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  1. Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico

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    Author(s): Robert E. Keane; Scott A. Mincemoyer; Kirsten M. Schmidt; Donald G. Long; Janice L. Garner
    Date: 2000
    Source: Gen. Tech. Rep. RMRS-GTR-46. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 126 p.
    Publication Series: General Technical Report (GTR)
    Station: Rocky Mountain Research Station
    DOI: https://doi.org/10.2737/RMRS-GTR-46
    PDF: View PDF  (490.0 KB)

    Description

    (Please note: This PDF is part of a CD-ROM package only and was not printed on paper.) Fuels and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Gila National Forest in New Mexico. Satellite imagery, terrain modeling, and biophysical simulation were used to create the three vegetation spatial data layers of biophysical settings, cover type, and structural stage. Fire behavior fuel models and vegetation characteristics needed by FARSITE were assigned to combinations of categories on maps developed from sampled field data and also from estimates by local fire managers, ecologists, and resource specialists. FARSITE fuels maps will be used to simulate growth of fires on the Gila National Forest aiding managers in the planning and allocation of resources for managing fire. An extensive accuracy assessment of all maps indicated surface and crown fuels layers are about 30 to 40 percent accurate. This methodology was designed to be replicated for other areas of the western United States.

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    Citation

    Keane, Robert E.; Mincemoyer, Scott A.; Schmidt, Kirsten M.; Long, Donald G.; Garner, Janice L. 2000. Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico. Gen. Tech. Rep. RMRS-GTR-46. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 126 p.

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    Keywords

    Gila National Forest, FARSITE modeling, fuels mapping, fire behavior fuel model, GIS, terrain modeling, satellite imagery classification, vegetation mapping, biophysical classification

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