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Using Remote Sensing to Assess Russian Forest Fire Carbon Emissions

机译:使用遥感评估俄罗斯森林火灾的碳排放

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摘要

Russian boreal forests are subject to frequent wildfires. The resulting combustion of large amounts of biomass not only transforms forest vegetation, but it also creates significant carbon emissions that total, according to some authors, from 35–94 Mt C per year. These carbon emissions from forest fires should be considered an important part of the forest ecosystem carbon balance and a significant influence on atmospheric trace gases. In this paper we discuss a new method to assess forest fire damage. This method is based on using multi-spectral high-resolution satellite images, large-scale aerial photography, and declassified images obtained from the space-borne national security systems. A normalized difference vegetation index (NDVI) difference image was produced from pre- and post-fire satellite images from SPOT/HRVIR and RESURS-O/MSU-E images. A close relationship was found between values of the NDVI difference image and forest damage level. High-resolution satellite data and large-scale aerial-photos were used to calibrate the NDVI-derived forest damage map. The method was used for mapping of forest fire extent and damage and for estimating carbon emissions from burned forest areas.
机译:俄罗斯的北方森林经常发生野火。一些作者认为,由此产生的大量生物质燃烧不仅改变了森林植被,而且还产生了大量的碳排放,每年的总碳排放量为35-94 MtC。应将森林大火产生的这些碳排放视为森林生态系统碳平衡的重要组成部分,并对大气中的痕量气体产生重大影响。在本文中,我们讨论了一种评估森林火灾损害的新方法。该方法基于使用多光谱高分辨率卫星图像,大规模航空摄影以及从星载国家安全系统获得的解密图像。从SPOT / HRVIR和RESURS-O / MSU-E图像发射前和发射后的卫星图像生成归一化差异植被指数(NDVI)差异图像。发现NDVI差异图像的值与森林破坏程度之间存在密切关系。使用高分辨率的卫星数据和大规模的航拍照片来校准源自NDVI的森林破坏图。该方法用于测绘森林火灾的程度和破坏程度,并估算出森林燃烧区的碳排放量。

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  • 来源
    《Climatic Change》 |2002年第2期|235-249|共15页
  • 作者单位

    Center of Problems of Ecology and Productivity of Forests (CEPL) Russian Academy of Science;

    Center of Problems of Ecology and Productivity of Forests (CEPL) Russian Academy of Science;

    Space Application Institute/Joint Research Center;

    Center of Problems of Ecology and Productivity of Forests (CEPL) Russian Academy of Science;

    World Resources Institute;

    Department of Geography University of Maryland;

    Department of Environmental Sciences University of Virginia;

    Altarum;

    U.S. National Imagery and Mapping Agency;

    U.S. National Imagery and Mapping Agency;

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  • 正文语种 eng
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