@Article{GaspariniSiShArArSiMa:2019:DeThDe,
               author = "Gasparini, Kaio Allan Cruz and Silva J{\'u}nior, Celso Henrique 
                         Leite and Shimabukuro, Yosio Edemir and Arai, Egidio and 
                         Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and Silva, Carlos 
                         Alberto and Marshall, Peter L.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {University of Maryland} and {University of British 
                         Columbia}",
                title = "Determining a threshold to delimit the Amazonian forests from the 
                         tree canopy cover 2000 GFC data",
              journal = "Sensors",
                 year = "2019",
               volume = "19",
               number = "22",
                pages = "e5020",
                month = "Nov.",
             keywords = "forest mapping, Google Earth Engine, REDD+, remote sensing, forest 
                         degradation.",
             abstract = "Open global forest cover data can be a critical component for 
                         Reducing Emissions from Deforestation and Forest Degradation 
                         (REDD+) policies. In this work, we determine the best threshold, 
                         compatible with the official Brazilian dataset, for establishing a 
                         forest mask cover within the Amazon basin for the year 2000 using 
                         the Tree Canopy Cover 2000 GFC product. We compared forest cover 
                         maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 
                         90%, and 95%) with a forest cover map for the same year from the 
                         Brazilian Amazon Deforestation Monitoring Project (PRODES) data, 
                         produced by the National Institute for Space Research (INPE). We 
                         also compared the forest cover classifications indicated by each 
                         of these maps to 2550 independently assessed Landsat pixels for 
                         the year 2000, providing an accuracy assessment for each of these 
                         map products. We found that thresholds of 80% and 85% best matched 
                         with the PRODES data. Consequently, we recommend using an 80% 
                         threshold for the Tree Canopy Cover 2000 data for assessing forest 
                         cover in the Amazon basin.",
                  doi = "10.3390/s19225020",
                  url = "http://dx.doi.org/10.3390/s19225020",
                 issn = "1424-3210",
             language = "en",
           targetfile = "sensors-19-05020.pdf",
        urlaccessdate = "25 abr. 2024"
}