@Article{PessôaACCSRRPAJOSSPMA:2020:InBuAr,
               author = "Pess{\^o}a, Ana Carolina Moreira and Anderson, Liana O. and 
                         Carvalho, Nath{\'a}lia Silva de and Campanharo, Wesley Augusto 
                         and Silva J{\'u}nior, Celso Henrique Leite and Rosan, Thais M. 
                         and Reis, Jo{\~a}o B. C. and Pereira, Francisca Rocha de Souza 
                         and Assis, Mauro and Jacon, Aline Daniele and Ometto, Jean Pierre 
                         Henry Balbaud and Shimabukuro, Yosio Edemir and Silva, Camila V. 
                         J. and Pontes Lopes, Aline and Morello, Thiago F. and Arag{\~a}o, 
                         Luiz Eduardo Oliveira e Cruz de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Centro 
                         Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {University 
                         of Exeter} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Atrium Forest Consulting} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Lancaster University} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         do ABC (UFABC)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Intercomparison of burned area products and its implication for 
                         carbon emission estimations in the Amazon",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "3684",
                pages = "1--25",
             keywords = "committed carbon, forest fire, land use and land cover change, 
                         regional assessment.",
             abstract = "Carbon (C) emissions from forest fires in the Amazon during 
                         extreme droughts may correspond to more than half of the global 
                         emissions resulting from land cover changes. Despite their 
                         relevant contribution, forest fire-related C emissions are not 
                         directly accounted for within national-level inventories or carbon 
                         budgets. A fundamental condition for quantifying these emissions 
                         is to have a reliable estimation of the extent and location of 
                         land cover types affected by fires. Here, we evaluated the 
                         relative performance of four burned area products (TREES, MCD64A1 
                         c6, GABAM, and Fire_cci v5.0), contrasting their estimates of 
                         total burned area, and their influence on the fire-related C 
                         emissions in the Amazon biome for the year 2015. In addition, we 
                         distinguished the burned areas occurring in forests from 
                         non-forest areas. The four products presented great divergence in 
                         the total burned area and, consequently, total related C 
                         emissions. Globally, the TREES product detected the largest amount 
                         of burned area (35,559 km2), and consequently it presented the 
                         largest estimate of committed carbon emission (45 Tg), followed by 
                         MCD64A1, with only 3% less burned area detected, GABAM (28,193 
                         km2) and Fire_cci (14,924 km2). The use of Fire_cci may result in 
                         an underestimation of 29.54 ± 3.36 Tg of C emissions in relation 
                         to the TREES product. The same pattern was found for non-forest 
                         areas. Considering only forest burned areas, GABAM was the product 
                         that detected the largest area (8994 km2), followed by TREES (7985 
                         km2), MCD64A1 (7181 km2) and Fire_cci (1745 km2). Regionally, 
                         Fire_cci detected 98% less burned area in Acre state in southwest 
                         Amazonia than TREES, and approximately 160 times less burned area 
                         in forests than GABAM. Thus, we show that global products used 
                         interchangeably on a regional scale could significantly 
                         underestimate the impacts caused by fire and, consequently, their 
                         related carbon emissions.",
                  doi = "10.3390/rs12233864",
                  url = "http://dx.doi.org/10.3390/rs12233864",
                 issn = "2072-4292",
             language = "en",
           targetfile = "pessoa_intercomparison.pdf",
        urlaccessdate = "05 maio 2024"
}