@InProceedings{ShimabukuroVeroBernPere:2013:AvQuPr,
               author = "Shimabukuro, Yosio Edemir and Verona, Jane Delane and Bernardes, 
                         Tiago and Pereira, Gabriel",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Avalia{\c{c}}{\~a}o da qualidade do produto Globcover para o 
                         Estado do Mato Grosso, Brasil, por meio de imagens do Google Earth 
                         e s{\'e}ries temporais de {\'{\i}}ndices de 
                         vegeta{\c{c}}{\~a}o derivados de imagens MODIS",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "3486--3493",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Globcover is a global land cover map derived from an automated 
                         processing chain of 300m resolution MERIS time series and is 
                         provided as a major reference for applications such as climate and 
                         ecological modeling. The objective of this study was to validate 
                         the Globcover product for the State of Mato Grosso Brazil using 
                         Google earth images and temporal profiles of MODIS derived 
                         vegetation indices as a support to validate the landcover classes. 
                         The Vegetation Map Types produced by Radam Brasil Projects was 
                         used as an auxiliary information to check the mapping product. The 
                         procedure was divided into 4 steps: i) elaborating a random set of 
                         points for each class to validate the map; ii) translating 
                         landcover classes described in the Globcover Map into landcover 
                         classes as described in Radam Brasil Project; iii) extract 
                         temporal profiles of vegetation indices concerning the main 
                         landcover classes in the State of Mato Grosso iv) interpreting 
                         Google Earth images (reference data) to check the accuracy of 
                         Globcover classes. For each of the 16 classes evaluated it was 
                         sorted random samples totaling 108 points for the whole study 
                         area. Temporal profiles of Enhanced Vegetation Index (EVI 2) were 
                         selected from the Visualization of MODIS time-series for land use 
                         and landcover change analyses tool developed at National Institute 
                         for Space Research within the concept of a Virtual Laboratory of 
                         Remote Sensing in order to describe the main land use classes. 
                         These profiles can be used to describe the behavior of mapped 
                         classes along the period previous the mapping (2000 to 2011) and 
                         give support for interpretation of the high resolution imagery by 
                         its seasonal dynamics in future mappings. The confusion matrix 
                         resulted a kappa index of 0.43 and an overall accuracy of 0.47. 
                         These values are lower than those reported on the Globcover 
                         Products Description and Validation Report. The six main classes 
                         presented about 95% of the area of Mato Grosso State. Class 14 
                         presented the larger area with about 50% of the total mapped and 
                         producer and user accuracies of 0.67 and 0.75, respectively. 
                         Temporal profiles of EVI showed that the classes describing single 
                         land cover types are properly defined since there is a well 
                         defined pattern of EVI profile. The classes describing a mixture 
                         of land cover types, showed similar temporal profiles of EVI and 
                         could not be well discriminated.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "498",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GDNB",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GDNB",
           targetfile = "p0498.pdf",
                 type = "Floresta e Vegeta{\c{c}}{\~a}o",
        urlaccessdate = "17 maio 2024"
}