@InProceedings{Arenas-ToledoEpip:2009:CrPaEx,
               author = "Arenas-Toledo, John Mauricio and Epiphanio, Jos{\'e} Carlos 
                         Neves",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Crop patterns extraction derived by classic Fourier analysis of 
                         EVI-MODIS time-series data to support crop discrimination",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "83--90",
         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 = "annual crops, Fourier series, harmonic terms, per-pixel 
                         classification.",
             abstract = "The current economic panorama with market crises, food crises, 
                         bio-fuels expansions, commodities crush down, etc. makes 
                         absolutely relevant for any country to setup agriculture 
                         information in a quick and operational way. In this complicated 
                         scenario we proposed an approach to perform crop discrimination 
                         based on crop patterns of major annual crops in Mato Grosso State, 
                         known as one of the largest world agriculture frontier. This 
                         region is a large agriculture producer, especially of soybean, 
                         cotton and maize. These annual crops have a short cycle, which 
                         makes crop monitoring hard to achieve only by using medium spatial 
                         resolution imagery because there is a coincidence with a period of 
                         high cloud cover, particularly during the summer season. 
                         Lowerorder harmonic terms derived from Time-series of EVI MODIS 
                         were related to crop patterns. We found that cotton areas were 
                         modeled by first-order term and succession soybean and second 
                         maize crop known as safrinha were modeled by second-order term. 
                         Per-pixel classifications of harmonic terms reached accuracies of 
                         90% for harmonic terms.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.17.12.05",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.12.05",
           targetfile = "83-90.pdf",
                 type = "Agricultura",
        urlaccessdate = "16 jun. 2024"
}