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Evaluating the SEVIRI fire thermal anomaly detection algorithm across the Central African Republic using the MODIS active fire product

Evaluating the SEVIRI fire thermal anomaly detection algorithm across the Central African Republic using the MODIS active fire product
Evaluating the SEVIRI fire thermal anomaly detection algorithm across the Central African Republic using the MODIS active fire product
Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI’s omission rate can be attributed to a coupling between SEVIRI’s low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI’s commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring
2072-4292
1890-1917
Freeborn, Patrick H,.
1ba882b4-5afa-4f1c-bb42-9c58e434e6b0
Wooster, Martin J.
b5333d24-509d-463b-8767-e2ca1f367805
Roberts, Gareth J.
fa1fc728-44bf-4dc2-8a66-166034093ef2
Xu, Weidong
76c3dcac-a4b6-43c7-81bf-d8bbeca8bb6b
Freeborn, Patrick H,.
1ba882b4-5afa-4f1c-bb42-9c58e434e6b0
Wooster, Martin J.
b5333d24-509d-463b-8767-e2ca1f367805
Roberts, Gareth J.
fa1fc728-44bf-4dc2-8a66-166034093ef2
Xu, Weidong
76c3dcac-a4b6-43c7-81bf-d8bbeca8bb6b

Freeborn, Patrick H,., Wooster, Martin J., Roberts, Gareth J. and Xu, Weidong (2014) Evaluating the SEVIRI fire thermal anomaly detection algorithm across the Central African Republic using the MODIS active fire product. Remote Sensing, 6 (3), 1890-1917. (doi:10.3390/rs6031890).

Record type: Article

Abstract

Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI’s omission rate can be attributed to a coupling between SEVIRI’s low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI’s commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring

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More information

Accepted/In Press date: 24 February 2014
e-pub ahead of print date: 28 February 2014
Published date: 2014
Organisations: Global Env Change & Earth Observation

Identifiers

Local EPrints ID: 362646
URI: http://eprints.soton.ac.uk/id/eprint/362646
ISSN: 2072-4292
PURE UUID: 80401f65-08fc-455f-94e8-ead396f43ad8
ORCID for Gareth J. Roberts: ORCID iD orcid.org/0009-0007-3431-041X

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Date deposited: 25 Apr 2014 07:48
Last modified: 15 Mar 2024 03:39

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Contributors

Author: Patrick H,. Freeborn
Author: Martin J. Wooster
Author: Weidong Xu

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