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LANDFIRE Existing Vegetation Cover
The Existing Vegetation Cover (EVC) product depicts percent canopy cover by life form and is an important input to other LANDFIRE mapping efforts. EVC is generated separately for tree, shrub and herbaceous life forms using training data and a series of geospatial predictor layers. Plots from the Forest Inventory and Analysis (FIA) program of USDA Forest Service (https://www.fia.fs.usda.gov/) were used as the training data for tree canopy cover mapping, with canopy cover of the plots estimated from stem-mapped tree data and calibrated with line intercept field measurements of canopy cover (Toney and others 2009). Shrub and herbaceous canopy cover training data were also derived from plot-level, ground-based visual assessments. More information regarding contributors of field plot data can be found at http://www.landfire.gov/participate_acknowledgements.php. Regression tree models were developed separately for each life form using the training data and a combination of multitemporal Landsat data, terrain data from a digital elevation model, and biophysical gradient data layers. Cubist software was used for modeling. The derived regression tree equations were then applied to the geospatial predictor data to create 30-m resolution, life form specific data layers (i.e., separate data layers are generated for tree, shrub and herbaceous vegetation cover). Each of the derived data layers (tree, shrub, herbaceous) has a potential range of 0-100 percent canopy cover. Tree, shrub and herbaceous values were binned into discrete classes (up to 10 bins at 10 percent intervals for tree, shrub and herbaceous canopy cover). The final EVC layer was evaluated and rectified through a series of QA/QC measures to ensure that the life form of the canopy cover code matched the life form of the LANDFIRE Existing Vegetation Type (EVT) layer. EVC is used in the development of subsequent LANDFIRE data layers. LF 2014 (lf_1.4.0) used modified LF 2010 (lf_1.2.0) data as a launching point to incorporate disturbance and its severity, both managed and natural, which occurred on the landscape 2013 and 2014. Specific examples of disturbance are: fire, vegetation management, weather, and insect and disease. The final disturbance data used in LANDFIRE is the result of several efforts that include data derived in part from remotely sensed land change methods, Monitoring Trends in Burn Severity (MTBS), and the LANDFIRE Events data call. Vegetation growth was modeled where both disturbance and non-disturbance occurs. Urban, agriculture, and wetlands were refined to reflect a 2012 landscape using the National Conservation Easement Database, National Wetlands Inventory (NWI), and Common Land Unit database (CLU) data.
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LANDFIRE Existing Vegetation Cover
공공데이터포털
The Existing Vegetation Cover (EVC) product depicts percent canopy cover by life form and is an important input to other LANDFIRE mapping efforts. EVC is generated separately for tree, shrub and herbaceous life forms using training data and a series of geospatial predictor layers. Plots from the Forest Inventory and Analysis (FIA) program of USDA Forest Service (https://www.fia.fs.usda.gov/) were used as the training data for tree canopy cover mapping, with canopy cover of the plots estimated from stem-mapped tree data and calibrated with line intercept field measurements of canopy cover (Toney and others 2009). Shrub and herbaceous canopy cover training data were also derived from plot-level, ground-based visual assessments. More information regarding contributors of field plot data can be found at http://www.landfire.gov/participate_acknowledgements.php. Regression tree models were developed separately for each life form using the training data and a combination of multitemporal Landsat data, terrain data from a digital elevation model, and biophysical gradient data layers. Cubist software was used for modeling. The derived regression tree equations were then applied to the geospatial predictor data to create 30-m resolution, life form specific data layers (i.e., separate data layers are generated for tree, shrub and herbaceous vegetation cover). Each of the derived data layers (tree, shrub, herbaceous) has a potential range of 0-100 percent canopy cover. Tree, shrub and herbaceous values were binned into discrete classes (up to 10 bins at 10 percent intervals for tree, shrub and herbaceous canopy cover). The final EVC layer was evaluated and rectified through a series of QA/QC measures to ensure that the life form of the canopy cover code matched the life form of the LANDFIRE Existing Vegetation Type (EVT) layer. EVC is used in the development of subsequent LANDFIRE data layers. LF 2014 (lf_1.4.0) used modified LF 2010 (lf_1.2.0) data as a launching point to incorporate disturbance and its severity, both managed and natural, which occurred on the landscape 2013 and 2014. Specific examples of disturbance are: fire, vegetation management, weather, and insect and disease. The final disturbance data used in LANDFIRE is the result of several efforts that include data derived in part from remotely sensed land change methods, Monitoring Trends in Burn Severity (MTBS), and the LANDFIRE Events data call. Vegetation growth was modeled where both disturbance and non-disturbance occurs. Urban, agriculture, and wetlands were refined to reflect a 2012 landscape using the National Conservation Easement Database, National Wetlands Inventory (NWI), and Common Land Unit database (CLU) data.
