LANDFIRE.PM_EVCFA18

Metadata Updated: November 12, 2020

Introduction: The LANDFIRE (LF) existing vegetation layers describe the following elements of existing vegetation for each LF 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. Abstract: The MoD-FIS for the Great Basin and Southwest is based on the vegetation greenness values from the Landsat-based Normalized Difference Vegetation Index (NDVI) and its relationship to LF Existing Vegetation Cover (EVC) for the herbaceous and shrub lifeforms. The current year NDVI values are compared to a ten year minimum, average, and maximum values provided by WELD (Web-enabled Landsat data). This 30 meter resolution data is the same scale as LF EVC and was temporally analyzed for the years 2003 through 2012. From this analysis values that range from barren to sparse and then 10% cover classes for herbaceous pixels through 99% cover were found for minimum, average, and maximum NDVI. Average NDVI values were found for all shrub pixels within the analysis area. Several key components that were developed within LF Fine Fuel Dynamic (LF_FFD) are described below to outline the workings of the system:A ten year (2003-2012) average NDVI value was calculated for each pixel within the analysis area (see map in Appendix A) which stretches from west Texas to Southeast Washington State.-The pixel average NDVI was combined with LF EVC and analyzed to calculate a weighted average NDVI value for each cover class by LF map zone.-A standard deviation test was developed for the average of all the map zones within the analysis area (14 map zones); whereas map zones whose weighted average value by cover class that was not within one standard deviation to the over-all average the zone was omitted as an outlier for that cover class (see relationship Appendix A).-A median value was then calculated for the accepted map zones values from the standard deviation test.-The median value was then used in a regression model from which the resulting equation is applied to NDVI to arrive at a cover class. That percent cover is then Re-classed through LF cover classifications to determine the NDVI predicted herbaceous and shrub mapping by cover class.-FBFM40 fuel models were developed for the NDVI predicted increase and/or decrease in herbaceous fuel cover.-The fuel rulesets for change in fuel model by predicted herbaceous cover were developed in grid format for the 10 year average, ten year maximum, and the year 2012 for testing.-Current year NDVI values are mapped by these cover and fuel model rules to adjust the amount of burnable fine fuel available across the analysis area on an annual basis.Shrub cover mapping-Shrubs mapping was conducted using the 10 year average NDVI rather than current year NDVI so change from year to year in the shrub lifeform will not be apparent.-10 to 19% shrub cover was added to the herbaceous lifeform cover class-With such sparse shrubs per pixel it was felt that if the reflectance picked up significant vegetation it would be herbaceous and that herbaceous vegetation would determine the fire behavior not the shrubs within those pixels.-Since NDVI is not zone specific seam lines that had previously existed in the LF data do not exist in this product.Barren and Sparse-The average NDVI linear model is used to determine the breakpoints for Barren and Sparse and percent cover.-Sparse breakpoints are at 0.1 to 9% cover and is given a burnable fuel model (GR1). Areas with 0% cover are Barren (had No vegetation growth within 10 year stack)The provisional MoD-FIS existing vegetation cover (PM_EVC) data layer depicts percent canopy cover by life form, and is an important input to other LF 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 () 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. 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). Visit existing vegetation cover for more information.

Access & Use Information

License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Date February 1, 2007
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Reference Date(s) June 30, 2018 (publication)
Frequency Of Update continual

Metadata Source

Harvested from DOI Open Data

Additional Metadata

Resource Type Dataset
Metadata Date February 1, 2007
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Reference Date(s) June 30, 2018 (publication)
Responsible Party Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey (Point of Contact)
Contact Email
Guid
Access Constraints Use Constraints: Although LANDFIRE products are delivered as 30-meter pixels, they should not be used at the individual pixel level or on small groups of pixels. LANDFIRE products were designed to support 1) national (all states) strategic planning, 2) regional (single large states or groups of smaller states), and 3) strategic/tactical planning for large sub-regional landscapes and Fire Management Units (FMUs) (such as significant portions of states or multiple federal administrative entities). The applicability of LANDFIRE products to support fire and land management planning on smaller areas will vary by product, location, and specific use. Further investigation by local and regional experts should be conducted to inform decisions regarding local applicability. However, it is the responsibility of the local user, using LANDFIRE metadata and local knowledge, to determine if and/or how LANDFIRE can be used for particular areas of interest. LANDFIRE products are not intended to replace local products, but rather serve as a back-up by providing wall-to-wall cross-boundary products. It is the responsibility of the user to be familiar with the value, assumptions, and limitations of LANDFIRE products. Managers and planners must evaluate LANDFIRE data according to the scale and requirements specific to their needs., Access Constraints: None
Bbox East Long -98.671
Bbox North Lat 37.998
Bbox South Lat 28.901
Bbox West Long -118.432
Coupled Resource
Frequency Of Update continual
Licence This product is reproduced from geospatial information prepared by the U.S. Department of Agriculture, Forest Service and USGS EROS. By removing the contents of this package or taking receipt of these files via electronic file transfer methods, you understand that the data stored on this media is in draft condition. Represented features may not be in an accurate geographic location. The Forest Service and USGS EROS make no expressed or implied warranty, including warranty of merchantability and fitness, with respect to the character, function, or capabilities of the data or their appropriateness for any user's purposes. The Forest Service and USGS EROS reserve the right to correct, update, modify, or replace this geospatial information without notification.
Metadata Language
Metadata Type geospatial
Progress completed
Spatial Data Service Type
Spatial Reference System
Spatial Harvester True

Didn't find what you're looking for? Suggest a dataset here.