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@InProceedings{ShimabukuroBGAMSGDAAA:2015:DeFoDe,
               author = "Shimabukuro, Yosio Edemir and Beuchle, Ren{\'e} and Grecchi, 
                         Rosana Cristina and Achard, Fr{\'e}d{\'e}ric and Miettinen, 
                         Jukka and Simonetti, Dario and Gomez, Marcela Velasco and Duarte, 
                         Valdete and Arai, Egidio and Anderson, Liana Oighenstein and 
                         Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and {} 
                         and {} and {} and {} and {} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Detection of forest degradation caused by fires in Amazonia from 
                         time series of MODIS fraction images",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "651--658",
         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",
             keywords = "burned forests, tropical ecosystem.",
             abstract = "A new method is presented to detect and assess the extent of 
                         burned forests in a tropical ecosystem. Our study area is located 
                         in Mato Grosso state southern flank of the Brazilian Amazon 
                         region. MODIS images are used over the dry season of year 2010. 
                         The proposed method is based on (i) linear spectral mixing model 
                         applied to MODIS imagery to derive soil and shade fraction images 
                         and (ii) image segmentation and classification applied to a 
                         multi-temporal dataset of MODIS-derived images. In a first step, 
                         deforested areas are identified and mapped from the soil fraction 
                         images while burned areas are identified and mapped from the shade 
                         fraction images. Then, burned forest areas are mapped by combining 
                         a forest/non forest mask with the resulting burned area map. Our 
                         results show that 14,220 km2 of forests were degraded by fire in 
                         Mato Grosso during year 2010. Our approach can be potentially used 
                         operationally for detecting forest degradation due to fires. The 
                         proposed method can also be applied to time series of medium and 
                         high spatial resolution images for regional and local analysis.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "127",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM45GQ",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM45GQ",
           targetfile = "p0127.pdf",
                 type = "Degrada{\c{c}}{\~a}o de florestas",
        urlaccessdate = "22 jan. 2021"
}


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