| Collection of field data is the most important task in this research effort. 3024 field locations have been GPS surveyed, digitally photographed and assigned values for fuel loading, according to NFFL fire models. Most remotely sensed products, such as aerial photographs and satellite images are suitable only for very coarse level extraction of fuel types because the surface fuels, which govern the spread of most timber stand fires, are often obscured from view by the forest canopy (Elvidge 1988, Lachowski et al, 1995). However, knowledge of the forest canopy can provide some insight into surface fuels, especially when extensive ground truthing is conducted and used in concert with existing GIS layers. Also, the most important FARSITE layer, the fire behavior fuel model (FBFM) layer, is based more on expected fire behavior for a stand than characterization of fuel loadings (Anderson 1982, Bradshaw 1978, Burgan 1988). Therefore, in-the-field collaboration with experienced RIDEM foresters is necessary to assist in assigning values to the FBFM layer. Finally, the characterization of FBFM is very difficult to extract from remotely sensed imagery alone. This is due to the fact that wildland fire propagates mainly through fine and dead fuel classes (grasses, pine needles and fine woody materials less than 1" in diameter (Fahnestock, 1970) and fuel loadings for these fuel classes are intrinsically difficult to extract from remotely sensed imagery in timber stands, since dead fuels do not have spectral signatures that can be correlated with tree species or forest community types (Jensen 1986, Jensen and Cowen 1999 ). Given the limitations of remote sensing data to accurately reflect fuel loading, field reference data is used as the primary method to assign fuel classes and assess the accuracy of fuel-type classification products. Landsat remote sensing data is used as a link to impute values for un-sampled locations in the study area. Reference data was collected during the summer and fall of 2002 and 2003 at locations throughout the state. A Garmin etrex Global Positioning System (GPS) unit was used to collect reference points while a Canon Field Imaging System (FIS) was used to capture photographs of various land-cover types at the ground-truthing sites. These data form the core of a virtual field reference database (VFRDB), which allows on-the-ground field observations to be rapidly associated with remote sensing data. Additionally, three RIDEM forestry personnel havee been trained in GPS/FIS use aided in the collection of VFRDB data. |
Landsat imagery alone cannot reliably delineate forest community types to the level of detail outlined in the RINHS forest community survey.
However, Landsat imagery serves as a valuable tool in assessing fuel load when used in concert with VFRDB data.
Some Landsat Limitations:
Given: -Tree canopy size is generally less than 30m in diameter
-Individual tree species produce distinct spectral signatures
-Forest community types are made up of different species of
trees making signature extraction difficult to impossible.
- Oak trees are not mutually exclusive to 1 forest community
type
and...
-RI Forest community types cannot reliably be linked to
fuel loadings necessary to produce a fire danger map.
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