The average relative difference of the mean inter-annual variability of vegetation production between a reference time period (1984-2014) and the current time period (2015-2019).

The percent area of a landscape analysis unit where the Wildland Fire Hazard 2020 class is High.

The percent area of a landscape analysis unit where the Wildland Fire Hazard 2020 class is High and the LANDFIRE Fire Regime is Moderate.

LANDFIRE's (LF) Remap Vegetation Condition Class (VCC) is a reclassification and categorization of the LF Remap Vegetation Departure (VDep) product. VCC indicates the general level to which current vegetation is different from the simulated historical reference condition. Therefore, VCC is a derivative of VDep; the VDep product indicates how different current vegetation is compared to the estimated historical reference condition, and is based on change to species composition, structure, and canopy closure. To learn more about VCC and VDep go to https://www.landfire.gov/fireregime.php. Condition classes for VCC are defined in two ways; the original 3 category system from Fire Regime Condition Class Guidebook (FRCC Guidebook), and a newer 6 category system that provides additional precision. For the original 3 category system, the VDep value is reclassified as: Condition Class I: VDep value from 0 to 33 (Low Departure), Class II: VDep value between 34 to 66 (Moderate Departure), and Condition Class III: VDep value from 67 to 100 (High Departure). The 6 category system provides more resolution to VCC and is collapsible to the 3 category system. The 6 VCC categories are defined as: Condition Class I.A: VDep between 0 and 16 (Very Low Departure), Condition Class I.B: VDep between 17 and 33 (Low to Moderate Departure); Condition Class II.A: VDep between 34 and 50 (Moderate to Low Departure); Condition Class II.B: VDep between 51 and 66 (Moderate to High Departure); Condition Class III.A: VDep between 67 and 83 (High to Moderate Departure), and Condition Class III.B: VDep between 84 and 100 (High Departure).

LANDFIRE's (LF) 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. EVT also includes ruderal or semi-natural vegetation types within the U.S. National Vegetation Classification [(NVC) http://usnvc.org/]. See the EVT product page (https://www.landfire.gov/evt.php) for more information about ecological systems and NVC. EVT is mapped using decision tree models, field data, Landsat imagery, elevation, 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. Urban and developed areas are derived from the National Land Cover Database (NLCD), whereas agricultural lands originate from the Cropland Data Layer (CDL) and Common Land Unit (CLU) database. Developed ruderal classes are identified by combining wildland-urban-interface (WUI) data with population density information from the US Census Bureau. Annual Disturbance products are included to describe areas that have experienced landscape change within the previous 10-year period. EVT is then reconciled through QA/QC measures to ensure lifeform is synchronized with both Existing Vegetation Cover (EVC) and Height (EVH) products.

LANDFIRE's (LF) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), topographic, climate, and other geospatial data sets to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100%. The three independent lifeform datasets are merged into a single product. The EVC product is then reconciled through QA/QC measures to ensure lifeform is synchronized with both Existing Vegetation Height (EVH) and Type (EVT) products. Disturbance events not visible in the source imagery are accounted for by incorporating LF Remap Annual Disturbance products. LF uses EVC as an input for LF Remap Fuel Vegetation Cover (FVC).

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.2 annual land cover products (1985–2018) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2018) at to a reference sample of 26,971 Landsat resolution (30m x 30m) pixels. These pixels were selected from a sample frame of all pixels in the ARD grid system which fell within the map area (Dwyer et al., 2018). Interpretation used the TimeSync reference data collection tool which visualizes Landsat images and Landsat data values for all usable images in the time series (1984–2018) (Cohen et al., 2010). Interpreters also referred to air photos and high resolution images available in Google Earth as well as several ancillary data layers. The interpreted land cover attributes were crosswalked to the LCMAP annual land cover classes: Developed, Cropland, Grass/Shrub, Tree Cover, Wetland, Water, Snow/Ice and Barren. Validation analysis directly compared reference labels with annual LCMAP land cover map attributes by cross tabulation. The results of that assessment are reported here as confusion matrices for land cover agreement and land cover change agreement. Accuracy and standard errors have been calculated using stratified estimation (Stehman, 2014). Land cover class proportions were also estimated from the reference data for each year, 1985–2018. A cluster sampling formulation was used to calculate standard sampling error for summary tables reporting results for multiple years of data comparison.

LANDFIRE's (LF) Remap Vegetation Departure (VDep) product categorizes departure between current vegetation condition and reference vegetation condition, according to the methods outlined in the Interagency Fire Regime Condition Class Guidebook [FRCC Guidebook (Hann et al 2010)]. VDep differs from the FRCC Guidebook, however, because it is based on the departure of current vegetation condition only, whereas the FRCC Guidebook approach includes departure of current fire regimes for the reference period. For VDep, summary units are defined as a BioPhysical Setting (BpS) with identical reference condition values regardless of map zone. For example, when a BpS is present in map zone 1, 2, 4, 5, 6 and 8, the reference conditions for this BpS are identical in map zones 1, 2, 4, 5, and 8, those map zones become a summary unit for VDep computation. Since reference conditions are unique for this BpS in map zone 6, it is a separate summary unit for calculating VDep. Within each BpS summary unit, we compare the reference percentage of each Succession Class (SClass) to the current percentage, then the smaller of the two is summed to determine the similarity index for the BpS. This value is then subtracted from 100 to determine the departure value, VDep value is always between 0 and 100, with 100 representing maximum departure. Reference conditions are derived from quantitative vegetation dynamics models that mimic native disturbance regimes. The current conditions are derived from the corresponding LF Remap SClass data. The proportion of the landscape occupied by each SClass, in each BpS unit, within each summary unit represents current condition of that SClass in VDep calculation. VDep is based entirely on the remaining area of each BpS unit that is occupied by valid SClasses.

The LANDFIRE Percent Mixed-Severity Fire (PMS) raster dataset (LF US_120_PMS) was combined with the Monitoring Trends in Burn Severity (MTBS) data (1984-2017) to identify areas that have experienced unnaturally severe wildfires in the recent past (1984-2017). Areas mapped are greater than 50% Mixed-Severity Fire and a high severity fire MTBS mapped fire at the same location.

LANDFIRE’s (LF) 2023 Vegetation Condition Class (VCC) is a reclassification and categorization of the LF 2023 Vegetation Departure (VDep) product. VCC indicates the general level to which current vegetation is different from the simulated historical reference condition. Therefore, VCC is a derivative of VDep; the VDep product indicates how different current vegetation is compared to the estimated historical reference condition, and is based on change to species composition, structure, and canopy closure. Condition classes for VCC are defined in two ways; the original 3 category system from Fire Regime Condition Class Guidebook (FRCC Guidebook), and a newer 6 category system that provides additional thematic detail. For the original 3-category system, the VDep value is reclassified as: Condition Class I: VDep value from 0 to 33 (Low Departure), Class II: VDep value between 34 - 66 (Moderate Departure), and Condition Class III: VDep value from 67 to 100 (High Departure). The 6-category system provides more detail and is collapsible to the 3-category system. The 6 VCC categories are defined as: Condition Class I.A: VDep between 0 and 16 (Very Low Departure), Condition Class I.B: VDep between 17 and 33 (Low to Moderate Departure); Condition Class II.A: VDep between 34 and 50 (Moderate to Low Departure); Condition Class II.B: VDep between 51 and 66 (Moderate to High Departure); Condition Class III.A: VDep between 67 and 83 (High to Moderate Departure), and Condition Class III.B: VDep between 84 and 100 (High Departure).