@InProceedings{ChavesAlve:2017:AvMaLa,
               author = "Chaves, Michel Eust{\'a}quio Dantas and Alves, Marcelo de 
                         Carvalho",
                title = "Avalia{\c{c}}{\~a}o do mapeamento das lavouras de soja em Mato 
                         Grosso na safra 2010/2011 realizado pelo projeto Soja Sat",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5872--5879",
         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 State of Mato Grosso is characterized by soybean cultivation 
                         in summer seasons. As the agricultural sector has an important 
                         participation in economy, the implementation of monitoring and 
                         systematic mapping tools is important for the strategic planning. 
                         Facing this demand, the connection of field data, orbital data and 
                         geostatistical techniques appears as a tool in the attempt to 
                         ensure accuracy of the generated information. This paper presents 
                         and evaluates the Soja Sat initiative, which aimed to map the 
                         areas cultivated with soybeans in Mato Grosso between the 
                         2000/2001 and 2010/2011 harvests. A combination of field data, 
                         which was obtained in partnership with Bom Futuro SA Group, daily 
                         vegetation data, which was derived from the Enhanced Vegetation 
                         Index (EVI) derived from the Moderate Resolution Imaging 
                         Spectroradiometer (MODIS), that is sensitive to biomass variations 
                         during the phenological cycle and geostatistical techniques were 
                         used. The period of analysis for validation involved the 2010/2011 
                         harvest due to the relevance in the production and the 
                         availability of geographical delimitation. Aiming at validating 
                         and demonstrating the accuracy of the mapping, 5 agglomerates of 
                         farms were chosen for reference. Subsequently, from a point 
                         analysis of the soybean plots and a reference map that is derived 
                         from the TerraClass project, reliability indexes were generated 
                         through a confusion matrix. The results obtained presented high 
                         agreement with the field data. The Global Accuracy (0.92) and the 
                         Kappa Index (0.84) indicated that the proposed method was 
                         efficient for the mapping soybean crops in the 2010/2011 harvest 
                         in Mato Grosso.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59339",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMBRP",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMBRP",
           targetfile = "59339.pdf",
                 type = "Geoprocessamento e aplica{\c{c}}{\~o}es",
        urlaccessdate = "27 abr. 2024"
}