Landscape Fire and Resource Management Planning Tools (LANDFIRE) 20241218 LF 2023 raster digital data Sioux Falls, SD Earth Resources Observation and Science Center (EROS), U.S. Geological Survey https://doi.org/10.5066/P9BJP7OV https://www.landfire.gov Jennifer L. Long Timothy D. Hatten 2023 publication n/a US Geological Survey https://doi.org/10.3133/fs20233044 LANDFIRE's (LF) 2023 update (LF 2023) Existing Vegetation Type (EVT) represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western hemisphere. In this context, a terrestrial ecological system is defined as a group of plant community types that tend to co-occur within landscapes with similar ecological processes, substrates, and/or environmental gradients. See the EVT product page (https://landfire.gov/vegetation/evt) for more information about ecological systems and NVC classifications. EVT is mapped using decision tree models, field data, Landsat imagery, topography, and biophysical gradient data. Decision tree models are developed separately for tree, shrub, and herbaceous lifeforms which are then used to produce a lifeform specific EVT product. These models are generated for each Environmental Protection Agency (EPA) Level III Ecoregion (https://www.epa.gov/eco-research/ecoregions). Riparian, alpine, sparse, and other site-specific EVTs are constrained by predetermined masks. In LF 2023 Conterminous United States (CONUS) extent, LF will map the lifeform, cover, and height of existing vegetation in areas that were mapped as disturbed over the last twenty years (see LF Annual Disturbance products) using machine learning methods. These disturbed areas were the focus because they are the areas that have changed the most since LF 2016 Remap. To learn more about this new methodology for LF EVC, EVH, and Existing Vegetation Type (EVT) go to https://landfire.gov/data/lf2023. The LF 2023 Update (LF 2023, version 240) is the fourth update to LANDFIRE’s new base map LF 2016 Remap (version 200) and will be releasing throughout calendar year 2024. LF 2023 products are designed to facilitate national and regional level strategic fire and resource management planning and reporting of management activities. The principal purposes of the products include providing: 1) national level landscape scale geospatial products to support fire and fuels management planning and 2) consistent fuels products to support fire planning, analysis, and budgeting to evaluate fire management alternatives. Products are created at a 30meter raster; however, the applicability of products varies by location and specific use. LF products were designed to support 1) national (all states) strategic planning, 2) regional (single large states or groups of smaller states), and 3) strategic/tactical planning for large sub regional landscapes and Fire Management Units (FMUs) (such as significant portions of states or multiple federal administrative entities). The applicability of LF products to support fire and land management planning on smaller areas will vary by product, location, and specific use. Managers and planners must evaluate LF products according to the scale and requirements specific to their needs. Beginning in LF 2022 and onward, LANDFIRE Hawaii products are offered in the projection Hawaii_Albers_Equal_Area_Conic (ESRI: 102700). 2023 ground condition Complete Annually -160.6050 -154.7598 22.2719 18.8544 ISO 19115 Topic Category imageryBaseMapsEarthCover biota USGS Thesaurus fires hazard preparedness remote sensing image collections geospatial datasets geographic information systems None raster digital data Existing Vegetation Type EVT U.S. Geological Survey (USGS) U.S. Forest Service (USFS) LANDFIRE 2023 LF 2023 USGS Metadata Identifier USGS:673b9d33d34e689449dca98b Common geographic areas US HI United States Hawaii OCONUS None None LANDFIRE, Earth Resources Observation and Science Center (EROS), U.S. Geological Survey Customer Service Representative physical

47914 252nd Street

