@InProceedings{FoschieraMellAtzbForm:2015:SuYiEs,
               author = "Foschiera, William and Mello, Marcio Pupin and Atzberger, Clement 
                         and Formaggio, Ant{\^o}nio Roberto",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and {} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Sugarcane yield estimation in S{\~a}o Paulo State - Brazil",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4329--4336",
         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 = "This paper presents a method for crop yield forecast based on 
                         remote sensing and official data. The method uses a statistical 
                         approach to extract different pixels of smoothed NDVI data derived 
                         from MODIS sensor to be used as proxies for sugarcane yield 
                         estimation at a municipal scale. From 368 municipalities with 
                         yield''s historical data from 2003 to 2012, three groups were 
                         created based on acreage percentile and then 30 municipalities was 
                         randomly selected, 10 for each group. Two municipalities with 
                         extreme acreage values (minimum and maximum) were discarded from 
                         each group and two different approaches were tested to normalize 
                         yield data and NDVI: Zscore and Rscore. In addition, two methods 
                         were used as selection criteria: RMSE and Spearman''s correlation. 
                         Results showed that municipalities with large sugarcane acreage 
                         tended to present better agreement between observed and estimated 
                         yield, which reinforce the potential of this method to be 
                         operationally used for sugarcane yield forecast over large areas. 
                         Moreover, the proposed method may estimate yield early in crop 
                         season, whereas official statistics are usually published late 
                         after harvest.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "847",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4CLL",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4CLL",
           targetfile = "p0847.pdf",
                 type = "An{\'a}lise de s{\'e}ries de tempo de imagens de sat{\'e}lite",
        urlaccessdate = "27 abr. 2024"
}