@InProceedings{MeloFontBerl:2003:MoAgEs,
               author = "Melo, Ricardo Wanke de and Fontana, Denise Cybis and Berlato, 
                         Moacir Antonio",
          affiliation = "{Universidade Federal do Rio Grande do Sul (UFRGS). Faculdade de 
                         Agronomia.} and {Universidade Federal do Rio Grande do Sul 
                         (UFRGS). Faculdade de Agronomia.} and {Universidade Federal do Rio 
                         Grande do Sul (UFRGS). Faculdade de Agronomia.}",
                title = "Modelo agrometeorol{\'o}gico-espectral de estimativa de 
                         rendimento da soja para o Estado do Rio Grande do Sul",
            booktitle = "Anais...",
                 year = "2003",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria 
                         Garcia",
                pages = "173--179",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 11. (SBSR).",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "soybeans, crop yield estimation, NDVI, Rio Grande do Sul.",
             abstract = "The objective of this study was to fit and validate an 
                         agrometeorological-spectral model to estimate soybean yield in the 
                         State of Rio Grande do Sul, Brazil. The fitness was done using 
                         agrometeorological model (meteorological data from 1975 to 2000 of 
                         the seven weather stations located in the major soybean production 
                         region), spectral data (NDVI/NOAA images from 1982 to 2000) and 
                         soybean yield averaged over the State (official governmental 
                         statistics from 1975 to 2000). The parameters of the 
                         agrometeorological-spectral model were obtained through a linear 
                         multiple regression of the addition of agrometeorological term and 
                         spectral term. The model showed a good fit, with determination 
                         coefficient of 0,91. The model validation, done with independent 
                         data, had also a good performance, with determination coefficient 
                         of 0,88. The agrometeorological-spectral model produces the yield 
                         estimations before the end of the harvest with objectivity, 
                         swiftness and low cost, and could be incorporated into crop 
                         forecasting programs.",
  conference-location = "Belo Horizonte",
      conference-year = "5-10 abr. 2003",
                 isbn = "85-17-00017-X",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "ltid.inpe.br/sbsr/2002/11.13.11.52",
                  url = "http://urlib.net/ibi/ltid.inpe.br/sbsr/2002/11.13.11.52",
           targetfile = "01_128.pdf",
                 type = "Agronomia / Agriculture",
        urlaccessdate = "2024, May 08"
}