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@InProceedings{AlmeidaGalvAragDelg:2017:AvInIn,
               author = "Almeida, Catherine Torres de and Galv{\~a}o, L{\^e}nio Soares 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and Delgado, 
                         Rafael Coll",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Avalia{\c{c}}{\~a}o da incerteza inserida pela cobertura da 
                         terra na estimativa da produtividade prim{\'a}ria bruta do 
                         produto MOD17A2",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2051--2058",
         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 = "The objective of this study is to assess how different land cover 
                         classes of the Amazon and Cerrado contribute to the uncertainty in 
                         the estimation of gross primary productivity (GPP) based on the 
                         MOD17A2 model. For this purpose, the accuracy of the land cover 
                         product MCD12Q1 type UMD was evaluated and a sensitivity analysis 
                         was performed to show how GPP estimates from the MOD17A2 model 
                         respond to variations in land cover. The MCD12Q1 land cover 
                         classification had low accuracy over heterogeneous areas, with 
                         confusion among anthropogenic areas and savanna. The overall 
                         accuracy of the MCD12Q1 was 69% with this performance mostly 
                         related to the class of evergreen broadleaf forest. The 
                         sensitivity analysis showed that land cover variations in MOD17A2 
                         model introduced uncertainty in the estimation of GPP in 
                         heterogeneous areas. However, it is possible that other model 
                         input variables cause greater error in the GPP estimation, which 
                         requires further studies.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59791",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLPS8",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3PSLPS8",
           targetfile = "59791.pdf",
                 type = "Monitoramento e modelagem ambiental",
        urlaccessdate = "29 nov. 2020"
}


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