@InProceedings{DalagnolWYBOFTMGSAASG:2023:InCaEm,
               author = "Dalagnol, Ricardo and Wagner, Fabien Hubert and Yang, Yan and 
                         Braga, Daniel and Osborn, Fiona and Favrichon, Samuel and 
                         Takougoum, Le Bienfaiteur Sagang and Mullissa, Adugna and George, 
                         Stephanie and Silva J{\'u}nior, Celso Henrique Leite and 
                         Anderson, Liana O. and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz 
                         de and Saatchi, Sassan and Galv{\~a}o, L{\^e}nio Soares",
          affiliation = "{University of California Los Angeles} and {University of 
                         California Los Angeles} and {California Institute of Technology} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         CTrees.org and JPL/NASA/Caltech and {University of California} and 
                         {University of California Los Angeles} and CTrees.org and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {National 
                         Center for Monitoring and Early Warning of Natural Disasters} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {NASA Jet 
                         Propulsion Laboratory} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Increasing Carbon Emissions from Amazonian Forest Degradation",
            booktitle = "Proceedings...",
                 year = "2023",
         organization = "AGU FAll Meeting",
            publisher = "AGU",
             abstract = "Selective logging and fire disturbances affect large areas of 
                         tropical forests every year causing forest degradation and the 
                         reduction of biomass and carbon. However, disturbances' true 
                         extent and impacts on carbon emissions are difficult to quantify. 
                         These limitations can be attributed to the fact that conventional 
                         monitoring systems do not accurately map these disturbances or 
                         provide attributions. In this study, we use a deep-learning 
                         approach and high-resolution Planet NICFI imagery (4.77-m) to map 
                         forests degraded by selective logging and fire in the entire 
                         Amazon region from 2017 to 2022 and estimate carbon emissions. To 
                         map degradation, we extended an approach based on the U-Net model, 
                         previously trained over Mato Grosso state (Brazil), to the entire 
                         Amazon basin, obtaining high accuracy (>80%). Carbon emissions 
                         were estimated for areas overlapping our degradation maps using 
                         both Airborne Laser Scanning (ALS) datasets collected by National 
                         Institute for Space Research (INPE/Brazil) between 2016 and 2018, 
                         and multi-temporal regional maps of Aboveground Carbon Density 
                         (ACD) derived from the Global Ecosystem Dynamics Investigation 
                         (GEDI) and remote sensing data. Our maps show that selective 
                         logging and fire degraded an average of 11,452 and 21,745 km2 of 
                         forests per year from 2017 to 2022, respectively. This area has 
                         been steadily increasing for logging and highly varying for fire, 
                         with the largest area found in 2020 (34,702 km2), which was a 
                         drought year. Logging and fire were mostly detected alongside the 
                         Arc of Deforestation. Logging occurred more clustered than fire, 
                         showing hotspots that overlapped known forest concessions such as 
                         Tapaj{\'o}s-Arapiuns/PA, Flona Tapaj{\'o}s/PA, 
                         Sarac{\'a}-Taquera/PA, Flona Jamari/RO, and Itapiranga/AM. We 
                         also found other hotspots in Brazil at Paragominas/PA, 
                         L{\'a}brea/AM, large areas of Mato Grosso state, as well as in 
                         Madre de Dios and west of Ucayali regions (Peru), in Guarayos 
                         (Bolivia), and in Suriname. For the Amazon basin, we estimated 
                         increasing carbon emissions from 2017 to 2022, with similar or 
                         higher magnitudes of carbon emissions from deforestation in some 
                         years, such as 2020. Overall, these new estimates of the extent 
                         and impacts of degradation for forest carbon in the Amazon region 
                         highlight that tackling degradation is key for reducing carbon 
                         emissions.",
  conference-location = "San Francisco, CA",
      conference-year = "11-15 Dec. 2023",
             language = "en",
        urlaccessdate = "03 maio 2024"
}