@InProceedings{NascimentoZullRodr:2009:AsMiDa,
               author = "Nascimento, Cristina Rodrigues and Zullo Junior, Jurandir and 
                         Rodrigues, Luiz Henrique Antunes",
          affiliation = "UNICAMP/CEPAGRI and UNICAMP/CEPAGRI and UNICAMP/FEAGRI",
                title = "Associa{\c{c}}{\~a}o de minera{\c{c}}{\~a}o de dados e imagens 
                         do sensor AVHRR/NOAA na busca de padr{\~o}es para 
                         identifica{\c{c}}{\~a}o de {\'a}reas com 
                         cana-de-a{\c{c}}{\'u}car no Estado de S{\~a}o Paulo",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7845--7853",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Image processing, Harmonic Analysis, NDVI, Processamento de 
                         imagens, An{\'a}lise Harm{\^o}nica, NDVI.",
             abstract = "Brazil is the first producer of sugar cane in the world. Despite 
                         the economic and social importance of agribusiness to Brazil, it 
                         is still very difficult to estimate the harvest of the its main 
                         crops with the precision and anticipation needed, justifying the 
                         study and development of new methods based on the use of remote 
                         sensing data. The use of time series of AVHRR/NOAA images 
                         presented a very satisfactory outcome, allowing an increase of the 
                         objectivity of the methods of agricultural monitoring. The study 
                         aims to evaluate the application of harmonic analysis in the time 
                         series of images AVHRR/NOAA-17 aimed at identifying areas with 
                         sugar cane in S{\~a}o Paulo state. In an analysis was first 
                         tested the feasibility of the methodology and use of the technique 
                         of decision trees in search of patterns that can be applied to 
                         characterize the growing season 2006/2007. the images generated 
                         from the application of harmonic analysis in the time series show 
                         promise for the identification of areas with sugar cane in the 
                         state. The methodology discussed in the patterns of 
                         discrimination, from the application of algorithms, decision tree, 
                         has proved efficient, but it is limited as the difficulty in 
                         locating space of the pixels with such characteristics.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.18.01.25",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.18.01.25",
           targetfile = "7845-7853.pdf",
                 type = "T{\'e}cnicas de Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o 
                         de Dados",
        urlaccessdate = "18 jun. 2024"
}