Data includes satellite derived pre-fire functional group cover of annual and perennial herbaceous, shrubs, bareground and litter across four rangeland megafires in the Western US, as well as field estimated invasive annual grass measurements from the 2nd to 3rd years post-fire. Additional landscape and restoration treatment covariates hypothesized to influence post-fire invasive annual grass cover are included.

Fifteen fires from the Chronosequence dataset (see Knutson et al. 2014) were visited in 2012 and 2013 and surveyed for cover of lichens and mosses. Fires were selected to cover the range of average precipitation for each of three water years following fire, fire severity, time since fire, season of ignition, total acres burned and grazing intensity. Cattle grazing was characterized by distance from water sources for cattle, cow dung density counts and Animal Unit Months from the Rangeland Administration System of the Bureau of Land Management. Fire was characterized by whether or not a site burned, time since fire, the area burned, and an estimated amount of shrub cover consumed by the fire as compared to seemingly comparable unburned sites. In total, 99 plots were surveyed.

Fifteen fires from the Chronosequence dataset (see Knutson et al. 2014) were visited in 2012 and 2013 and surveyed for cover of lichens and mosses. Fires were selected to cover the range of average precipitation for each of three water years following fire, fire severity, time since fire, season of ignition, total acres burned and grazing intensity. Cattle grazing was characterized by distance from water sources for cattle, cow dung density counts and Animal Unit Months from the Rangeland Administration System of the Bureau of Land Management. Fire was characterized by whether or not a site burned, time since fire, the area burned, and an estimated amount of shrub cover consumed by the fire as compared to seemingly comparable unburned sites. In total, 99 plots were surveyed.

Data is a combined collection of post-fire species point intercept cover monitoring data across the Murphy 2007 fire, Rush 2012 fire, Holloway 2012 fire, and Soda 2015 fire. Data was collected between 2008 and 2022 by the Bureau of Land Management, US Geological Survey, and Idaho Fish and Wildfire for various purposes. The species data was leveraged to assess post-fire community structure and trajectories.

Data is a combined collection of post-fire species point intercept cover monitoring data across the Murphy 2007 fire, Rush 2012 fire, Holloway 2012 fire, and Soda 2015 fire. Data was collected between 2008 and 2022 by the Bureau of Land Management, US Geological Survey, and Idaho Fish and Wildfire for various purposes. The species data was leveraged to assess post-fire community structure and trajectories.

Data includes functional group cover of exotic annual grasses, deep rooted perennial grasses, and shallow rooted perennial grasses within the first five years after the 2015 Soda wildfire across different post-fire restoration treatments. Additional landscape and weather covariates hypothesized to influence treatment effectiveness are included.

Data includes functional group cover of exotic annual grasses, deep rooted perennial grasses, and shallow rooted perennial grasses within the first five years after the 2015 Soda wildfire across different post-fire restoration treatments. Additional landscape and weather covariates hypothesized to influence treatment effectiveness are included.

LANDFIRE's (LF) 2023 update (LF 2023) Existing Vegetation Height (EVH) represents the average height of the dominant vegetation for a 30-m cell. EVH is produced separately for tree, shrub, and herbaceous lifeforms using training data depicting the weighted average height by species cover and Existing Vegetation Type (EVT) lifeform. Decision tree models using field reference data, lidar, and Landsat are developed separately for each lifeform, then lifeform specific height class layers are merged along with land cover into a single EVH product based on the dominant lifeform of each pixel. EVH ranges are continuous for the herbaceous lifeform category ranging from 0.1 to 1 meter with decimeter increments, 0.1 to 3 meters for shrub lifeform, and 1 to 99 meters for tree lifeform. If the height values of each lifeform exceed the continuous value range, they are binned into the appropriate maximum height class. EVH is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Cover (EVC). 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://www.landfire.gov/data/lf2023.

LANDFIRE's (LF) 2023 update (LF 2023) Existing Vegetation Height (EVH) represents the average height of the dominant vegetation for a 30-m cell. EVH is produced separately for tree, shrub, and herbaceous lifeforms using training data depicting the weighted average height by species cover and Existing Vegetation Type (EVT) lifeform. Decision tree models using field reference data, lidar, and Landsat are developed separately for each lifeform, then lifeform specific height class layers are merged along with land cover into a single EVH product based on the dominant lifeform of each pixel. EVH ranges are continuous for the herbaceous lifeform category ranging from 0.1 to 1 meter with decimeter increments, 0.1 to 3 meters for shrub lifeform, and 1 to 99 meters for tree lifeform. If the height values of each lifeform exceed the continuous value range, they are binned into the appropriate maximum height class. EVH is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Cover (EVC). 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://www.landfire.gov/data/lf2023.

LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Height (EVH) represents the average height of the dominant vegetation for a 30-m cell. EVH is produced separately for tree, shrub, and herbaceous lifeforms using training data depicting the weighted average height by species cover and Existing Vegetation Type (EVT) lifeform. Decision tree models using field reference data, lidar, and Landsat are developed separately for each lifeform, then lifeform specific height class layers are merged along with land cover into a single EVH product based on the dominant lifeform of each pixel. EVH ranges are continuous for the herbaceous lifeform category ranging from 0.1 to 1 meter with decimeter increments, 0.1 to 3 meters for shrub lifeform, and 1 to 99 meters for tree lifeform. If the height values of each lifeform exceed the continuous value range, they are binned into the appropriate maximum height class. EVH is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Cover (EVC). Urban and developed areas are derived from the National Land Cover Database (NLCD), and the latest available Microsoft Building Footprint dataset. Agricultural lands originate from the 2022 Cropland Data Layer (CDL) and the 2019 California Statewide Crop Mapping layer. Disturbance events after 2016 are accounted for by incorporating transition rulesets using LF 2022 Fuel Disturbance (FDist). LF uses EVH as an input for LF 2022 Fuel Vegetation Height (FVH).