@Article{FerroMADMSPOA:2024:ReAsBu,
               author = "Ferro, Poliana Domingos and Mataveli, Guilherme Augusto Verola and 
                         Arcanjo, Jeferson de Souza and Dutra, D{\'e}bora Joana and 
                         Medeiros, Tha{\'{\i}}s Pereira de and Shimabukuro, Yosio Edemir 
                         and Pess{\^o}a, Ana Carolina Moreira and Oliveira, Gabriel de and 
                         Anderson, Liana Oighenstein",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {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 de Pesquisa Ambiental 
                         da Amaz{\^o}nia (IPAM)} and {University of South Alabama} and 
                         {Centro Nacional de Monitoramento e Alertas de Desastres 
                         Naturais}",
                title = "Regional-Scale Assessment of Burn Scar Mapping in Southwestern 
                         Amazonia Using Burned Area Products and CBERS/WFI Data Cubes",
              journal = "Fire",
                 year = "2024",
               volume = "7",
               number = "3",
                pages = "e67",
                month = "Mar.",
             keywords = "Amazon, burned area, CBERS, data cubes, linear spectral mixture 
                         model, regional assessment.",
             abstract = "Fires are one of the main sources of disturbance in fire-sensitive 
                         ecosystems such as the Amazon. Any attempt to characterize their 
                         impacts and establish actions aimed at combating these events 
                         presupposes the correct identification of the affected areas. 
                         However, accurate mapping of burned areas in humid tropical forest 
                         regions remains a challenging task. In this paper, we evaluate the 
                         performance of four operational BA products (MCD64A1, Fire_cci, 
                         GABAM and MapBiomas Fogo) on a regional scale in the southwestern 
                         Amazon and propose a new approach to BA mapping using fraction 
                         images extracted from data cubes of the Brazilian orbital sensors 
                         CBERS-4/WFI and CBERS-4A/WFI. The methodology for detecting burned 
                         areas consisted of applying the Linear Spectral Mixture Model to 
                         the images from the CBERS-4/WFI and CBERS-4A/WFI data cubes to 
                         generate shadow fraction images, which were then segmented and 
                         classified using the ISOSEG non-supervised algorithm. Regression 
                         and similarity analyses based on regular grid cells were carried 
                         out to compare the BA mappings. The results showed large 
                         discrepancies between the mappings in terms of total area burned, 
                         land use and land cover affected (forest and non-forest) and 
                         spatial location of the burned area. The global products MCD64A1, 
                         GABAM and Fire_cci tended to underestimate the area burned in the 
                         region, with Fire_cci underestimating BA by 88%, while the 
                         regional product MapBiomas Fogo was the closest to the reference, 
                         underestimating by only 7%. The burned area estimated by the 
                         method proposed in this work (337.5 km2) was 12% higher than the 
                         reference and showed a small difference in relation to the 
                         MapBiomas Fogo product (18% more BA). These differences can be 
                         explained by the different datasets and methods used to detect 
                         burned areas. The adoption of global products in regional studies 
                         can be critical in underestimating the total area burned in 
                         sensitive regions. Our study highlights the need to develop 
                         approaches aimed at improving the accuracy of current global 
                         products, and the development of regional burned area products may 
                         be more suitable for this purpose. Our proposed approach based on 
                         WFI data cubes has shown high potential for generating more 
                         accurate regional burned area maps, which can refine BA estimates 
                         in the Amazon.",
                  doi = "10.3390/fire7030067",
                  url = "http://dx.doi.org/10.3390/fire7030067",
                 issn = "2571-6255",
             language = "en",
           targetfile = "fire-07-00067-v2.pdf",
        urlaccessdate = "05 maio 2024"
}