author = "Picoli, Michelle Cristina Araujo and Rocha, Jansle Vieira and 
                         Esquerdo, J{\'u}lio C{\'e}sar Dalla Mora and Lamparelli, Rubens 
                         Augusto Camargo",
          affiliation = "{Universidade Estadual de Campinas-UNICAMP-FEAGRI/SP} and 
                         {Universidade Estadual de Campinas-UNICAMP-FEAGRI/SP} and {Embrapa 
                         Inform{\'a}tica Agropecu{\'a}ria/SP} and {Centro de Pesquisas 
                         Meteorol{\'o}gicas Aplicadas a Agricultura-CEPAGRI/SP}",
                title = "O uso de m{\'a}scaras para sele{\c{c}}{\~a}o autom{\'a}tica de 
                         {\'a}reas plantadas com soja no estado de S{\~a}o Paulo",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                pages = "333--338",
         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, area estimates, NDVI.",
             abstract = "This paper aimed to develop an automatic procedure for soybean 
                         crop identification in the State of S{\~a}o Paulo. Official 
                         statistics from IBGE (Instituto Brasileiro de Geografia e 
                         Estat{\'{\i}}stica) were used as reference of soybean planted 
                         area. The method proposed by this study is based on the temporal 
                         variation of the NDVI (Normalized Difference Vegetation Index) in 
                         agricultural areas. Time series of Moderate Resolution Imaging 
                         Spectroradiometer (MODIS) imagery were acquired between January 
                         2003 and May 2008. The HANTS (Harmonic Analysis of NDVI 
                         Time-Series) algorithm was used to filter the time series through 
                         low frequency sine functions to represent the seasonal effect of 
                         the vegetation development. The soybean mask was built according 
                         to the seasonal variation of the soybean pixels. Results have 
                         showed that, although the method has overestimated the soybean 
                         planted areas, it can help government agencies in generating 
                         agricultural statistics. At the municipal scale, the coefficient 
                         of determination (R2) was always greater than 0,7.",
      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 = "333-338.pdf",
                 type = "Agricultura",
        urlaccessdate = "18 jan. 2021"