An accurate estimation of biomass burning emissions is in part limited by the lack of knowledge of fire burning phase (smoldering/flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in the night. In contrast, VIIRS 4 µm moderate resolution band #13 (M13), though capable to detect fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered due to their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to M-band pixels’ footprint that is based on DNB and M-band’s respective characteristics in their onboard schemes for detector aggregation and bow-tie effect removals. Subsequently, the visible energy fraction (VEF) as an indicator of fire burning phase is introduced and is calculated as the ratio of visible light power (VLP) and FRP for each fire pixel retrieved from VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing mostly smoldering wildfires such as peatland fires (with smaller VEF values) in Indonesia, flaming wildfires (with larger VEF values) over grasslands and savannahs in sub-Sahel region, and gas fares with largest VEF values in the Middle East. VEF is highly correlated with modified combustion efficiency (MCE) for different land cover types or regions. These results together with a case study of the 2018 California Campfire show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-8523 |
| Date | 01 August 2019 |
| Creators | Roudini, Sepehr |
| Contributors | Wang, Jun |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright © 2019 Sepehr Roudini |
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