author = "Adami, Marcos and Moreira, Mauricio Alves and Barros, Marco 
                         Aur{\'e}lio and Martins, Vagner Azarias and Rudorff, Bernardo 
                         Friedrich Theodor",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {GEOAMBIENTE 
                         Sensoriamento Remoto Ltda} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                title = "Avalia{\c{c}}{\~a}o da exatid{\~a}o do mapeamento da cultura do 
                         caf{\'e} no Estado de Minas Gerais",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                pages = "1--8",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "remote sensing, sampling, error matrix, sensoriamento remoto, 
                         amostragem, matriz de erros.",
             abstract = "Accurate and updated agricultural statistics on coffee crop area 
                         estimation, based on an objective method, is not available. Remote 
                         sensing images are an important source of information to estimate 
                         crop area, especially when crop identification procedure is 
                         carried out in an effective way. The objective of the present work 
                         is to evaluate a coffee crop map obtained from remote sensing 
                         images in the state of Minas Gerais. In the adopted method the 
                         samples were randomly selected within strata obtained in a two 
                         stage stratification. In the first stage five strata were obtained 
                         based on both percent of coffee area and regional crop management 
                         characteristics. In the second stage the strata were divided into 
                         areas with and without coffee crop. For each stratum 52 samples 
                         were randomly selected. Prior to the field work the samples were 
                         visually identified on both high spatial resolution images 
                         available in Google Earth and recent Landsat images used to 
                         perform the map. Several samples could be clearly identified as 
                         coffee or non-coffee reducing drastically the field work. 
                         Confusion matrix was used to provide the global accuracy index, 
                         the consumer accuracy and the producer accuracy for each stratum. 
                         Overall mapping accuracy for strata 1, 2, 3, 4 and 5 were 99%, 
                         90%, 95%, 86% and 83%, respectively. Global mapping accuracy for 
                         Minas Gerais was 95%. It was observed that the mapping accuracy is 
                         related to: a) regional vegetation that may cause confusion with 
                         coffee; b) cultural practices; c) crop management; and d) 
      accessionnumber = "0",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/",
                  url = "http://urlib.net/rep/dpi.inpe.br/sbsr@80/2008/",
           targetfile = "1-8.pdf",
                 type = "Agricultura",
        urlaccessdate = "15 jan. 2021"