@InProceedings{JungesFont:2011:PeTeND,
               author = "Junges, Amanda Heemann and Fontana, Denise Cybis",
          affiliation = "{Universidade Federal do Rio Grande do Sul - UFRGS} and 
                         {Universidade Federal do Rio Grande do Sul - UFRGS}",
                title = "Perfis temporais de NDVI/MODIS de {\'a}reas agr{\'{\i}}colas de 
                         outono-inverno, na regi{\~a}o de Passo Fundo (RS), provenientes 
                         de m{\'a}scara de cultivos e classifica{\c{c}}{\~a}o n{\~a}o 
                         supervisionada",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "31--38",
         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 = "winter cereals, black oat, pastures, cereais de inverno, aveia 
                         preta, pastagens.",
             abstract = "This study aimed to elaborate temporal NDVI/MODIS profiles for 
                         cropping areas, with the main purpose to distinguish winter 
                         cereals among other crops, in the region of Passo Fundo (RS, 
                         Brazil). The data set comprised 17 NDVI/MODIS images, from April 
                         to December of the 2000-2008 series. Firstly, crop masks were 
                         elaborated by subtracting the minimum NDVI image (April to May) 
                         from the maximum NDVI image (June to October). Then, an 
                         unsupervised classification of NDVI/MODIS images was carried out, 
                         considering the crop masking areas. The Isodata algorithm was used 
                         in this classification (five to ten classes and 100 iterations). 
                         According to results, the method of crop masking allowed to 
                         identify cropping areas with high NDVI variation, from April to 
                         December. The unsupervised classification could distinguish five 
                         crop classes. Temporal NDVI/MODIS profiles from these classes were 
                         in agree with several crop patterns (e.g. sowing period, plant 
                         growth and developmental stage, as well as management standard) 
                         for most winter crops. Those classes were named as winter cereals 
                         (class 2), black oat for soil covering before either soybeans 
                         (class 3) or maize (class 4), and pastures (class 5). Therefore, 
                         unsupervised classification based on crop masking allows 
                         distinguishing the temporal NDVI profile of winter cereals crops, 
                         in comparison to temporal NDVI profiles of other cropping areas.",
  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/3A44G78",
                  url = "http://urlib.net/ibi/3ERPFQRTRW/3A44G78",
           targetfile = "p0453.pdf",
                 type = "Agricultura",
        urlaccessdate = "04 jun. 2024"
}