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New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America

New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America
New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America
Vegetation fires are a key global terrestrial disturbance factor and a major source of atmospheric trace gases and aerosols. Therefore, many earth-system science and operational monitoring applications require access to repetitive, frequent and well-characterized information on fire emissions source strengths. Geostationary imagers offer important temporal advantages when studying rapidly changing phenomena such as vegetation fires. Here we present a new algorithm for detecting and characterising active fires burning within the imager footprints of the Geostationary Operational Environmental Satellites (GOES), including consideration of cloud-cover and calculation of fire radiative power (FRP), a metric shown to be strongly related to fuel consumption and smoke emission rates. The approach is based on a set of algorithms now delivering near real time (NRT) operational FRP products from the Meteosat Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) imager (available from http://landsaf.meteo.pt/), and the GOES processing chain presented here is designed to deliver a compatible fire product to complete geostationary coverage of the Western hemisphere. Results from the two GOES imagers are intercompared, and are independently verified against the well regarded MODIS cloud mask and active fire products. We find that the detection of cloud and active fires from GOES matches that of MODIS very well for fire pixels having FRP > 30 MW, when the GOES omission error falls to less than 10%. The FRP of fire clusters detected near simultaneously by both GOES and MODIS have a bias of only 22 MW, and a similar bias is found when comparing near-simultaneous GOES East and GOES West FRP observations. However, many fire pixels having FRP < 30 MW remain undetected by GOES, probably unavoidably since it has a much coarser spatial resolution than MODIS. Adjustment using data from the less frequent but more accurate views obtained from high spatial resolution polar orbiting imagers could be used to bias correct regional FRP totals. Temporal integration of the GOES FRP record indicates that during the summer months, biomass burning combusts thousands of millions of tonnes of fuel daily across the Americas. Comparison of these results to those of the Global Fire Emissions Database (GFEDv2) indicate strong linear relationships (r² > 0.9), suggesting that the timely FRP data available from a GOES real-time data feed is likely to be a suitable fire emissions source strength term for inclusion in schemes aiming to forecast the concentrations of atmospheric constituents affected by biomass burning
0034-4257
1876-1895
Xu, W.
367fce1d-4335-45cc-995c-5aa75de74278
Wooster, M.J.
4b91034b-d585-49ec-85b2-0729f9bca9dc
Roberts, G.
ea00db4e-84e7-4b39-8273-9b71dbd7e2f3
Freeborn, P.
f4924d4f-6135-4c2f-9b1a-66a13c532be6
Xu, W.
367fce1d-4335-45cc-995c-5aa75de74278
Wooster, M.J.
4b91034b-d585-49ec-85b2-0729f9bca9dc
Roberts, G.
ea00db4e-84e7-4b39-8273-9b71dbd7e2f3
Freeborn, P.
f4924d4f-6135-4c2f-9b1a-66a13c532be6

Xu, W., Wooster, M.J., Roberts, G. and Freeborn, P. (2010) New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America. Remote Sensing of Environment, 114 (9), 1876-1895. (doi:10.1016/j.rse.2010.03.012).

Record type: Article

Abstract

Vegetation fires are a key global terrestrial disturbance factor and a major source of atmospheric trace gases and aerosols. Therefore, many earth-system science and operational monitoring applications require access to repetitive, frequent and well-characterized information on fire emissions source strengths. Geostationary imagers offer important temporal advantages when studying rapidly changing phenomena such as vegetation fires. Here we present a new algorithm for detecting and characterising active fires burning within the imager footprints of the Geostationary Operational Environmental Satellites (GOES), including consideration of cloud-cover and calculation of fire radiative power (FRP), a metric shown to be strongly related to fuel consumption and smoke emission rates. The approach is based on a set of algorithms now delivering near real time (NRT) operational FRP products from the Meteosat Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) imager (available from http://landsaf.meteo.pt/), and the GOES processing chain presented here is designed to deliver a compatible fire product to complete geostationary coverage of the Western hemisphere. Results from the two GOES imagers are intercompared, and are independently verified against the well regarded MODIS cloud mask and active fire products. We find that the detection of cloud and active fires from GOES matches that of MODIS very well for fire pixels having FRP > 30 MW, when the GOES omission error falls to less than 10%. The FRP of fire clusters detected near simultaneously by both GOES and MODIS have a bias of only 22 MW, and a similar bias is found when comparing near-simultaneous GOES East and GOES West FRP observations. However, many fire pixels having FRP < 30 MW remain undetected by GOES, probably unavoidably since it has a much coarser spatial resolution than MODIS. Adjustment using data from the less frequent but more accurate views obtained from high spatial resolution polar orbiting imagers could be used to bias correct regional FRP totals. Temporal integration of the GOES FRP record indicates that during the summer months, biomass burning combusts thousands of millions of tonnes of fuel daily across the Americas. Comparison of these results to those of the Global Fire Emissions Database (GFEDv2) indicate strong linear relationships (r² > 0.9), suggesting that the timely FRP data available from a GOES real-time data feed is likely to be a suitable fire emissions source strength term for inclusion in schemes aiming to forecast the concentrations of atmospheric constituents affected by biomass burning

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Published date: September 2010

Identifiers

Local EPrints ID: 188473
URI: http://eprints.soton.ac.uk/id/eprint/188473
ISSN: 0034-4257
PURE UUID: b7475d45-6264-4298-8137-5a1489efd077
ORCID for G. Roberts: ORCID iD orcid.org/0000-0003-2252-1248

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Date deposited: 25 May 2011 12:27
Last modified: 15 Mar 2024 03:22

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Contributors

Author: W. Xu
Author: M.J. Wooster
Author: G. Roberts ORCID iD
Author: P. Freeborn

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