Laboratory experiments to estimate interception of infrared radiation by tree canopies
Bill J. Mathews A , Eva K. Strand A E , Alistair M. S. Smith A , Andrew T. Hudak B , Matthew , B. Dickinson C and Robert L. Kremens D
+ Author Affiliations
- Author Affiliations
A Forest, Rangeland and Fire Sciences, College of Natural Resources, 875 Perimeter Drive MS 1135, University of Idaho, Moscow, ID 83844, USA.
B Rocky Mountain Research Station, USDA Forest Service, 1221 South Main Street, Moscow, ID 83843, USA.
C US Forest Service Northern Research Station, 359 Main Road, Delaware, OH 43015, USA.
D Rochester Institute of Technology, Center for Imaging Science, 54 Lomb Memorial Drive, Rochester, NY 14623, USA.
E Corresponding author. Email: evas@uidaho.edu
International Journal of Wildland Fire 25(9) 1009-1014 https://doi.org/10.1071/WF16007
Submitted: 14 January 2016 Accepted: 27 June 2016 Published: 1 August 2016
Abstract
Estimates of biomass-burning in wildfires or prescribed fires are needed to account for the production of trace gases and aerosols that enter the atmosphere during combustion. Research has demonstrated that the biomass consumption rate is linearly related to fire radiative power (FRP), and that total biomass consumed is linearly related to fire radiative energy (FRE). Measurement of these is biased by certain characteristics of a forest canopy, such as foliar moisture content and tree canopy cover. Laboratory experiments were conducted to assess the influence of canopy cover on the FRP observed from an overhead sensor (e.g. an aircraft or satellite). A range of canopy cover from 0 to 90% and two classes of canopy (non-transpiring living and desiccated branches) were used in the experiments. Experiments suggest that in cases of complete or nearly complete canopy closure, fires obscured by the canopy may be below the detection threshold of above-canopy FRP sensors. Results from this research will reduce uncertainties in estimates of biomass consumption in surface fires burning under forest canopies.
Additional keywords: biomass combustion, fire intensity, FRE, FRP, fuel consumption, remote sensing.
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