LANDFIRE Existing Vegetation Cover
공공데이터포털
The Existing Vegetation Cover (EVC) product depicts percent canopy cover by life form and is an important input to other LANDFIRE mapping efforts. EVC is generated separately for tree, shrub and herbaceous life forms using training data and a series of geospatial predictor layers. Plots from the Forest Inventory and Analysis (FIA) program of USDA Forest Service (https://www.fia.fs.usda.gov/) were used as the training data for tree canopy cover mapping, with canopy cover of the plots estimated from stem-mapped tree data and calibrated with line intercept field measurements of canopy cover (Toney and others 2009). Shrub and herbaceous canopy cover training data were also derived from plot-level, ground-based visual assessments. More information regarding contributors of field plot data can be found at http://www.landfire.gov/participate_acknowledgements.php. Regression tree models were developed separately for each life form using the training data and a combination of multitemporal Landsat data, terrain data from a digital elevation model, and biophysical gradient data layers. Cubist software was used for modeling. The derived regression tree equations were then applied to the geospatial predictor data to create 30-m resolution, life form specific data layers (i.e., separate data layers are generated for tree, shrub and herbaceous vegetation cover). Each of the derived data layers (tree, shrub, herbaceous) has a potential range of 0-100 percent canopy cover. Tree, shrub and herbaceous values were binned into discrete classes (up to 10 bins at 10 percent intervals for tree, shrub and herbaceous canopy cover). The final EVC layer was evaluated and rectified through a series of QA/QC measures to ensure that the life form of the canopy cover code matched the life form of the LANDFIRE Existing Vegetation Type (EVT) layer. EVC is used in the development of subsequent LANDFIRE data layers. LF 2014 (lf_1.4.0) used modified LF 2010 (lf_1.2.0) data as a launching point to incorporate disturbance and its severity, both managed and natural, which occurred on the landscape 2013 and 2014. Specific examples of disturbance are: fire, vegetation management, weather, and insect and disease. The final disturbance data used in LANDFIRE is the result of several efforts that include data derived in part from remotely sensed land change methods, Monitoring Trends in Burn Severity (MTBS), and the LANDFIRE Events data call. Vegetation growth was modeled where both disturbance and non-disturbance occurs. Urban, agriculture, and wetlands were refined to reflect a 2012 landscape using the National Conservation Easement Database, National Wetlands Inventory (NWI), and Common Land Unit database (CLU) data.
LANDFIRE 2022 Existing Vegetation Cover (EVC) CONUS
공공데이터포털
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 lifeform of each pixel. The EVC product is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Height (EVH). 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 EVC as an input for LF 2022 Fuel Vegetation Cover (FVC).
LANDFIRE 2022 Existing Vegetation Cover (EVC) CONUS
공공데이터포털
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 lifeform of each pixel. The EVC product is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Height (EVH). 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 EVC as an input for LF 2022 Fuel Vegetation Cover (FVC).
LANDFIRE 2022 Existing Vegetation Type (EVT) CONUS
공공데이터포털
LANDFIRE's (LF) 2022 update (LF 2022) 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) https://usnvc.org/]. See the EVT product page (https://www.landfire.gov/evt.php) 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. Urban and developed areas are derived from the National Land Cover Database (NLCD), and the latest Microsoft Building Footprint dataset. Agricultural lands originate from the 2022 Cropland Data Layer (CDL) and the 2019 California Statewide Crop Mapping layer. Burnable developed classes are identified from building footprint dataset thresholds. LF 2022 retains circa 2016 EVT labels except where shifts in urban, agriculture, and developed classes occur. While Existing Vegetation Cover (EVC) and Height (EVH) are updated using transition rulesets with ST-Sim to account for disturbances, EVT remains unchanged, therefore EVT lifeform is not synchronized to the EVC/EVH lifeform as in some previous versions. LF uses EVT as an input for LF 2022 Fuel Vegetation Type (FVT).
LANDFIRE 2022 Existing Vegetation Type (EVT) CONUS
공공데이터포털
LANDFIRE's (LF) 2022 update (LF 2022) 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) https://usnvc.org/]. See the EVT product page (https://www.landfire.gov/evt.php) 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. Urban and developed areas are derived from the National Land Cover Database (NLCD), and the latest Microsoft Building Footprint dataset. Agricultural lands originate from the 2022 Cropland Data Layer (CDL) and the 2019 California Statewide Crop Mapping layer. Burnable developed classes are identified from building footprint dataset thresholds. LF 2022 retains circa 2016 EVT labels except where shifts in urban, agriculture, and developed classes occur. While Existing Vegetation Cover (EVC) and Height (EVH) are updated using transition rulesets with ST-Sim to account for disturbances, EVT remains unchanged, therefore EVT lifeform is not synchronized to the EVC/EVH lifeform as in some previous versions. LF uses EVT as an input for LF 2022 Fuel Vegetation Type (FVT).
LANDFIRE 2023 Existing Vegetation Type (EVT) CONUS
공공데이터포털
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://www.landfire.gov/data/lf2023.
LANDFIRE 2023 Existing Vegetation Type (EVT) CONUS
공공데이터포털
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://www.landfire.gov/data/lf2023.
LANDFIRE Remap 2016 Existing Vegetation Type (EVT) CONUS
공공데이터포털
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 Remap 2016 Existing Vegetation Type (EVT) CONUS
공공데이터포털
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.