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Remote sensing of Canadian boreal forest fires: hotspots, burned area, and smoke plumes

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4 Author(s)
Z. Li ; Canada Centre for Remote Sensing, Ottawa, Ont., Canada ; J. Cihlar ; R. H. Fraser ; A. Khananian

A comprehensive investigation of Canadian boreal forest fires was conducted using NOAA-AVHRR. Algorithms were developed for detecting active fires (hotspots), burned areas, and smoke plumes, which employ single images and 10-day Normalised Difference Vegetation Index (NDVI) composites. The hotspot algorithm was applied to four years (1994-97) of imagery, producing a daily fire mask for Canada. Almost all fire events were detected, but cumulative hotspot area was significantly smaller (~30%) than burned area reported by fire agencies. To provide more accurate estimates of burned area, a burn mapping algorithm was developed that synergistically combines the hotspot product with anniversary date NDVI composites. The hybrid technique produced estimates of Canada-wide burned area that were within 5 percent of official statistics. A neural-network classifier was also developed that allows smoke plumes to be effectively separated from cloud cover at a regional scale

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Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International  (Volume:4 )

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