Sioux Falls SD 57198 U.S. 605-594-6151 helpdesk@landfire.gov These products were created by the LF team at USGS EROS, Sioux Falls, SD. Refer to the contact information throughout this metadata to contact the LF team. None in place Unclassified If there is ever doubt, contact the LF Help Desk at helpdesk@landfire.gov Microsoft Windows 10; ESRI ArcGIS Suite USGS Advanced Research Computing (ARC) 2021 publication https://www.usgs.gov/advanced-research-computing/usgs-denali-supercomputer https://www.usgs.gov/advanced-research-computing LF 2023 EVT for natural vegetation is the same as LF 2016 Remap EVT except in recently disturbed and developed ruderal classes. Modeled vegetation from 2016 replaced these classes, if the pixels were outside of new burnable developed classes or urban. For LF Remap EVT the Auto-Keys process was re-designed. Auto-Keys are used to determine Existing Vegetation Type classification based on plot data in the LF Reference Database (LFRDB). A validation of the EVT product is conducted by comparing the EVT product for a pixel with the Auto-Key EVT assignment for a sample plot contained in that pixel. These agreement assessments have been developed for each LF AK GeoArea. To read more about EVT agreement assessments go to https://landfire.gov/vegetation/evt. The products were pixel "truth" tested for consistency of land or water characteristics across all products. Products were formally tested to ensure that valid data was produced for all pixels. Each product was then validated and tested for duplicates, omissions, and errors. US Forest Service (USFS) US Natural Resource Manager's (USNRM) 2009 remote-sensing image https://data.fs.usda.gov/geodata/edw/datasets.php https://data.fs.usda.gov/nrm/briefingpapers/FACTS.pdf Digital and/or Hardcopy 2009 2023 observed FACTS Landscape change in forested areas US Forest Service (USFS) US Department of the Interior (USDOI) 2000 application/service https://www.nfpors.gov/ https://www.forestsandrangelands.gov/resources/overview/ Digital and/or Hardcopy 2000 2023 observed NFPORS National Fire Plan US Bureau of Land Management (USBLM) National Park Service (USNPS) US Forest Service (USFS) US Fish and Wildlife Service (USFWS) Fire Administration and the National Association of State Foresters US Bureau of Indian Affairs (USBIA) 1965 application/service https://www.nifc.gov/ https://www.nifc.gov/fire-information/maps Digital and/or Hardcopy 1965 2023 observed NIFC Wildfire maps. US Forest Service (USFS) 2012 raster digital data https://www.fs.usda.gov/science-technology/data-tools-products/fhp-mapping-reporting/national-insect-disease-risk-and-hazard-mapping Digital and/or Hardcopy 2012 2023 observed NIDRM NIDRM Insect and Disease Detection Survey US Forest Service (USFS) 1928 application/service Check https://landfire.gov/reference for more information. https://research.fs.usda.gov/programs/fia Digital and/or Hardcopy Unknown observed FIA Read more about each version of LANDFIRE and its inputs at https://landfire.gov/ US Geological Survey (USGS) 1982 raster digital data Fact Sheet 2022-3084 Reston, VA USGS https://doi.org/10.3133/fs20223084 https://www.usgs.gov/landsat-missions/landsat-collection-2-level-3-dynamic-surface-water-extent-science-product https://www.usgs.gov/landsat-missions Digital and/or Hardcopy Unknown ground condition DSWE The Landsat Collection 2 (C2) Level-3 Dynamic Surface Water Extent (DSWE) product provides raster layers that represent surface water inundation per-pixel in Landsat data. US Geological Survey (USGS) 1996 raster digital data https://doi.org/10.1016/j.isprsjprs.2018.09.006 https://www.mrlc.gov/data https://www.mrlc.gov/viewer/ https://www.sciencebase.gov/catalog/item/6345b637d34e342aee0863aa Digital and/or Hardcopy 2021 ground condition NLCD LANDFIRE always utilizes the latest products from NLCD, read more about each version of LANDFIRE and its inputs at https://landfire.gov/ US Department of Agriculture (USDA) 1961 application/service https://www.nass.usda.gov/ Digital and/or Hardcopy Unknown ground condition NASS Read more about each version of LANDFIRE and its inputs at https://landfire.gov/ US Geological Survey (USGS) 2005 raster digital data https://www.mtbs.gov/ https://www.mtbs.gov/viewer https://burnseverity.cr.usgs.gov/ Digital and/or Hardcopy 1984 2023 ground condition MTBS MTBS is an interagency program whose goal is to consistently map the burn severity and extent of large fires across all lands of the United States from 1984 to present. US Geological Survey (USGS) US Forest Service (USFS) 2001 application/service