B034-0008
Inferring energy incident on sensors in low-intensity surface fires from remotely-sensed radiation and using it to predict tree stem injury

Wednesday, 9 December 2020
Poster
Matthew B Dickinson, USDA Forest Service, Delaware, OH, United States, Bret Butler, Missoula Fire Sciences Laboratory, Missoula, MT, United States, Andrew T Hudak, USDA Forest Service, Rocky Mountain Research Station, Moscow, ID, United States, Benjamin C Bright, Rocky Mountain Research Station, Moscow, ID, United States, Robert Kremens, Rochester Institute of Techno, Carlson Center for Imaging Science, Rochester, NY, United States and Carine Klauberg Silva, Rocky Mountain Research Station Moscow, Moscow, ID, United States
Abstract:
Remotely-sensed radiation measurements, attractive for their spatial coverage, offer a means of inferring energy deposition in fires (e.g., on soils, fuel particles, and tree stems) but coordinated remote and in-situ (in flame) measurements are lacking. We relate remotely-sensed measurements of fire radiative energy density (FRED) from nadir (overhead) radiometers on towers and the Wildfire Airborne Sensor Program (WASP) infrared camera on a piloted, fixed-wing aircraft to energy incident on in situ, horizontally-oriented, wide-angle total-flux sensors positioned at ~0.5 m above ground level. Measurements were obtained in non-forested herbaceous and shrub dominated sites and in (forested) longleaf pine (Pinus palustris Miller) savanna. Incident energy was strongly related to nadir radiometer FRED (R2 = 0.79) and moderately related to WASP FRED (R2 = 0.50). As a demonstration of how this approach could be applied to ecological effects, we predict stem injury for turkey oak (Quercus laevis Walter), a common tree species at our study site, using incident energy inferred from remotely-sensed FRED. Larger diameter stems were expected to be killed in the forested than in the non-forested sites. Measurement challenges remain for remote and in-situ measurements including further consideration of error associated with inferring energy incident on tree stems.