2017
DOI: 10.1016/j.rse.2017.07.003
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Detecting high and low-intensity fires in Alaska using VIIRS I-band data: An improved operational approach for high latitudes

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Cited by 33 publications
(19 citation statements)
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“…The dominance of smoldering fires in the Arctic may pose a challenge for satellite detection of wildfires. For example, Waigl et al () find that Moderate Resolution Imaging Spectroradiometer failed to detect 45% of wildfires in Alaska in 2016, leading to a large bias in emission estimates for this region. In addition, fires burning low to the ground, as opposed to high crown fires, possibly emit into the boundary layer rather than further aloft, which may lead to less dilution and hence higher pollutant concentrations at the surface.…”
Section: Local Arctic Air Pollutant Emissionsmentioning
confidence: 99%
“…The dominance of smoldering fires in the Arctic may pose a challenge for satellite detection of wildfires. For example, Waigl et al () find that Moderate Resolution Imaging Spectroradiometer failed to detect 45% of wildfires in Alaska in 2016, leading to a large bias in emission estimates for this region. In addition, fires burning low to the ground, as opposed to high crown fires, possibly emit into the boundary layer rather than further aloft, which may lead to less dilution and hence higher pollutant concentrations at the surface.…”
Section: Local Arctic Air Pollutant Emissionsmentioning
confidence: 99%
“…The moderate resolution imaging spectroradiometer (MODIS), the land remote-sensing satellite program (Landsat), and the visible infrared imaging radiometer suite (VIIRS) are some of the most commonly used EOSs for forest fire detection, monitoring, and assessment on a regional and global scale [13][14][15][16]. The variation of spatial and temporal resolutions of EOS sensors is a critical issue for fire detection.…”
Section: Introductionmentioning
confidence: 99%
“…It provides two kinds of active fire products globally, the MODIS Collection 6 (C6, 1 km) accumulated since November 11, 2000 and VIIRS Version 1 (V1, 375 m) collected after January 20, 2012. Compared with the contextual fire detection algorithm used for MODIS C6 (Giglio, Descloitres, Justice, & Kaufman, 2003), VIIRS data are superior to mapping performance because the radiometer's finer resolution and unique sampling scheme with data aggregation (Schroeder, Oliva, Giglio, & Csiszar, 2014;Waigl et al, 2017). The latter complements the former by highly responding to small fires and smoldering combustion and improves mapping of large fire perimeters as well.…”
Section: The Fire Information For Resource Management System-viirs mentioning
confidence: 99%
“…Although active fires have increasingly been investigated using VIIRS (Giglio et al, 2000;Hessl, 2011;Zhong, Duckham, Chong, & Tolhurst, 2016), spatial and temporal analyses of active fire occurrence frequencies at national, pan-regional, and global scales remain lacking (Mu et al, 2011;Waigl, Stuefer, Prakash, & Ichoku, 2017).…”
Section: Introductionmentioning
confidence: 99%