@InProceedings{FerreiraTCSFALVS:2015:PrMe,
               author = "Ferreira, George Porto and Toniol, Alana Carla and Cruz, Pedro 
                         Ferraz and Sano, Edson Eyji and Freitas, Daniel Moraes and Aguiar, 
                         Marcelo Cabral and Lopes, Camila Aparecida Lima and Vilela, 
                         Lidiane de F{\'a}tima and Souza, Marcelo Soares",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Detec{\c{c}}{\~a}o de altera{\c{c}}{\~o}es recentes na 
                         cobertura vegetal natural da Amaz{\^o}nia Legal por meio de 
                         imagens Landsat-8: proposta metodol{\'o}gica",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4727--4733",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "INPE has monitored deforestation in the Brazilian Amazon in near 
                         real-time using the Moderate Resolution Imaging Spectroradiometer 
                         (MODIS) data, which has 1-2 repeat pass and 250-m spatial 
                         resolution. As farmers started to clear-cut forests in small 
                         patches more intensively, the use of MODIS sensor is becoming 
                         limited. In order to complement the information provided by the 
                         INPE´s system, we propose a methodological approach to detect 
                         alterations in forestlands from the Legal Amazonia based on two 
                         subsequent Landsat-8 overpasses in time. The study area was a set 
                         of 85 Landsat-8 scenes located mostly in the states of 
                         Rond{\^o}nia, Mato Grosso and Par{\'a} where ongoing 
                         deforestation is significant. The approach is based on the 
                         difference between these two images, which is entirely processed 
                         using the color rendering function available in the public domain 
                         Quantum GIS Desktop 2.4.0. Pixels presenting spectral changes are 
                         highlighted in bright tones and may be related to clear-cutting or 
                         to forest degradation processes. Visual interpretation of RGB 
                         color composites are then conducted only on such highlighted 
                         portions of images, making the whole process of image analysis 
                         much faster. In the time period of August 1 October 3, 2014, we 
                         identified a total of 924,49 km2 of alterations in the study area. 
                         The municipality of Altamira, Para State, presented the highest 
                         area of alteration (90,3 km2). Results showed that the approach 
                         developed in this study is suitable to detect small-size 
                         alterations in the Brazilian Amazon (~ > 6 ha) within the Landsat 
                         patch frame (185 km) in near real-time.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "926",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4D7H",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4D7H",
           targetfile = "p0926.pdf",
                 type = "Floresta e vegeta{\c{c}}{\~a}o",
        urlaccessdate = "27 abr. 2024"
}