Title

Use of Satellite Remote Sensing Data for Modeling Carbon Emissions from Fires: A Perspective in North America

Document Type

Book Chapter

Publication Date

2006

Keywords

Normalize Difference Vegetation Index, Emission Factor, Burned Area, Fuel Loading, Fire Danger

Digital Object Identifier (DOI)

https://doi.org/10.1007/978-3-540-37293-6_18

Abstract

Accurate accounting of carbon cycling is paramount to understanding and modeling global climate change. At present, a considerable amount of global carbon uptake (∼2 Gt/year) remains unaccounted for in the carbon budget. It has been argued that the missing carbon may be absorbed in the terrestrial biomes of the Northern Hemisphere (Tans et al., 1990), in particular the temperate and boreal forests in North America (NA), which could account for the bulk (1.7 Gt/year) of the missing carbon (Fan et al., 1998). Fire is a driving factor controlling the carbon dynamics in NA, which affects both the sign and magnitude of the carbon budget (Stocks et al., 1996; Conard and Ivanova, 1997; Kasischke, 2000). According to the modeling results of Chen et al. (2000), boreal forests in NA have undergone tremendous fluctuations in its carbon budget over the last 200 years (Fig. 18.1). Around 1880 when widespread severe fires released a huge amount of carbon into the atmosphere, the forests were a very large source of carbon (∼140 GtC/year) while around 1940, the forests became a very large sink of carbon (∼200 GtC/year) due to fast forest regeneration that absorbed a large quantity of atmospheric carbon. The net carbon exchange is now so small that it is being debated whether the boreal forest is currently a sink (Chen et al., 2000) or a source (Kurz et al., 1995). The close correlation between the carbon budget and fire activity demonstrates the importance of the accurate estimation of carbon emissions from fires.

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Citation / Publisher Attribution

Use of Satellite Remote Sensing Data for Modeling Carbon Emissions from Fires: A Perspective in North America, in J. J. Qu, W. Gao, M. Kafatos, R. E. Murphy & V. V. Salmonson (Eds.), Earth Science Satellite Remote Sensing, Springer, p. 337-362

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