https://burnseverity.cr.usgs.gov/baer/ Digital and/or Hardcopy 2001 2023 ground condition BAER BARC BARC is a satellite-derived data layer of post-fire vegetation condition. The BARC has four classes, representing burn severity: high, moderate, low, and unburned. This product is used as an input to the soil burn severity map produced by the BAER teams. US Geological Survey (USGS) Gap Analysis Project (GAP) 2022 application/service https://doi.org/10.5066/P9Q9LQ4B Digital and/or Hardcopy 2022 ground condition PAD The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas. Microsoft Maps 2022 application/service https://github.com/Microsoft/USBuildingFootprints Digital and/or Hardcopy 2022 ground condition Building Footprint Microsoft Maps released country wide open building footprints datasets in the United States. This dataset contained 129,591,852 computer generated building footprints. US Geological Survey (USGS) 1984 raster digital data https://www.usgs.gov/landsat-missions/landsat-collection-2-level-3-burned-area-science-product https://doi.org/10.1016/j.rse.2020.111801 Digital and/or Hardcopy 1984 2023 ground condition BA The Landsat Collection 2 (C2) Level-3 Burned Area (BA) science product is designed to identify burned areas across all ecosystems (e.g., forests, shrublands, and grasslands) for Landsat 4-9 data, containing two acquisition-based raster layers that represent burn classification and burn probability. US Geological Survey (USGS) US Forest Service (USFS) 2007 remote-sensing image https://burnseverity.cr.usgs.gov/ravg/ Digital and/or Hardcopy Unknown ground condition RAVG The RAVG program provides assessments of vegetation conditions (burn severity) following large wildland fires on forested National Forest System (NFS) lands. Read more about each version of LANDFIRE and its inputs at https://landfire.gov/ Beginning with the new base map of LANDFIRE 2016 Remap (LF Remap), LF products were created using recent advances in image compositing, tiling algorithms, and faster computing hardware to ensure that LF products remained relevant. LF Remap leveraged the Landsat archive, lidar data, and user contributed field plot data compiled into the LF Reference Database (LFRDB), to create new vegetation products. Reference resources utilized in LF Remap and all updates since includes but is not limited to: Forest Inventory and Analysis (FIA) program plot data, Landsat Dynamic Surface Water Extent (DSWE), the National Land Cover Database (NLCD), and National Agricultural Statistics Service (NASS). FIA DSWE NLCD NASS 20241126 For LF 2023 reference resources include but are not limited to: Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC) and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), PAD 3.0 for federal and protected lands identification, and a rasterized version of the Microsoft building footprint for 2022 to update developed areas. Three main submitted sources were also used: the US Bureau of Land Management (BLM), National Park Service (NPS), and the US Fish and Wildlife Service (USFWS). MTBS BAER BARC RAVG PAD Building Footprint 20241126 Disturbances in LF 2023 were also identified with LF's Remote Sensing of Landscape Change (RSLC), which identifies spectral change in vegetation using automated algorithms and image analyst review of the entire country with Landsat imagery. Burned Area (BA) data from Landsat was also used and national events (polygons) were used to identify areas and types of disturbance. BA 20241126 To read more about LF reference resources go to https://landfire.gov/reference. Information about LF 2023 product testing is available by request or via the website at https://www.landfire.gov. 20241126 Raster Grid Cell 12600 20385 1 Hawaii Albers Conical Equal Area 8.0 18.0 -157.0 13.0 0.0 0.0 row and column 30.0 30.0 meters North_American_Datum_1983 GRS 1980 6378137.0 298.2572221010042 EVT LF 2023 EVT attributes spreadsheet. LF 2023 VALUE Code that identifies the vegetation and land cover types. LF 2023 -9999 NoData LF 2023 4401 9994 EVT_NAME Existing Vegetation Type name. LF 2023 See the ADD for additional information. LFRDB LF Reference Database (LFRDB) code. LF 2023 NA NoData LF 2023 4401 9994 EVT_FUEL EVT fuel code. LF 2023 NA NoData LF 2023 11 4620 EVT_Fuel_N EVT fuel name. LF 