LANDFIRE - Environmental Site Potential (LANDFIRE.US_130ESP)
Dates
Publication Date
2010-01-01
Citation
Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey, 20100101, LANDFIRE.US_130ESP: Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey: Sioux Falls, SD, http://landfire.cr.usgs.gov/viewer/, http://www.landfire.gov.
Summary
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 SUMMARY: The environmental site potential (ESP) data layer represents the vegetation that could be supported at a given site based on the biophysical environment. Map units are named according to NatureServe's Ecological Systems classification, which is a nationally consistent set of mid-scale ecological [...]
Summary
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 SUMMARY: The environmental site potential (ESP) data layer represents the vegetation that could be supported at a given site based on the biophysical environment. Map units are named according to NatureServe's Ecological Systems classification, which is a nationally consistent set of mid-scale ecological units (Comer and others 2003). Usage of these classification units to describe environmental site potential, however, differs from the original intent of Ecological Systems as units of existing vegetation. As used in LANDFIRE, map unit names represent the natural plant communities that would become established at late or climax stages of successional development in the absence of disturbance. They reflect the current climate and physical environment, as well as the competitive potential of native plant species. The ESP layer is similar in concept to other approaches to classifying potential vegetation in the western United States, including habitat types (for example, Daubenmire 1968 and Pfister and others 1977) and plant associations (for example, Henderson and others 1989). It is important to note that ESP is an abstract concept and represents neither current nor historical vegetation. To create the ESP data layer, we first assign field plots to one of the ESP map unit classes. Go to http://www.landfire.gov/participate_acknowledgements.php for more information regarding contributors of field plot data. Assignments are based on presence and abundance of indicator plant species recorded on the plots and on the ecological amplitude and competitive potential of these species. We then intersect plot locations with a series of 30-meter spatially explicit gradient layers. Most of the gradient layers used in the predictive modeling of ESP are derived using the WX-BGC simulation model (Keane and Holsinger, in preparation; Keane and others 2002). WX-BGC simulations are based largely on spatially extrapolated weather data from DAYMET (Thornton and others 1997; Thornton and Running 1999; http://www.daymet.org/ ) and on soils data in STATSGO (NRCS 1994). Additional indirect gradient layers, such as elevation, slope, and indices of topographic position, are also used. We use data from plot locations to develop predictive classification tree models, using See5 data mining software (Quinlan 1993; Rulequest Research 1997), for each LANDFIRE map zone. These decision trees are applied spatially to predict the ESP for every pixel across the landscape. Finally, ESP pixel values are, in some cases, modified based on a comparison with the LANDFIRE existing vegetation type (EVT) layer created with the use of 30-meter Landsat ETM satellite imagery. We make such modifications only in non-vegetated areas (such as water, rock, snow, or ice) and where information in the EVT layer clearly enables a better depiction of the environmental site potential concept. Although the ESP data layer is intended to represent current site potential, the actual time period for this data set is variable. The weather data used in DAYMET were compiled from 1980 to 1997. Refer to spatial metadata for date ranges of field plot data and satellite imagery for each LANDFIRE map zone. A number of changes were implemented for the LF2010 ESP product that worked with this original data. LF2010 updates to mapping EVT map units for Barren, Snow-Ice, and Water were translated to the LF2010 ESP product so those map units will coincide with the EVT. Subsequent to that, each ESP map unit was stratified spatially two different ways. First, each ESP map unit was stratified by LANDFIRE map zone. Second, each ESP map unit was stratified by an ESP life form classification layer that incorporated NLCD 2001 data, LF2001 EVC data, a Vegetation Change Tracker (VCT) dataset (Huang, 2010), and the National Wetlands Inventory (NWI) data. Each layer was leveraged against each other to determine areas of stable Sparse, Upland Herb, Upland Shrub, Upland Woodland, Upland Forest, Wetland Shrub-herb, Wetland Forest, Wetland Shrub, and Wetland Herb. Areas mapped as agriculture, urban, barren, snow-ice, and water were described as Undetermined.
LANDFIRE data products are designed to facilitate national- and regional-level strategic planning and reporting of management activities. Data products are created at a 30-meter grid spatial resolution raster data set; however, the applicability of data products varies by location and specific use. Principal purposes of the data products include providing, 1) national-level, landscape-scale geospatial products to support fire and fuels management planning, and, 2) consistent fuels data to support fire planning, analysis, and budgeting to evaluate fire management alternatives. Users are advised to evaluate the data carefully for their applications.
