@InProceedings{SilvaGrzJohPalJún:2015:EsÁrPl,
               author = "Silva, La{\'{\i}}za Cavalcante de Albuquerque and Grzegozewski, 
                         Denise Maria and Johann, Jerry Adriani and Paloschi, Rennan Andres 
                         and J{\'u}nior, Cl{\'o}vis Cechim",
                title = "Estimativa de {\'a}rea plantada com soja e milho, safra 
                         2013/2014, no Oeste paranaense utilizando um mapa de alvos 
                         permanentes",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4270--4277",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The west of Paran{\'a} is characterized by corn and soybean 
                         cultivation in spring and summer seasons. As the agricultural 
                         sector has an important participation in economy, it is important 
                         to develop a reliable estimation of the crop area of each culture, 
                         aiming to provide solid information to assist government 
                         departments to make decisions. This paper aims to estimate the 
                         crop area of corn and soybean for the 2013/2014 harvest, using 
                         scenes from the Modis and Landsat-8 sensors. A time-spectral 
                         series of EVI from the Modis Sensor was used and, after the 
                         smoothing process flat smoother filter was applied to reduce 
                         noise, it was possible to establish minimum EVI (sowing and 
                         initial development phase) and maximum EVI (maximum development 
                         phase) images. For the supervised classification process the SAM 
                         algorithm (Spectral Angle Mapper Targets Finder with BandMax) had 
                         been used together with the time-spectral EVI profile of the 
                         control classes (forest, reforested area and city), generating a 
                         map of the regions soil use and occupation. Also, after the soil 
                         use and permanent target mapping, the arithmetic band technique 
                         was used to compose a new estimation, which showed greater 
                         accuracy (global accuracy: 90.5%; kappa index: 0.8110) when 
                         compared to the preliminary estimation. The obtained data was 
                         compared with the official data (available from SEAB). The SAM 
                         classification improved the initial estimation and reduced the 
                         masks noise, evidencing its effectiveness and applicability.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "837",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4CJS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4CJS",
           targetfile = "p0837.pdf",
                 type = "An{\'a}lise de s{\'e}ries de tempo de imagens de sat{\'e}lite",
        urlaccessdate = "05 maio 2024"
}