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@Article{DinizSSDLMMGNVMA:2015:NeAmNe,
               author = "Diniz, Cesar Guerreiro and Souza, Arleson Antonio de Almeida and 
                         Santos, Diogo Correa and Dias, Miriam Correa and Luz, Nelton 
                         Cavalcante and Moraes, Douglas Rafael Vidal de and Maia, Janaina 
                         Sant'Ana and Gomes, Alessandra Rodrigues and Narvaes, Igor da 
                         Silva and Valeriano, Dalton de Morisson and Maurano, Luis Eduardo 
                         Pinheiro and Adami, Marcos",
          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 {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 {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "DETER-B: the new Amazon near real-time deforestation detection 
                         system",
              journal = "IEEE Journal of Selected Topics in Applied Earth Observations and 
                         Remote Sensing",
                 year = "2015",
               volume = "8",
               number = "7",
                pages = "3619--3628",
                month = "July",
             keywords = ": Deforestation, Monitoring, Public policy, Remote sensing, Space 
                         research, Area estimation, Detection capability, Detection system, 
                         Early Warning System, Government investment, Monitoring system, 
                         Near-real time, rainforest, Real time systems, deforestation, 
                         early warning system, forestry policy, MODIS, monitoring system, 
                         rainforest, real time, remote sensing, satellite imagery, 
                         Amazonia, Brazil.",
             abstract = "The Brazilian Legal Amazon (BLA), the largest global rainforest on 
                         earth, contains nearly 30% of the rainforest on earth. Given the 
                         regional complexity and dynamics, there are large government 
                         investments focused on controlling and preventing deforestation. 
                         The National Institute for Space Research (INPE) is currently 
                         developing five complementary BLA monitoring systems, among which 
                         the near real-time deforestation detection system (DETER) excels. 
                         DETER employs MODIS 250 m imagery and almost daily revisit, 
                         enabling an early warning system to support surveillance and 
                         control of deforestation. The aim of this paper is to present the 
                         methodology and results of the DETER based on AWIFS data, called 
                         DETER-B. Supported by 56 m images, the new system is effective in 
                         detecting deforestation smaller than 25 ha, concentrating 80% of 
                         its total detections and 45% of the total mapped area in this 
                         range. It also presents higher detection capability in identifying 
                         areas between 25 and 100 ha. The area estimation per municipality 
                         is statistically equal to those of the official deforestation data 
                         (PRODES) and allows the identification of degradation and logging 
                         patterns not observed with the traditional DETER system.",
                  doi = "10.1109/JSTARS.2015.2437075",
                  url = "http://dx.doi.org/10.1109/JSTARS.2015.2437075",
                 issn = "1939-1404 and 2151-1535",
             language = "en",
        urlaccessdate = "05 dez. 2020"
}


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