@InProceedings{MartinsGalVieJorAlm:2017:UsMoEm,
               author = "Martins, George Deroco and Galo, Maria de Lourdes Bueno Trindade 
                         and Vieira, Bruno S{\'e}rgio and Jorge, Ricardo Falqueto and 
                         Almeida, Cinara Xavier",
                title = "Uso de modelos emp{\'{\i}}ricos obtidos a partir de imagens 
                         RapidEye para estimar a concentra{\c{c}}{\~a}o de nutrientes no 
                         cafeeiro infectada por nematoides",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4298--4305",
         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 = "Seeking the improvement of crop productivity, radiometric models 
                         and vegetation indexes derived from image data, obtained by remote 
                         sensing, has been used for control and continuous monitoring of 
                         agricultural areas. From empiric models, it is possible to 
                         estimate the nutrients concentration and health parameters of 
                         plants infected by pathogens. Regarding this statement, the goal 
                         of this study was to evaluate the potential of empiric models to 
                         estimate the nutrients concentration in coffee culture infected by 
                         nematodes. The empiric models were generated using original bands 
                         and vegetation indexes derived from a RapidEye scene. In this 
                         approach, it was possible to estimate the concentration of 
                         potassium (K) and calcium (Ca) from empiric models, derived from 
                         vegetation index SR (simple reason), with a RMSE of 14.7% and 
                         7.5%, respectively. With a model derived from the near-infrared 
                         band was possible to estimate the concentration of boron (B) with 
                         a RMSE of 13.3%.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59297",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM2RB",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM2RB",
           targetfile = "59297.pdf",
                 type = "Produ{\c{c}}{\~a}o e previs{\~a}o agr{\'{\i}}cola",
        urlaccessdate = "27 abr. 2024"
}