The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment

The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched in October 2011 aboard the Suomi-National Polar-orbiting Partnership (S-NPP) satellite. The VIIRS instrument carries two separate sets of multi-spectral channels providing full global coverage at both 375m and 750m nominal reso...

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Published in:Remote sensing of environment 2014-03, Vol.143, p.85-96
Main Authors: Schroeder, Wilfrid, Oliva, Patricia, Giglio, Louis, Csiszar, Ivan A.
Format: Article
Language:English
Subjects:
Active fire detection
Algorithms
Assessments
Biomass burning
Channels
Construction
Fire detection
Fires
MODIS
Pixels
S-NPP/VIIRS
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Oliva, Patricia
Giglio, Louis
Csiszar, Ivan A.
description The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched in October 2011 aboard the Suomi-National Polar-orbiting Partnership (S-NPP) satellite. The VIIRS instrument carries two separate sets of multi-spectral channels providing full global coverage at both 375m and 750m nominal resolutions every 12h or less depending on the latitude. In this study, we introduce a new VIIRS active fire detection algorithm, which is driven primarily by the 375m middle and thermal infrared imagery data. The algorithm builds on the well-established MODIS Fire and Thermal Anomalies product using a contextual approach to detect both day and nighttime biomass burning and other thermal anomalies. Here we present the fire algorithm's design and implementation, including important information describing the input data characteristics and potential artifacts associated with pixel saturation and the South Atlantic Magnetic Anomaly, both found to affect the middle infrared channel data. Initial assessment using results derived from the global processing of the algorithm indicated small, although variable, commission errors (
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The VIIRS instrument carries two separate sets of multi-spectral channels providing full global coverage at both 375m and 750m nominal resolutions every 12h or less depending on the latitude. In this study, we introduce a new VIIRS active fire detection algorithm, which is driven primarily by the 375m middle and thermal infrared imagery data. The algorithm builds on the well-established MODIS Fire and Thermal Anomalies product using a contextual approach to detect both day and nighttime biomass burning and other thermal anomalies. Here we present the fire algorithm's design and implementation, including important information describing the input data characteristics and potential artifacts associated with pixel saturation and the South Atlantic Magnetic Anomaly, both found to affect the middle infrared channel data. Initial assessment using results derived from the global processing of the algorithm indicated small, although variable, commission errors (&lt;1.2%) for nominal confidence fire pixels. We achieved improved performance using the 375m active fire data compared to the VIIRS 750m baseline fire product, resulting in a 3× and 25× factor increase in the absolute number of fire pixels detected using day and nighttime data, respectively. 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subjects Active fire detection
Algorithms
Assessments
Biomass burning
Channels
Construction
Fire detection
Fires
MODIS
Pixels
S-NPP/VIIRS
title The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment
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