LANDFIRE - Forest Canopy Base Height (LANDFIRE.US_130CBH)
Dates
Publication Date
2010-01-01
Citation
Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey, 20100101, LANDFIRE.US_130CBH: Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological: Sioux Falls, SD, http://www.landfire.gov, http://landfire.cr.usgs.gov/viewer/.
Summary
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: 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. This critical canopy [...]
Summary
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: 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. This critical canopy base height (CBH) describes the lowest point in a stand where there is sufficient available fuel (0.25 in dia.) to propagate fire vertically through the canopy. Specifically, CBH is defined as the lowest point at which the canopy bulk density is .012 kg m-3. 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 70,000 plots(Go to http://www.landfire.gov/participate_acknowledgements.phpfor more information regarding contributors of field plot data.) 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 in Forest Vegetation Simulator (http://www.fs.fed.us/fmsc/fvs/). This process of deriving field referenced estimates for CBH was employed to create a training data set to model 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. To model these relationshipsa regression tree analysis (RTA) approach was implemented in R for each EVT. (Juniper EVTs consistently showed similar CBH outputs and were given a constant value of 4.0 mx10.)It was determined that there was not enough plot data to account for all EVC, EVH, and EVT combinations during the CBH RTA development. A filling approach was implemented to account for data gaps. The basic premise of this approach was to map assignments with the most detailed data available and fill in gaps with coarser aggregates to account for all combinations. Aggregate values for EVTs were derived at two coarser levels, existing vegetation groups (EVG) and existing vegetation systems (EVS). Each vegetation group was more generalized than the previous grouping. The resultant maps were analyzed, peer reviewed and tested to assess performance against previous LANDFIRE versions. For each vegetation grouping (or subset) a data threshold greater than or equal to thirty plots per EVT/EVG/EVS had to be reached before the RTA was implemented. All outliers greater than or equal to two standard deviations from the mean were removed prior to computing a CBH RTA 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 and urban vegetation that are deemed burnable were assigned a constant value by LFTFC rule-sets based on region and vegetation type.LANDFIRE 2012 (lf_1.3.0) and used LANDFIRE 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 after 2010. 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 disturbance occurred.
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.