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The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees. DATA SUMMARY: The existing vegetation height (EVH) data layer is an important input to LANDFIRE modeling efforts. Canopy height is generated separately for tree, shrub and herbaceous cover life forms using training data and a series of geospatial data layers. EVH is determined by the average height weighted by species...
The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARY: The existing vegetation type (EVT) data layer represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western Hemisphere (http://www.natureserve.org/publications/usEcologicalsystems.jsp). A terrestrial ecological system is defined as a group...
LANDFIRE disturbance data are developed to provide temporal and spatial information related to landscape change for determining vegetation transitions over time and for making subsequent updates to LANDFIRE vegetation, fuel and other data. Disturbance data include attributes associated with disturbance year, type, and severity. These data are developed through use of Landsat satellite imagery, local agency derived disturbance polygons, and other ancillary data. DATA SUMMARY: The disturbance data are developed through a multistep process. Inputs to this process include; Landsat imagery and derived NBR (normalized burn ratio) data; polygon data developed by local agencies for the LANDFIRE Refresh effort; fire data...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
The LANDFIRE vegetation layers describe the following elements of existing and potential vegetation for each LANDFIRE mapping zone: environmental site potentials, biophysical settings, existing vegetation types, canopy cover, and vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARYThe biophysical settings (BpS) data layer represents the vegetation that may have been dominant on the landscape prior to Euro-American settlement and is based on both the current biophysical environment and an approximation of the historical disturbance regime. It is a refinement...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
LANDFIRE's (LF) 2022 update (LF 2022) 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), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
The LANDFIRE fuel data describe the composition and characteristics of both surface fuel and canopy fuel. Specific products include fire behavior fuel models, canopy bulk density (CBD), canopy base height (CBH), canopy cover (CC), canopy height (CH), and fuel loading models (FLMs). These data may be implemented within models to predict the behavior and effects of wildland fire. These data are useful for strategic fuel treatment prioritization and tactical assessment of fire behavior and effects. DATA SUMMARY: Thirteen typical surface fuel arrangements or "collections of fuel properties" (Anderson 1982) were described to serve as input for Rothermel's mathematical surface fire behavior and spread model (Rothermel...
The LANDFIRE (LF) Canadian Forest Fire Danger Rating System (CFFDRS) product depicts fuel types as an identifiable association of fuel elements of distinctive species, form, size, arrangement, and continuity. CFFDRS exhibits characteristic fire behavior under the specified burn conditions. In LF 2022 Canadian fuel models are derived from the Fuel Model Guide to Alaska Vegetation (Alaska Fuel Model Guide Task Group, 2018) and subsequent updates. The LF CFFDRS product contains the fuel models used for the Fire Behavior Prediction (FBP) system fuel type inputs. Default values assigned to the Canadian Fuel Models required to run the Prometheus fire behavior software (Prometheus, 2021) are added as attributes to the...
LANDFIRE's (LF) 2022 Forest Canopy Height (CH) describes the average height of the top of the canopy for a stand. CH is used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CH supplies information for fire behavior models, such as FARSITE (Finney 1998), that can determine the starting point of embers in the spotting model, wind reductions, and the volume of crown fuels. To create this product, plot level CH values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance Canopy Cover and CH are used as predictors of disturbed CH using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and time since...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. LF 2022 Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2013 to 2022. FDist is created from LF 2022 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Canopy Cover (CC), Canopy Height (CH), Canopy Bulk Density (CBD), Canopy Base Height (CBH),...
The LANDFIRE fuel data describe the composition and characteristics of both surface fuel and canopy fuel. Specific products include fire behavior fuel models, canopy bulk density (CBD), canopy base height (CBH), canopy cover (CC), canopy height (CH), and fuel loading models (FLMs). These data may be implemented within models to predict the behavior and effects of wildland fire. These data are useful for strategic fuel treatment prioritization and tactical assessment of fire behavior and effects. DATA SUMMARY: Thirteen typical surface fuel arrangements or "collections of fuel properties" (Anderson 1982) were described to serve as input for Rothermel's mathematical surface fire behavior and spread model (Rothermel...
Categories: Data;
Types: Downloadable;
Tags: 13,
Federal Government,
Fire Behavior Fuel Model,
Fuel Map,
GIS,
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
LANDFIRE disturbance data are developed to provide temporal and spatial information related to landscape change for determining vegetation transitions over time and for making subsequent updates to LANDFIRE vegetation, fuel and other data. Disturbance data include attributes associated with disturbance year, type, and severity. These data are developed through use of Landsat satellite imagery, local agency derived disturbance polygons, and other ancillary data. DATA SUMMARY: The disturbance data are developed through a multistep process. Inputs to this process include; Landsat imagery and derived NBR (normalized burn ratio) data; polygon data developed by local agencies for the LANDFIRE Refresh effort; fire data...
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