Calibration of Estimates on Direct Wildfire Emissions from Remote Sensing Data
- Authors: Ponomarev E.I.1,2, Shvetsov E.G.1, Litvintsev K.Y.3
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Affiliations:
- Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, Federal Research Center KSC SB RAS
- Joint Regional Center for Remote Sensing, Federal Research Center KSC SB RAS
- Kutateladze Institute of Thermophysics, Siberian Branch, Russian Academy of Sciences
- Issue: Vol 55, No 9 (2019)
- Pages: 1065-1072
- Section: Methods and Tools for Space Data Processing and Interpretation
- URL: https://journals.rcsi.science/0001-4338/article/view/148794
- DOI: https://doi.org/10.1134/S0001433819090408
- ID: 148794
Cite item
Abstract
This study is based on the processing of satellite imagery in the wave range 3.93–3.99 μm (Terra/Modis satellite) and numerical simulation results. It has been found for combustion conditions in Siberian forests that the observed fire radiative power (FRP) is 15% of the total fire power. Variations between 10 and 30% depend on both the fire development scenario (specific burnup rate of 0.01–0.1 kg/m2 s and fire front velocity of 0.01–0.1 m/s) and the conditions for remote imaging. Instrumental estimates for the ratio of fire areas by given intensity quantiles for Siberian forests are presented. The share of low-, medium-, and high-intensity fires is 41.2–58.9, 35.0–46.5, and 6.10–13.44% of the total area. Refined estimates of fire emissions have been obtained taking into account the amount of biomass burnt and variable burning intensity. The proposed method allows the mass of burned forest fuel materials (FFM) and direct fire emissions to be estimated quantitatively at a level 14–21% lower than the values calculated with the help of standard approaches. The estimates of direct carbon emissions in the given time interval of 2002–2016 were 83 ± 21 Tg/year on average, which is 17% lower than the value 112 ±25 Tg/year obtained with the standard method.
About the authors
E. I. Ponomarev
Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, Federal Research Center KSC SB RAS; Joint Regional Center for Remote Sensing, Federal Research Center KSC SB RAS
Author for correspondence.
Email: evg@ksc.krasn.ru
Russian Federation, Krasnoyarsk; Krasnoyarsk
E. G. Shvetsov
Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, Federal Research Center KSC SB RAS
Email: evg@ksc.krasn.ru
Russian Federation, Krasnoyarsk
K. Yu. Litvintsev
Kutateladze Institute of Thermophysics, Siberian Branch, Russian Academy of Sciences
Email: evg@ksc.krasn.ru
Russian Federation, Novosibirsk