@InProceedings{BernardesAdamMore:2015:MoDaEs,
               author = "Bernardes, Tiago and Adami, Marcos and Moreira, Mauricio Alves",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Modelagem de dados espectrais e meteorol{\'o}gicos na 
                         produtividade da cultura do caf{\'e}",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3911--3918",
         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 = "Remote sensing and meteorological data were used to model coffee 
                         yield on the South of Minas Gerais state. Several vegetation 
                         indices derived parameters were applied to estimate an indicator 
                         factor of biennial bearing effect on coffee yield and to be 
                         incorporated into the agrometeorological model to estimate yield. 
                         The final model penalizes the potential yield as a function of: i) 
                         relative evapotranspiration (water penalization) obtained from 
                         meteorological data and ii) yield of previous year. Meteorological 
                         data were obtained from the regional weather prediction model ETA, 
                         and the yield of previous year was estimated from relationships 
                         between yield and remote sensing derived vegetation indices. The 
                         final model was evaluated at two levels: coffee plots and 
                         municipalities. Overall performance of the model at the level of 
                         coffee plots was considered inconclusive errors varying from 13,73 
                         to 17,46 60-kg bags of green coffee per hectare (MSE) and 18,51 to 
                         23,15 60-kg bags of green coffee per hectare (RMSE), R2 values 
                         varying from 0,50 to 0,69, d1 index from 0,45 to 0,53 and d2 index 
                         from 0,59 a 0,70. At the level of municipality the performance was 
                         considerably better errors varying from 1.607 to 2.147 kg (MSE) 
                         and 2.490 to 3.526 kg (RMSE), R2 values varying from 0,86 to 0,93, 
                         d1 index from 0,78 to 0,83 and d2 index from 0,92 to 0,96.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "776",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4C8E",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4C8E",
           targetfile = "p0776.pdf",
                 type = "Produ{\c{c}}{\~a}o e previs{\~a}o agr{\'{\i}}cola",
        urlaccessdate = "27 abr. 2024"
}