@InProceedings{MoraesRoch:2011:ImCoQu,
               author = "Moraes, Rafael Aldighieri and Rocha, Jansle Vieira",
          affiliation = "{Universidade Estadual de Campinas – UNICAMP/FEAGRI} and 
                         {Universidade Estadual de Campinas – UNICAMP/FEAGRI}",
                title = "Imagens de coeficiente de qualidade (Quality) e de confiabilidade 
                         (Reliability) para sele{\c{c}}{\~a}o de pixels em imagens de 
                         NDVI do sensor MODIS para monitoramento da 
                         canade-a{\c{c}}{\'u}car no estado de S{\~a}o Paulo",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "547--552",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "vegetation index, MOD13Q1, time series, mask, {\'{\i}}ndice de 
                         vegeta{\c{c}}{\~a}o, MOD13Q1, s{\'e}ries temporais, 
                         m{\'a}scara.",
             abstract = "Estimating and monitoring sugarcane planted area is important, 
                         especially in S{\~a}o Paulo state, which accounts for 60 percent 
                         of production in Brazil. NDVI images from the MODIS (250m) have 
                         great potential for mapping sugarcane, mainly because it occupies 
                         large areas has a uniform canopy. However, the presence of noise 
                         and clouds in the images, degrades data and make analysis 
                         difficult. Our objective is to present a method to reduce presence 
                         of clouds or poor quality in NDVI images using VI Quality and 
                         Reliability data, present at MOD13Q1 product, during the sugarcane 
                         cycle for the 2008 - 2009 cropping season. We used 28 images, a 
                         mosaic of tiles h13v10 and h13v11, where the limits of Sao Paulo 
                         state were clipped. Thereafter, it was made the failed pixels 
                         separation by means of pre-established criteria and masks were 
                         generated for each image in which they were recorded and displayed 
                         in map form. The results showed that the NDVI images present a 
                         large concentration of failed pixels, mainly in the rainy season 
                         (spring and summer) and located in the southern region of the 
                         state. The conclusion is that the images of VI Quality and 
                         Reability allow to separate pixels with clouds and quality 
                         problems.",
  conference-location = "Curitiba",
      conference-year = "30 abr. - 5 maio 2011",
                 isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW/39UQR4B",
                  url = "http://urlib.net/ibi/3ERPFQRTRW/39UQR4B",
           targetfile = "p0376.pdf",
                 type = "Agricultura",
        urlaccessdate = "13 maio 2024"
}