Land managers need cost-effective methods for mapping and characterizing fire fuels quickly and accurately. The advent of sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite and gradient modeling for mapping fuel layers for fire behavior modeling within FARSITE and FLAMMAP. Empirical models, based upon field data and spectral information from an ASTER image, were employed to test the efficacy of ASTER for mapping and characterizing canopy closure and crown bulk density. Surface fuel models (NFFL 1-13) were mapped using a classification tree based upon three gradient layers; potential vegetation type, cover type, and structural stage.