Testing an Approach to Improving Fire Fuel Mapping by Modeling Fuel Structure and Types Based on Combined Satellite Imagery and Field Data - Final Report   [open pdf - 442KB]

"When this project was proposed, there were no good mapping tools to relate information collected on field inventory plots with remotely sensed imagery, a technique that was needed in order to produce useful wildland fuel data. The project was envisioned to develop and test an algorithm that could accomplish the mapping of key vegetation parameters to meet the needs of the fire science community in test areas of the conterminous U.S. and Alaska. Specific objectives of the project were: 1) Develop a simple, practical methodology (the k nearest neighbor or k-NN) to integrate spatial data from field sample sites and satellite image data. 2) Map several key fire fuel layers including vegetation type, canopy density, canopy height, basal area, and green biomass. 3) Calibrate and validate the data sets, and conduct the technology transfer."

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