{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T14:06:43Z","timestamp":1768313203938,"version":"3.49.0"},"reference-count":86,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,10,5]],"date-time":"2018-10-05T00:00:00Z","timestamp":1538697600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000270","name":"Natural Environment Research Council","doi-asserted-by":"publisher","award":["NE\/M017958\/1"],"award-info":[{"award-number":["NE\/M017958\/1"]}],"id":[{"id":"10.13039\/501100000270","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>African landscape fires are widespread, recurrent and temporally dynamic. They burn large areas of the continent, modifying land surface properties and significantly affect the atmosphere. Satellite Earth Observation (EO) data play a pivotal role in capturing the spatial and temporal variability of African biomass burning, and provide the key data required to develop fire emissions inventories. Active fire observations of fire radiative power (FRP, MW) have been shown to be linearly related to rates of biomass combustion (kg s\u22121). The Meteosat FRP-PIXEL product, delivered in near real-time by the EUMETSAT Land Surface Analysis Satellite Applications Facility (LSA SAF), maps FRP at 3 km resolution and 15-min intervals and these data extend back to 2004. Here we use this information to assess spatio-temporal variations in fire activity across sub-Saharan Africa, and identify an overall trend of decreasing annual fire activity and fuel consumption, agreeing with the widely-used Global Fire Emissions Database (GFEDv4) based on burned area measures. We provide the first comprehensive assessment of relationships between per-fire FRE-derived fuel consumption (Tg dry matter, DM) and temporally integrated Moderate Resolution Imaging Spectroradiometer (MODIS) net photosynthesis (PSN) (Tg, which can be converted into pre-fire fuel load estimates). We find very strong linear relationships over southern hemisphere Africa (mean r = 0.96) that are partly biome dependent, though the FRE-derived fuel consumptions are far lower than those derived from the accumulated PSN, with mean fuel consumptions per unit area calculated as 0.14 kg DM m\u22122. In the northern hemisphere, FRE-derived fuel consumption is also far lower and characterized by a weaker linear relationship (mean r = 0.76). Differences in the parameterization of the biome look up table (BLUT) used by the MOD17 product over Northern Africa may be responsible but further research is required to reconcile these differences. The strong relationship between fire FRE and pre-fire fuel load in southern hemisphere Africa is encouraging and highlights the value of geostationary FRP retrievals in providing a metric that relates very well to fuel consumption and fire emission variations. The fact that the estimated fuel consumed is only a small fraction of the fuel available suggests underestimation of FRE by Spinning Enhanced Visible and Infrared Imager (SEVIRI) and\/or that the FRE-to-fuel consumption conversion factor of 0.37 MJ kg\u22121 needs to be adjusted for application to SEVIRI. Future geostationary imaging sensors, such as on the forthcoming Meteosat Third Generation (MTG), will reduce the impact of this underestimation through its ability to detect even smaller and shorter-lived fires than can the current second generation Meteosat.<\/jats:p>","DOI":"10.3390\/rs10101591","type":"journal-article","created":{"date-parts":[[2018,10,5]],"date-time":"2018-10-05T12:16:44Z","timestamp":1538741804000},"page":"1591","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Fire Activity and Fuel Consumption Dynamics in Sub-Saharan Africa"],"prefix":"10.3390","volume":"10","author":[{"given":"Gareth","family":"Roberts","sequence":"first","affiliation":[{"name":"Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6375-7949","authenticated-orcid":false,"given":"Martin J.","family":"Wooster","sequence":"additional","affiliation":[{"name":"Department of Geography, Kings College London, Strand, London, WC2R 2LS, UK"},{"name":"NERC National Centre for Earth Observation (NCEO), Kings College London, Strand, London, WC2R 2LS, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weidong","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Geography, Kings College London, Strand, London, WC2R 2LS, UK"},{"name":"NERC National Centre for Earth Observation (NCEO), Kings College London, Strand, London, WC2R 2LS, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangping","family":"He","sequence":"additional","affiliation":[{"name":"Department of Geography, Kings College London, Strand, London, WC2R 2LS, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1126\/science.1163886","article-title":"Fire in the Earth System","volume":"234","author":"Bowman","year":"2009","journal-title":"Science"},{"key":"ref_2","first-page":"G02008","article-title":"Fire as an interactive component of dynamics vegetation models","volume":"110","author":"Arora","year":"2005","journal-title":"J. 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