LANDFIRE

In response to a need for a national evaluation of the spatial distribution of fire risk, the USDA Forest Service developed a partnership with 4 other agencies to develop LANDFIRE ( http://www.landfire.gov/index.html). The goal of LANDFIRE is to identify areas at risk due to accumulation of hazardous fuel for the purpose of prioritizing hazardous fuel reduction projects and improving hazardous fuel treatment coordination between agencies. The program is designed to produce landscape-scale maps and data describing vegetation, fire, and fuel characteristics across the United States (at a 30-m grid resolution) (Keane and others 2004, Rollins and others 2002, Rollins and others 2004, Schmidt and others 2002). LANDFIRE is providing many of the raw materials that will be necessary to produce an estimate of fire risk. Although it is not yet in general use or publicly available, it is important to discuss it here because of the key role LANDFIRE will play in fire risk assessment over the next decade.

Fig. 1 - A diagram of the Landscape
Ecosystem Inventory System

The spatial distribution of potential vegetation, existing vegetation, canopy height, and canopy cover is mapped using gradient-based field inventories coupled with gradient modeling, remote sensing, ecosystem simulation, and statistical analyses. Biophysical gradient maps have been created containing 38 geographical information system (GIS) layers describing the direct and indirect gradients affecting the distribution of vegetation and fire regimes. The vegetation of the continental United States is divided into approximately 500 biophysical units, based on plant composition and the Ecological Systems categorization ( http://www.natureserve.org/). Each successional stage of each biophysical type is separately tracked. Fuel models are assigned to each mapping region, producing fuel maps for fire behavior models, canopy fuel projections, and fuel characterization classes. Crown bulk density and height to crown base are calculated at the plot level from tree lists.

Inputs consist of coarse-scale, 1-km² resolution, spatial data layers. These include potential natural vegetation type, current cover type, site characteristics (such as soils, climate, and topography), historical natural fire regime (fire frequency and severity), and Fire Regime Current Condition Class (layer depicting the degree of departure from historical fire regimes). There are three additional databases that are used as input:

1. National Fire Occurrence, Federal and non-Federal fire occurrences from 1986 to 1996
2. Potential Fire Characteristics— the number of days of high or extreme fire danger calculated from 8 years of historical National Fire Danger Rating System (NFDRS) data
3. Wildland Fire Risk to Flammable Structures—the potential risk of wildland fire burning flammable structures based on an integration of population density, fuel, and weather spatial data

Landscape characteristics that are used to determine fire occurrence and behavior include height to crown base, crown bulk density, fuel loadings, cover type, percent cover, height for each of the forest, shrub, and herbaceous layer, and an estimate of the departure from reference normal fire regime condition class. The interaction between these characteristics and fire probability is estimated by using a suite of computer models, WXFIRE, BIOME-BGC, LANDSUMv4, FARSITE, and HRVStat, discussed in the next section.

LANDFIRE produces three fire regime maps:

1. simulated historical fire frequency and severity
2. fire regime condition class (FRCC)
3. indices of departure from reference conditions

Fig. 2 - LANDFIRE National Fire
Regime Condition Class Map

These tools are used for determining the degree to which current landscape conditions have departed from historical reference condition vegetation, fuel, and disturbance regimes. Figure 2 shows an example map of fire regime condition classes produced by LANDFIRE. An example map of reference fire regimes is shown in Figure 3.

The data layers being produced by LANDFIRE will provide basic information from which a risk assessment can be calculated. However, there are drawbacks to this system. LANDFIRE'S classifications of fire conditions may be too coarse. The calculation of probabilities may require data on a continuous scale. Further, it is not clear whether this data is sufficient to predict the average likelihood of a fire at a location or the distribution probabilities of fires of different sizes and intensities. The probability of a worst case scenario would be difficult to estimate from LANDFIRE'S products.

Fig. 3 - LANDFIRE rapid assessment reference

Because the past condition and fire susceptibility had much to do with past climate, it is unclear whether LANDFIRE will correctly predict the relationship between vegetation, fuel loadings, and fire that will be shaped by future climates. LANDFIRE places less emphasis on the importance of the heterogeneity of types of fire and the key differences among these types, such as crown fires vs. ground fires. LANDFIRE focuses on classes that are relevant to management and current vegetation classifications. There may be advantages to having the flexibility to make changes in these classifications. Natural variability in landscape and fire characteristics, and their influence on fire (and the uncertainty with which predictions can be based on these characteristics) is not treated implicitly within the system.