2023 NA NoData LF 2023 See the ADD for additional information. EVT_LF EVT lifeform. LF 2023 NA NoData LF 2023 Shrub Shrub lifeform. LF 2023 Tree Tree lifeform. LF 2023 Sparse Sparse. LF 2023 Herb Herbaceous lifeform. LF 2023 Water Water. LF 2023 Barren Barren. LF 2023 Developed Developed. LF 2023 Snow-Ice Snow/Ice. LF 2023 Agriculture Agriculture. LF 2023 EVT_PHYS EVT physiognomy. LF 2023 NA NoData LF 2023 Shrubland Shrubland. LF 2023 Riparian Riparian. LF 2023 Sparsely Vegetated Sparse. LF 2023 Grassland Grassland. LF 2023 Conifer Conifer. LF 2023 Hardwood Hardwood. LF 2023 Conifer-Hardwood Conifer- Hardwood LF 2023 Open Water Water LF 2023 Quarries-Strip Mines-Gravel Pits-Well and Wind Pads Strip mines, gravel pits, well/wind pads. LF 2023 Developed-Low Intensity Low intensity. LF 2023 Developed-Medium Intensity Medium intensity. LF 2023 Developed-High Intensity High intensity. LF 2023 Developed-Roads Roads LF 2023 Developed-Open Space Open space. LF 2023 Snow-Ice Snow. LF 2023 Agricultural Agricultural. LF 2023 Developed Developed. LF 2023 Exotic Herbaceous Exotic herbaceous. LF 2023 Exotic Tree-Shrub Exotic tree shrub. LF 2023 EVT_GP EVT group code. LF 2023 NA NoData LF 2023 11 829 EVT_GP_N EVT group name. LF 2023 NA NoData LF 2023 See ADD for additional information. SAF_SRM Crosswalk to Society of American Foresters and Society of Range Management cover types. LF 2023 NA NoData LF 2023 Crosswalk to Society of American Foresters and Society of Range Management cover types. EVT_ORDER EVT physiognomic order from FGDC classification. LF 2023 NA NoData LF 2023 Shrub-dominated Shrub dominated. LF 2023 No dominant lifeform No dominant lifeform. LF 2023 Herbaceous / Nonvascular-dominated Herbaceous dominated. LF 2023 Tree-dominated Tree dominated. LF 2023 No Dominant Life Form No dominant life form. LF 2023 Non-vegetated Non-vegetated. LF 2023 EVT_CLASS EVT physiognomic class from FGDC classification. LF 2023 NA NoData LF 2023 Dwarf Shrubland Dwarf shrub. LF 2023 Shrubland Shrubland. LF 2023 Sparsely Vegetated Sparsely vegetated. LF 2023 Herbaceous - forbland Herbaceous forbs. LF 2023 Closed tree canopy Closed tree canopy. LF 2023 Herbaceous - Shrub Steppe Herbaceous shrub steppe. LF 2023 Open Tree Canopy Open tree canopy. LF 2023 Herbaceous - Grassland Herbaceous grassland. LF 2023 Nonvascular Non-vascular. LF 2023 Sparse Tree Canopy Sparse tree canopy. LF 2023 Non-vegetated Non-vegetated. LF 2023 No Dominant Lifeform None. LF 2023 EVT_SBCLS EVT physiognomic subclass from FGDC classification. LF 2023 See ADD for additional information. R Red color value/255 LF 2023 0 255 G Green color value/255 LF 2023 0 255 B Blue color value/255 LF 2023 0 255 RED Red color value. LF 2023 0.0 1.0 GREEN Green color value. LF 2023 0.0 1.0 BLUE Blue color value. LF 2023 0.0 1.0 LANDFIRE (LF) 2023 Existing Vegetation Type (EVT) HI. An Attribute Table is included with each product download as a .csv and embedded in the metadata. The Attribute Data Dictionary (ADD) can be found at https://www.landfire.gov/. https://landfire.gov/vegetation/evt U.S. Geological Survey GS ScienceBase mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov This product is reproduced from geospatial information prepared by the U.S. Department of the Interior (DOI) USGS EROS. By removing the contents of this package or taking receipt of these files via electronic file transfer methods, you understand that the data stored on this media can be updated at any time. Represented features may not be in an accurate geographic location. USGS EROS makes no expressed or implied warranty, including warranty of merchantability and fitness, with respect to the character, function, or capabilities of the data or their appropriateness for any user's purposes. USGS EROS reserves the right to correct, update, modify, or replace this geospatial information without notification. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. ARCG 20241126 LF 2023 https://doi.org/10.5066/P9BJP7OV none 20241218 LANDFIRE, Earth Resources Observation and Science Center (EROS), U.S. Geological Survey Customer Service Representative physical

47914 252nd Street

Sioux Falls SD 57198 U.S. 605-594-6151 helpdesk@landfire.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time None Unclassified None