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

Autor: Dickinson, Matthew B., Butler, Bret W., Hudak, Andrew T., Bright, Benjamin C., Kremens, Robert L., Klauberg, Carine
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Zdroj: International Journal of Wildland Fire; 2019, Vol. 28 Issue 3, p230-236, 7p
Abstrakt: Remotely sensed radiation, attractive for its spatial and temporal coverage, offers a means of inferring energy deposition in fires (e.g. on soils, fuels 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 ~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. Using log–log scaling to reveal downward bias, incident energy was positively related to FRED from nadir radiometers (R 2 = 0.47) and WASP (R 2 = 0.50). As a demonstration of how this result could be used to describe 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. On average, larger-diameter stems were expected to be killed in the forested than in the non-forested sites. Though the approach appears promising, challenges remain for remote and in situ measurement. We infer energy incident on in situ (in-flame) sensors from energy measured using nadir (overhead) sensors borne on towers and a piloted aircraft for surface fires in non-forested sites and longleaf pine (Pinus palustris) savanna. We predict turkey oak (Quercus laevis) stem mortality from inferred incident energy. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index