https://www.fs.usda.gov/treesearch/pubs/63129. Decimal positive values including zero and null. Exp_NonFS_ManagedConifer Double 8 38 8 Exp_USFS_Forest Predicted building exposure from US Forest Service lands with forested land cover. Attribute Exp_USFS filtered to only inlcude forested lands. Filter based on the National Landcover Data (USGS, 2011). Internal validation: This field combined with Exp_USFS_NonForest should equal Exp_USFS. Forested exposure is from both managed and protected lands. Decimal positive values including zero and null. Exp_USFS_Forest Double 8 38 8 Crisis_Strategy Firesheds used in the FY 2022 Landscape analysis process. 'All-Lands' priority firesheds were published with the "Confronting the Wildfire Crisis" strategy document that was released in December of 2021. The document included a map of 141 firesheds where scenario planning scheduled the most treatment throughout the western U.S. https://usdagcc.sharepoint.com/sites/fs-wo-oc/Fire-Hub/SiteAssets/Confronting%20the%20Wildfire%20Crisis/Confronting%20the%20Wildfire%20Crisis.pdf 'USFS-Only' priority firesheds include an additional list of 130 firesheds with the highest measure of manageable conifer exposure on Forest Service lands. Where both criteria are met, only the 'All-Lands' label is applied. 'All-Lands', 'USFS-Only', or null Crisis_Strategy String 10 0 0 Dist_Vs All exposure metrics are updated for disturbance as defined here. Years of disturbance activities in the value domain are defined as Dist_Vs = 2019-2020 accounts for hazardous fuels treatments through 2019 and wildfire disturbances through October 2020; Dist_Vs = 2021 accounts for disturbances through 2021. More values will be added for future updates. '2019-2020', '2021' Dist_Vs String 50 0 0 Exp_NonFS_ManagedForest Predicted building exposure from non-Forest Service lands with forested land cover available for mechanical treatment. Attribute Exp_NonFS filtered for both forested lands and manageable landbase. Internal validation: This field should be less than or equal to both Exp_NonFS_Managed and Exp_NonFS_Forest. Decimal positive values including zero and null. Exp_NonFS_ManagedForest Double 8 38 8 Exp_NonFS_NonForest Predicted building exposure from non-Forest Service lands without forested land cover. Attribute Exp_NonFS filtered to only inlcude non-forested lands. Filter based on the National Landcover Data (USGS, 2011). Internal validation: This field combined with Exp_NonFS_Prot should equal Exp_NonFS. Non-forested exposure is from both managed and protected lands. Decimal positive values including zero and null. Exp_NonFS_NonForest Double 8 38 8 Exp_NonFS_Conifer Predicted building exposure from non-Forest Service lands with conifer land cover. Attribute Exp_NonFS filtered to only inlcude conifer lands. Filter based on Forest Vegetation Simulator forest types (Crookston and Dixon, 2005). Internal validation: This field should be less than or equal to Exp_NonFS_Forest. Conifer exposure is from both managed and protected lands. Decimal positive values including zero and null. Exp_NonFS_Conifer Double 8 38 8 Exp_NonFS_Managed Predicted building exposure from non-Forest Service lands available for mechanical treatment. Attribute Exp_NonFS filtered to only inlcude manageable lands. Filter based on the protected areas database (USGS, 2016, 2019) plus USFS wilderness, roadless and nationally designated areas databases. Internal validation: This field combined with Exp_NonFS_Protected should equal Exp_NonFS. Managed exposure includes both forested and non-forested exposure. Decimal positive values including zero and null. Exp_NonFS_Managed Double 8 38 8 Exp_NonFS_Protected Predicted building exposure from non-Forest Service lands not available for mechanical treatment. Attribute Exp_NonFS filtered to only inlcude protected lands. Filter based on the protected areas database (USGS, 2016, 2019) plus USFS wilderness, roadless and nationally designated areas databases. Internal validation: This field combined with Exp_NonFS_Managed should equal Exp_NonFS. Decimal positive values including zero and null. Exp_NonFS_Protected Double 8 38 8 KEY_PERFORMANCE_INDICATOR Key_Preformance_Indicator String 3 0 0 Is work in the fireshed contributing to the fireshed key performance indicator? FAM will determine which firesheds are included in the KPI measurement. Yes Yes USFS No No USFS National_USFS_Rank Rank all firesheds from highest to lowest by Exp_USFS_ManagedForest values. USFS Integer positive values. National_USFS_Rank SmallInteger 2 5 0 End_Date Time series data management. The ending date when this row of data was accurate. Null values indicate that the record is currently accurate. ESRI Date - Time field type, with Dates only. Calendar dates. End_Date Date 8 0 0 Exp_USFS Predicted building exposure from US Forest Service lands. Attribute Exp_Total filtered to only inlcude US Forest Service ownwership. Internal validation: This field combined with Exp_NonFS should equal Exp_Total. Compare USFS exposure to NonFS exposure to understand how USFS lands contribute to the overall exposure. Decimal positive values including zero and null. Exp_USFS Double 8 38 8 Exp_NonFS_NonConifer_HiHaz Predicted building exposure excluding non-Forest Service lands, excluding conifer land cover, filtered for high or very high hazard potential, and available for mechanical treatment. Attribute Exp_NonFS_Managed filtered to exclude conifer land cover and moderate or low hazard potential. Wildfire hazard potential filter based on (Dillon and Gilbertson-Day, 2020); not available for eastern US. This exposure measure was explicitly used in the 2021 3-zone scenario for the western US, shared through the "Confronting the Wildfire Crisis Strategy." Decimal positive values including zero and null. Exp_NonFS_NonConifer_HiHaz Double 8 38 8 Exp_Total Total predicted building exposure from ignitions on undisturbed lands within this fireshed. Exp_Total describes the overall exposure of structures to wildfire. Bunzel et.al. Decimal positive values including zero and null. Exp_Total Double 8 38 8 FSHED_ID Unique fireshed identifier USFS 1 7709 FSHED_ID Integer 4 10 0 Fireshed science is a way to measure the relative likelihood that a fire in this area will grow and encompass structures. The publication is a compiled combination of fireshed registry structure exposure data sets generated by researchers for eastern and western conterminous United States. Structure exposure at this level is useful for strategic resource allocation. In addition, the data set includes multiple years of results, represented with Start and End dates to support temporal system versioning. These metrics are designed to be joined to the Fireshed Registry Project Areas geographic theme. Null values in the exposure attributes occur when no calculation was done. This may happen if the selected land base (such as USFS ownership) does not occur in the selected Project Area. Null is also used when an attribute is only calculated for part of the U.S. Researchers originally called these "annual TRansmission" (a.k.a. 'aTR') values. Those labels were changed to Exposure values, 'Exp', for a simpler shorthand label. None provided dataset