Nonlinear approximation of wildfire front temperature on MODIS data for sub-pixel analysis of burning

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: All-Russian Conference with International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2021

Год издания: 2021

Ключевые слова: active combustion zone, radiation, remote data, sub-pixel analysis, wildfire

Аннотация: An improved approach to evaluate thermal anomalies characteristics using the pixel-based analysis of the MODIS imagery was proposed. The approach allows us to improve the accuracy in estimating characteristics of active combustion zones comparing to the standard Dozier method. We used the imagery of active wildfires in Siberian forПоказать полностьюests from the MODIS radiometer acquired in the spectral ranges of 3.930–3.990 and 10.780–11.280 μm (bands 21 and 31, respectively). Nonlinear exponential function was used to describe the approximation of the temperature of combustion zones. Available data of field and numerical experiments were used for validating of the approximation accuracy. Nonlinear approximation of wildfire front temperature allows to determine the portion of the active pixel of the MODIS image with the given temperature excess comparing to the temperature of background cover. This improves the accuracy in extracting of active burning zones as well as in classifying the heat release rate at the sub-pixel level of analysis. © 2021 Copyright for this paper by its authors.

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Издание

Журнал: CEUR Workshop Proceedings

Выпуск журнала: Vol. 3006

Номера страниц: 161-171

ISSN журнала: 16130073

Издатель: CEUR-WS

Персоны

  • Litvintsev K.Yu. (S.S. Kutateladze Institute of Thermophysics SB RAS, Novosibirsk, Russian Federation)
  • Ponomarev E.I. (V.N. Sukachev Institute of Forest, Federal Research Center “Krasnoyarsk Science Center SB RAS”, Krasnoyarsk, Russian Federation, Siberian Federal University, Krasnoyarsk, Russian Federation)
  • Shvetsov E.G. (V.N. Sukachev Institute of Forest, Federal Research Center “Krasnoyarsk Science Center SB RAS”, Krasnoyarsk, Russian Federation)

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