Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning

<p>Many nations are challenged by landscape fires. A confident knowledge of the area and distribution of burning is crucial to monitor these fires and to assess how they might best be reduced. Given the differences that arise using different detection approaches, and the uncertainties surround...

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Autores principales:	D. L. A. Gaveau, A. Descals, M. A. Salim, D. Sheil, S. Sloan
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Environmental sciences GE1-350 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/4b6ede3c9a414ea8a86808f160086d7a
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spelling	oai:doaj.org-article:4b6ede3c9a414ea8a86808f160086d7a2021-11-18T08:49:21ZRefined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning10.5194/essd-13-5353-20211866-35081866-3516https://doaj.org/article/4b6ede3c9a414ea8a86808f160086d7a2021-11-01T00:00:00Zhttps://essd.copernicus.org/articles/13/5353/2021/essd-13-5353-2021.pdfhttps://doaj.org/toc/1866-3508https://doaj.org/toc/1866-3516<p>Many nations are challenged by landscape fires. A confident knowledge of the area and distribution of burning is crucial to monitor these fires and to assess how they might best be reduced. Given the differences that arise using different detection approaches, and the uncertainties surrounding burned-area estimates, their relative merits require evaluation. Here we propose, illustrate, and examine one promising approach for Indonesia where recurring forest and peatland fires have become an international crisis.</p> <p>Drawing on Sentinel-2 satellite time-series analysis, we present and validate new 2019 burned-area estimates for Indonesia. The corresponding burned-area map is available at <a href="https://doi.org/10.5281/zenodo.4551243">https://doi.org/10.5281/zenodo.4551243</a> (Gaveau et al., 2021a). We show that <span class="inline-formula">>3.11</span> million hectares (Mha) burned in 2019. This burned-area extent is double the Landsat-derived official estimate of 1.64 <span class="inline-formula">Mha</span> from the Indonesian Ministry of Environment and Forestry and 50 % more that the MODIS MCD64A1 burned-area estimate of 2.03 <span class="inline-formula">Mha</span>. Though we observed proportionally less peatland burning (31 % vs. 39 % and 40 % for the official and MCD64A1 products, respectively), in absolute terms we still observed a greater area of peatland affected (0.96 <span class="inline-formula">Mha</span>) than the official estimate (0.64 <span class="inline-formula">Mha</span>). This new burned-area dataset has greater reliability than these alternatives, attaining a user accuracy of 97.9 % (CI: 97.1 %–98.8 %) compared to 95.1 % (CI: 93.5 %–96.7 %) and 76 % (CI: 73.3 %–78.7 %), respectively. It omits fewer burned areas, particularly smaller- (<span class="inline-formula"><100</span> <span class="inline-formula">ha</span>) to intermediate-sized (100–1000 <span class="inline-formula">ha</span>) burns, attaining a producer accuracy of 75.6 % (CI: 68.3 %–83.0 %) compared to 49.5 % (CI: 42.5 %–56.6 %) and 53.1 % (CI: 45.8 %–60.5 %), respectively. The frequency–area distribution of the Sentinel-2 burn scars follows the apparent fractal-like power law or Pareto pattern often reported in other fire studies, suggesting good detection over several magnitudes of scale. Our relatively accurate estimates have important implications for carbon-emission calculations from forest and peatland fires in Indonesia.</p>D. L. A. GaveauA. DescalsM. A. SalimD. SheilS. SloanCopernicus PublicationsarticleEnvironmental sciencesGE1-350GeologyQE1-996.5ENEarth System Science Data, Vol 13, Pp 5353-5368 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Environmental sciences GE1-350 Geology QE1-996.5
spellingShingle	Environmental sciences GE1-350 Geology QE1-996.5 D. L. A. Gaveau A. Descals M. A. Salim D. Sheil S. Sloan Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
description	<p>Many nations are challenged by landscape fires. A confident knowledge of the area and distribution of burning is crucial to monitor these fires and to assess how they might best be reduced. Given the differences that arise using different detection approaches, and the uncertainties surrounding burned-area estimates, their relative merits require evaluation. Here we propose, illustrate, and examine one promising approach for Indonesia where recurring forest and peatland fires have become an international crisis.</p> <p>Drawing on Sentinel-2 satellite time-series analysis, we present and validate new 2019 burned-area estimates for Indonesia. The corresponding burned-area map is available at <a href="https://doi.org/10.5281/zenodo.4551243">https://doi.org/10.5281/zenodo.4551243</a> (Gaveau et al., 2021a). We show that <span class="inline-formula">>3.11</span> million hectares (Mha) burned in 2019. This burned-area extent is double the Landsat-derived official estimate of 1.64 <span class="inline-formula">Mha</span> from the Indonesian Ministry of Environment and Forestry and 50 % more that the MODIS MCD64A1 burned-area estimate of 2.03 <span class="inline-formula">Mha</span>. Though we observed proportionally less peatland burning (31 % vs. 39 % and 40 % for the official and MCD64A1 products, respectively), in absolute terms we still observed a greater area of peatland affected (0.96 <span class="inline-formula">Mha</span>) than the official estimate (0.64 <span class="inline-formula">Mha</span>). This new burned-area dataset has greater reliability than these alternatives, attaining a user accuracy of 97.9 % (CI: 97.1 %–98.8 %) compared to 95.1 % (CI: 93.5 %–96.7 %) and 76 % (CI: 73.3 %–78.7 %), respectively. It omits fewer burned areas, particularly smaller- (<span class="inline-formula"><100</span> <span class="inline-formula">ha</span>) to intermediate-sized (100–1000 <span class="inline-formula">ha</span>) burns, attaining a producer accuracy of 75.6 % (CI: 68.3 %–83.0 %) compared to 49.5 % (CI: 42.5 %–56.6 %) and 53.1 % (CI: 45.8 %–60.5 %), respectively. The frequency–area distribution of the Sentinel-2 burn scars follows the apparent fractal-like power law or Pareto pattern often reported in other fire studies, suggesting good detection over several magnitudes of scale. Our relatively accurate estimates have important implications for carbon-emission calculations from forest and peatland fires in Indonesia.</p>
format	article
author	D. L. A. Gaveau A. Descals M. A. Salim D. Sheil S. Sloan
author_facet	D. L. A. Gaveau A. Descals M. A. Salim D. Sheil S. Sloan
author_sort	D. L. A. Gaveau
title	Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
title_short	Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
title_full	Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
title_fullStr	Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
title_full_unstemmed	Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
title_sort	refined burned-area mapping protocol using sentinel-2 data increases estimate of 2019 indonesian burning
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/4b6ede3c9a414ea8a86808f160086d7a
work_keys_str_mv	AT dlagaveau refinedburnedareamappingprotocolusingsentinel2dataincreasesestimateof2019indonesianburning AT adescals refinedburnedareamappingprotocolusingsentinel2dataincreasesestimateof2019indonesianburning AT masalim refinedburnedareamappingprotocolusingsentinel2dataincreasesestimateof2019indonesianburning AT dsheil refinedburnedareamappingprotocolusingsentinel2dataincreasesestimateof2019indonesianburning AT ssloan refinedburnedareamappingprotocolusingsentinel2dataincreasesestimateof2019indonesianburning
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Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning

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