LANDFIRE.AK_120CBH

Metadata Updated: November 12, 2020

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: Canopy base height (CBH) describes the lowest point in a stand where there is sufficient available fuel (=> .25 in dia.) to propagate fire vertically through the canopy. Specifically, CBH is defined as the lowest point at which the canopy bulk density is >= 0.012 kg m-3. A spatially explicit map of canopy base height supplies information used in fire behavior models such as FARSITE (Finney 1998) to determine the point at which a surface fire will transition to a crown fire. It should be noted that LANDFIRE layers will not include canopy characteristics in fuel types where the tree canopy is considered a part of the surface fuel and the surface fire behavior fuel model is chosen to reflect these conditions. This is because LANDFIRE assumes that the potential burnable biomass in the shorter tree canopies has been accounted for in the surface fuel model parameters. For example, maps of areas dominated by young or short conifer stands where the trees are represented by a shrub type fuel model will not include canopy characteristics. The CBH mapping process began by deriving field referenced estimates of canopy characteristics through LFRDB plot analysis. Approximately 50,000 plots were acquired throughout the U.S. for estimating CBH. Utilizing these plots, field referenced CBH values were calculated for each plot using the canopy fuel estimation software FuelCalc (Reinhardt et al. 2006b). Go to http://www.landfire.gov/participate_acknowledgements.php for more information regarding contributors of field plot data. This process of deriving field referenced estimates for CBH was employed to create a training data set with the aim of modeling CBH values. Statistical analysis of plot variables indicated that Existing Vegetation Type (EVT) and Existing Vegetation Height (EVH) demonstrated some influence on CBH, with Existing Vegetation Cover (EVC) affecting CBH values within certain EVTs. Unfortunately, these relationships were not statistically strong enough to model CBH and alternate approaches were explored. The only relationship that was statistically significant was that related to juniper EVTs. From this analysis, juniper EVTs consistently showed similar CBH outputs and were hardwired to a value of 4.0 mx10. Using the information gleaned from the statistical analysis it was decided to map CBH values using an average look up table (LUT) approach based on plot level combinations of EVT, EVC, and EVH. To assign averages using these variables, various grouping combinations of EVT, EVC, and EVH were tested to determine which would map CBH values most logically. For each grouping, a set of look-up tables was calculated enabling CBH to be mapped with the Fuels Change Mapping Tool, or ToFu Delta. These maps were analyzed, peer reviewed and tested to determine which performed best. In the process of developing and testing these grouping strategies it was realized that not enough plot data was available to account for all EVT, EVH and EVC combinations. To account for these missing values and fill in data gaps, a 'pyramid approach' was adopted for mapping CBH that would allow for a value to be assigned at some level. The basic premise of this approach was to map assignments with the most detailed data available and fill in behind it with coarser level aggregate values to account for all combinations. To accomplish these aggregate assignments, aggregate values for EVTs were derived at two coarser levels, existing vegetation groups (EVG) and existing vegetation systems (EVS). Each aggregate was more comprehensive than the previous and comprised of subgroups of cover and height combinations (ECHGs). Existing vegetation cover height groups (ECHGs) were derived by grouping CBH values into aggregate groups of EVT, EVG, and EVS. Each aggregate group was split into subgroups of the Existing Vegetation Height (EVH) classes. Lastly, the subgroups were split into two more groups where the greatest average difference occurred between an upper and lower range of forested canopy cover and the difference was greater than or equal to two feet CBH. Each ECHG was assigned an average CBH from the plots - the standard deviation of the plots that meet the requirements of EVT, EVG, or EVS and EVH and EVC. Prior to implementing this aggregate grouping strategy certain data thresholds had to be met in an attempt to ensure that a representative data set was being utilized. For each group (or subset) a data threshold greater than or equal to five plots per ECHG had to be reached before it could be implemented. Subsequently all outliers greater than or equal to three standard deviations from the mean were removed prior to computing a CBH value. The CBH data represented in the resultant layer are continuous from 0 to 9.9 meters (to the nearest 0.1 meter). Some stands dominated by broadleaf species which typically do not permit initiation of crown fire (e.g. Populus spp.) are coded with a CBH of 10 meters. Since crown fire is rarely observed in most hardwood stands, the highest CBH value possible was used to prevent false simulation of crown fire in these areas. Similarly, all non-forest values, including herbaceous, and shrub systems and non-burnable types such as urban, barren, snow and ice and agriculture, were coded as 0. Finally, certain types of agriculture that are deemed burnable were assigned a value by ToFuDelta based on region and vegetation type. LANDFIRE 2010 (lf_1.2.0) and Refresh 2008 (lf_1.1.0) used 2001 data as a launching point to incorporate disturbance and its severity, both managed and natural, which occurred on the landscape after 2001. Specific examples of disturbance are: fire, vegetation management, weather, and insect and disease. Disturbance data used in the updating 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. For details on methods, see Process Description for and LANDFIRE 2010 (lf_1.2.0) and Refresh 2008 (lf_1.1.0).

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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.

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Dates

Metadata Date February 1, 2007
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Reference Date(s) January 1, 2010 (publication)
Frequency Of Update notPlanned

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) January 1, 2010 (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 -138.75803269007818
Bbox North Lat 71.14926911648406
Bbox South Lat 50.824773478534226
Bbox West Long -179.8299135763675
Coupled Resource
Frequency Of Update notPlanned
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

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