Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird)
Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Cent...
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description | Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future. |
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The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0159410</identifier><identifier>PMID: 27486664</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Biology and Life Sciences ; Burning ; Carbon ; Carbon - metabolism ; Cold Temperature ; Disasters ; Dry season ; Dynamic tests ; Earth Sciences ; Ecology and Environmental Sciences ; Ecosystem biology ; Ecosystems ; El Nino ; El Nino-Southern Oscillation event ; Emission analysis ; Emission measurements ; Engineering and Technology ; Fire behavior ; Fire detection ; Fire fighting ; Fire prevention ; Fires ; Forest & brush fires ; Greenhouse effect ; Greenhouse gases ; Haze ; Image acquisition ; Impact analysis ; Indonesia ; Landsat ; Landsat satellites ; Logging ; Low temperature ; Medicine and Health Sciences ; Mitigation ; MODIS ; Monitoring ; National parks ; Natural gas ; Peat ; Peat bogs ; Peatlands ; People and Places ; Propagation ; Protection and preservation ; Remote sensing ; Remote sensing systems ; Research and Analysis Methods ; Satellite Communications - instrumentation ; Sensitivity ; Sensors ; Smoke ; Southern Oscillation ; Spatial discrimination ; Spatial resolution</subject><ispartof>PloS one, 2016-08, Vol.11 (8), p.e0159410-e0159410</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Atwood et al. 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The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27486664</pmid><doi>10.1371/journal.pone.0159410</doi><tpages>e0159410</tpages><oa>free_for_read</oa></addata></record> |
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recordid | cdi_plos_journals_1808601662 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Algorithms Biology and Life Sciences Burning Carbon Carbon - metabolism Cold Temperature Disasters Dry season Dynamic tests Earth Sciences Ecology and Environmental Sciences Ecosystem biology Ecosystems El Nino El Nino-Southern Oscillation event Emission analysis Emission measurements Engineering and Technology Fire behavior Fire detection Fire fighting Fire prevention Fires Forest & brush fires Greenhouse effect Greenhouse gases Haze Image acquisition Impact analysis Indonesia Landsat Landsat satellites Logging Low temperature Medicine and Health Sciences Mitigation MODIS Monitoring National parks Natural gas Peat Peat bogs Peatlands People and Places Propagation Protection and preservation Remote sensing Remote sensing systems Research and Analysis Methods Satellite Communications - instrumentation Sensitivity Sensors Smoke Southern Oscillation Spatial discrimination Spatial resolution |
title | Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird) |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T13%3A05%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Detection%20and%20Characterization%20of%20Low%20Temperature%20Peat%20Fires%20during%20the%202015%20Fire%20Catastrophe%20in%20Indonesia%20Using%20a%20New%20High-Sensitivity%20Fire%20Monitoring%20Satellite%20Sensor%20(FireBird)&rft.jtitle=PloS%20one&rft.au=Atwood,%20Elizabeth%20C&rft.date=2016-08-03&rft.volume=11&rft.issue=8&rft.spage=e0159410&rft.epage=e0159410&rft.pages=e0159410-e0159410&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0159410&rft_dat=%3Cgale_plos_%3EA471019138%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1808601662&rft_id=info:pmid/27486664&rft_galeid=A471019138&rft_doaj_id=oai_doaj_org_article_6c44564558e849019f602a4f774676b5&rfr_iscdi=true |