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@InProceedings{AraiDAAABSGS:2017:MoDeFo,
               author = "Arai, Egidio and Duarte, Valdete and Anderson, Liana Oighenstein 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and Achard, 
                         Fr{\'e}d{\'e}ric and Beuchle, Ren{\'e} and Simonetti, Dario and 
                         Grecchi, Rosana Cristina and Shimabukuro, Yosio Edemir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and {} and {} and 
                         {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Monitoring deforestation and forest degradation in the Amazon 
                         basin using multi-temporal fraction images derived from Sentinel-2 
                         sensor data",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "1218--1225",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "In this work we present a semi-automated procedure for monitoring 
                         deforestation and forest degradation in the Brazilian Amazon using 
                         a multi-temporal dataset of Sentinel-2 sensor. Forest cover 
                         degradation in the Brazilian Amazon region is mainly due to 
                         selective logging of intact/un-managed forests and to wildfires. 
                         The study area covers part of a Sentinel-2 sensor scene located in 
                         the State of Mato Grosso, in the deforestation arc of the 
                         Brazilian Legal Amazon. We selected three cloud-free Sentinel-2 
                         images acquired on 21st June, 1st August and 10th September 2016. 
                         We generated soil, vegetation and shade fraction images for 
                         highlighting the deforested, burned and selectively logged areas. 
                         Our analysis shows that deforestation and forest degradation by 
                         fire can be mapped using object based analysis. On the other hand, 
                         forest degradation by selective logging can be mapped using a 
                         pixel based classification of fraction images. Our results allowed 
                         the estimative of recent deforestation processes in old growth 
                         forests: 1,000 ha between 21st June and 1st August and 900 ha 
                         between 1st August and 10th September 2016. The burned forest 
                         areas corresponded to 10,700 ha between 21st June and 1st August 
                         and to 22,800 ha between 1st August and 10th September 2016. 
                         Degraded forest areas due to selective logging added to 135,000 ha 
                         as mapped in the image dated 1st August 2016 with 17,300 ha of new 
                         areas mapped in the image dated 10th September 2016. The proposed 
                         approach shows great potential for monitoring deforestation and 
                         forest degradation activities by selective logging and fires using 
                         the Sentinel-2 multi-temporal dataset, facilitating the 
                         implementation of actions of forest protection in Amazon region.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59232",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS4GBK",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3PS4GBK",
           targetfile = "59232.pdf",
                 type = "Degrada{\c{c}}{\~a}o de florestas",
        urlaccessdate = "26 nov. 2020"
}


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