Assessment of Pre- and Post-Fire Fuel Availability for Wildfire Management Based on L-Band Polarimetric SAR

Many communities coexist with wildfires that lead to loss of lives, property, and ecosystem services. Remote sensing tools can aid disaster response and post-event assessment, offering fire agencies opportunities for additional surveillance with radar, an all-weather instrument that can image day or night. The Station (2009) and Bobcat (2020) Fires are the two largest fires in Los Angeles County history, each burning over 100,000 acres. These areas are imaged with NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar L-band instrument. We test whether polarimetric radar can detect fire scars, burn severity, and different fuel types through its sensitivity to different scattering mechanisms. Polarimetric SAR products are moved into geographic information system-friendly formats, and in lieu of available field measurements are analyzed alongside agency data showing fire perimeters, burn progression outlines, and soil burn severity. We find that the HV polarization returns and the primary scattering mechanism, quantified through the Cloude-Pottier decomposition, are the most sensitive parameters. Higher HV values pre-fire correspond well to areas of moderate and high soil burn severity, and the pattern of fire progression follows higher HV to some extent. Using an HV difference threshold of 1.5 dB, the Bobcat burn scar is identified at 0.70 accuracy when compared with the published fire perimeter. Alpha 1 Angle can also demonstrate sensitivity to soil burn severity pre- and post-fire, showing vegetation types with increased surface scattering post-fire, which can be used to map burn scars and track recovery by vegetation type. Wildfires around the world lead to loss of lives, property, and environmental benefits. The increasing usage of satellite imagery to aid disaster response and monitoring offers fire agencies an opportunity for additional surveillance. Radar instruments can see through smoke, haze, and clouds during the day or night, which is especially relevant when cloud cover or weather conditions block traditional visual surveys of damage. The Station (2009) and Bobcat (2020) Fires are the two largest fires in Los Angeles County history, each burning over 100,000 acres. These areas were imaged with NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar, an airborne sensor with high quality measurements and detailed resolution. For these neighboring fires, we investigate the usage of radar remote sensing to detect fire scars, burn severity, and different fuel (vegetation) types. These fire characteristics are observed using a variety of polarimetric radar products. These products are analyzed alongside agency data such as burned area outlines, burn progression outlines, and burn severity. We demonstrate the advantages of using radar data sets to understand the vegetation which contributed to the fires and to monitor post-fire recovery. Polarimetric radar products can offer supplementary information on available fuels, past fire scars, and vegetation recovery Alpha angle from eigenvectors is able to separate burn severity classes, while HV polarization better identifies burned from unburned area Long-term monitoring with a similar L-band instrument can be achieved once the upcoming NASA-ISRO Synthetic Aperture Radar sensor is fully operational