@InProceedings{AntunesEsqu:2009:MoAgUs,
               author = "Antunes, Jo{\~a}o Francisco Gon{\c{c}}alves and Esquerdo, 
                         J{\'u}lio C{\'e}sar Dalla Mora",
          affiliation = "{Embrapa Inform{\'a}tica Agropecu{\'a}ria/SP} and {Embrapa 
                         Inform{\'a}tica Agropecu{\'a}ria/SP}",
                title = "Monitoramento agr{\'{\i}}cola usando an{\'a}lise harm{\^o}nica 
                         de s{\'e}ries temporais de dados NDVI/AVHRR-NOAA",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "49--55",
         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 = "remote sensing, image processing, temporal profiles, sensoriamento 
                         remoto, processamento de imagens, perfis temporais.",
             abstract = "High temporal resolution images obtained from NOAA satellites have 
                         been used to monitor the most important crops in Brazil, such as 
                         soybeans and maize. The harmonic analysis is a technique that is 
                         being applied to time series of remote sensing imagery to 
                         characterize the phenology of vegetation and to better understand 
                         its dynamics. This study aimed to monitor the crop lands in the 
                         west of Paran{\'a} State during the 2006/2007 and 2007/2008 
                         cropping seasons through NDVI/NOAA data and harmonic analysis. The 
                         NDVI temporal profiles, smoothed by HANTS algorithm, have shown 
                         that the annual crops have greater amplitude of NDVI values due to 
                         the temporal variation of biomass. The HANTS algorithm has removed 
                         noises caused by NDVI changes due to clouds and also predicted the 
                         trends of the curve in missing data periods. The relationship 
                         between NDVI and climatic variables can point out the productive 
                         potential of agricultural crops and the analysis of temporal 
                         profiles allowed to compare the nowadays conditions to previous 
                         cropping seasons conditions. The systems presented by this study 
                         showed to be an important tool for NOAA's image users, mainly 
                         those who need to process long time series and to generate 
                         temporal profiles of spectral and meteorological data in an 
                         automatic way.",
  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@80/2008/11.17.15.51.23",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.15.51.23",
           targetfile = "49-55.pdf",
                 type = "Agricultura",
        urlaccessdate = "15 jun. 2024"
}