Integration of geostationary FRP and polar-orbiter burned area datasets for an enhanced biomass burning inventory
Integration of geostationary FRP and polar-orbiter burned area datasets for an enhanced biomass burning inventory
Earth Observation (EO) sensors play an important role in quantifying biomass burning related fuel consumption and carbon emissions, and capturing their spatial and temporal dynamics. Typically, biomass burning emissions inventories are developed by exploiting either burned area (BA) or active fire (AF) measures of fire radiative energy (FRE). These approaches have both advantages and limitations. For example, methods based on burned area data typically require hard-to-obtain estimates of fuel load and combustion completeness, and the accuracy of the BA algorithm may deteriorate for small fires or those in densely forested terrain. Conversely, ‘raw’ FRE-based methods are typically low-biassed due to the non-detection of low intensity fires, and are also hindered by cloud cover. Here we develop a methodology integrating these two EO data types to deliver a high temporal resolution emissions inventory, maximising the benefit of each data type without requiring additional information. We focus on Africa, the most fire affected continent, and combine daily FRE observations provided by Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) with BA measures delivered by Moderate Resolution Imaging Spectroradiometer (MODIS). For individual fires detected by both types of data, we estimate fuel consumption per unit area (FCA: g·m? 2) via the ratio of FRE-derived total fuel consumption (FCT) to BA. These values are then extrapolated to fires that were mapped using the BA data but which remained undetected in the SEVIRI AF product, thus correcting for the ‘low spatial resolution bias’ inherent in geostationary AF datasets. Calculated daily continental scale FCT for Africa varies between 0.3 and 20 Tg for the period February 2004–January 2005. We estimate annual continental FCT to be 1418 Tg, far closer to the 2272 Tg provided by the widely used Global Fire Emissions Database (version 3; GFEDv3) than is obtained when using ‘raw’ FRE data alone. This synergistic approach has substantially narrowed the gap between GFEDv3 and FRE-derived emissions inventories, whilst the geostationary FRP observations offer the advantage that the daily emissions estimates can be distributed more accurately over the diurnal fire cycle if required for linking to atmospheric transport models.
2047-2061
Roberts, G.
fa1fc728-44bf-4dc2-8a66-166034093ef2
Wooster, M.J.
4b91034b-d585-49ec-85b2-0729f9bca9dc
Freeborn, P.H.
232c8991-6d80-4aaf-824a-57ee9fb1e36f
Xu, W.
367fce1d-4335-45cc-995c-5aa75de74278
15 August 2011
Roberts, G.
fa1fc728-44bf-4dc2-8a66-166034093ef2
Wooster, M.J.
4b91034b-d585-49ec-85b2-0729f9bca9dc
Freeborn, P.H.
232c8991-6d80-4aaf-824a-57ee9fb1e36f
Xu, W.
367fce1d-4335-45cc-995c-5aa75de74278
Roberts, G., Wooster, M.J., Freeborn, P.H. and Xu, W.
(2011)
Integration of geostationary FRP and polar-orbiter burned area datasets for an enhanced biomass burning inventory.
Remote Sensing of Environment, 115 (8), .
(doi:10.1016/j.rse.2011.04.006).
Abstract
Earth Observation (EO) sensors play an important role in quantifying biomass burning related fuel consumption and carbon emissions, and capturing their spatial and temporal dynamics. Typically, biomass burning emissions inventories are developed by exploiting either burned area (BA) or active fire (AF) measures of fire radiative energy (FRE). These approaches have both advantages and limitations. For example, methods based on burned area data typically require hard-to-obtain estimates of fuel load and combustion completeness, and the accuracy of the BA algorithm may deteriorate for small fires or those in densely forested terrain. Conversely, ‘raw’ FRE-based methods are typically low-biassed due to the non-detection of low intensity fires, and are also hindered by cloud cover. Here we develop a methodology integrating these two EO data types to deliver a high temporal resolution emissions inventory, maximising the benefit of each data type without requiring additional information. We focus on Africa, the most fire affected continent, and combine daily FRE observations provided by Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) with BA measures delivered by Moderate Resolution Imaging Spectroradiometer (MODIS). For individual fires detected by both types of data, we estimate fuel consumption per unit area (FCA: g·m? 2) via the ratio of FRE-derived total fuel consumption (FCT) to BA. These values are then extrapolated to fires that were mapped using the BA data but which remained undetected in the SEVIRI AF product, thus correcting for the ‘low spatial resolution bias’ inherent in geostationary AF datasets. Calculated daily continental scale FCT for Africa varies between 0.3 and 20 Tg for the period February 2004–January 2005. We estimate annual continental FCT to be 1418 Tg, far closer to the 2272 Tg provided by the widely used Global Fire Emissions Database (version 3; GFEDv3) than is obtained when using ‘raw’ FRE data alone. This synergistic approach has substantially narrowed the gap between GFEDv3 and FRE-derived emissions inventories, whilst the geostationary FRP observations offer the advantage that the daily emissions estimates can be distributed more accurately over the diurnal fire cycle if required for linking to atmospheric transport models.
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Published date: 15 August 2011
Organisations:
Remote Sensing & Spatial Analysis
Identifiers
Local EPrints ID: 188453
URI: http://eprints.soton.ac.uk/id/eprint/188453
ISSN: 0034-4257
PURE UUID: 2704e72c-be7f-42f2-8c51-2ebfb562890e
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Date deposited: 25 May 2011 10:34
Last modified: 15 Mar 2024 03:39
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Author:
M.J. Wooster
Author:
P.H. Freeborn
Author:
W. Xu
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