author = "Adami, Marcos and Gomes, Alessandra Rodrigues and Belluzzo, Amanda 
                         Pinoti and Coelho, Andr{\'e}a dos Santos and Valeriano, Dalton de 
                         Morisson and Ramos, Felipe de Souza and Narvaes, Igor da Silva and 
                         Brown, Irving Foster and Oliveira, Ivanilson Dias de and Santos, 
                         Lucyana Barros and Eduardo, Luis",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "A confiabilidade do PRODES: estimativa da acur{\'a}cia do 
                         mapeamento do desmatamento no estado Mato Grosso",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4189--4196",
         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 = "PRODES is completing almost thirty years of uninterrupted 
                         monitoring of clear-cut deforestation over the Brazilian Amazon. 
                         Until now, no estimate of its mapping accuracy has been made. In 
                         this sense, this article brings a first approximation of mapping 
                         accuracy estimation of PRODES deforested areas, taking as example 
                         the state of Mato Grosso for the year 2014. For this, a random 
                         sampling panel was constructed, stratified with two strata, the 
                         deforestation of 2014 and the remaining forest. The sample size 
                         was calculated using the binomial function. In addition, a web 
                         platform was built to evaluate the points drawn by three 
                         independent evaluators. The global accuracy of the mapping of 
                         deforestation for the state of Mato Grosso, for the year 2014 was 
                         94.5%, and may vary between 92.4% and 96.5%, in the evaluated 
                         scenario there was no class discordance to be found. Regarding the 
                         Forest class, the user accuracy was 90.5% and the producer''s 
                         accuracy was 88.4%, this imbalance between user accuracy and 
                         producer accuracy indicates that there is a tendency for the 
                         forest class area to be underestimated for this mapping, in this 
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59299",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM2LF",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3PSM2LF",
           targetfile = "59299.pdf",
                 type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
        urlaccessdate = "29 nov. 2020"