Quantitative Comparison of Spectral Indices and Transformations of Multi-Resolution Remotely Sensed Data Using Ground Measurements: Implications for Fire Severity Modeling

摘要

The number and severity of wildfires in the western United States since the late 1990s has focused research efforts and subsequent management actions on assessing fire hazards using remote sensing imagery and processing techniques. A major factor that determines fire hazard is live fuel moisture (LFM) content. The changes in live fuel moisture are dynamic, and fuel conditions modify fire behavior and fire danger ratings in shrublands and forested ecosystems. We investigated the empirical relationship between field-measured LFM and remotely-sensed greenness and moisture measures from the Airborne Visible/Infrared Imaging spectrometer (AVIRIS) and the Moderate Resolution Imaging Spectrometer (MODIS). Key goals were to assess the nature of these relationships as they varied between sensors, across sites, and across years. Live Fuel Moisture (LFM) is a strong determinant governing ignition success and fire intensity, particularly in shrublands where a majority of the biomass available for combustion is living. This information can be useful both for prescribed fire planning and for predicting fire intensity and crown fire initiation of wildfires.