@InProceedings{SotheAlmeSchiLies:2017:PoDaSe,
               author = "Sothe, Camile and Almeida, Cl{\'a}udia Maria de and Schimalski, 
                         Marcos Benedito and Liesenberg, Veraldo",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Potencial dos dados Sentinel-2 e Landsat-8 para a 
                         classifica{\c{c}}{\~a}o do uso e cobertura da terra de um 
                         ambiente costeiro",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3672--3679",
         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 = "Considering the provision of timely, and accurate data from remote 
                         sensing system, satellite images are important source of creating 
                         land cover/use information. This study assessed the performance of 
                         the Sentinel-2 and Landsat-8 data for classification of a 
                         subtropical coastal zone. Two approaches were compared: maximum 
                         likelihood (MAXVER) and random forest (RF). Sentinel-2 data 
                         resulted in Kappa index 0.97 and 0.94 with MAXVER and RF 
                         classifier, respectively, while Landsat-8 Kappa index were 0.92 
                         and 0.90. All methods differed significantly from one another, 
                         indicating that the use of Sentinel-2 satellite images had 
                         superior results to Landsat-8. The analysis of the variables 
                         relevance with RF classifier showed that the new bands of 
                         Sentinel-2, like red-edge and near infrared plateau, were decisive 
                         for the successful classification of Sentinel-2 data. Additional 
                         research is needed to assess the full potential of Sentinel-2 data 
                         and to explore potential applications of this data in other 
                         environments or land cover change monitoring.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59714",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLTCF",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLTCF",
           targetfile = "59714.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "27 abr. 2024"
}