@InProceedings{SarmientoInaColFerAlv:2017:DiFeCu,
               author = "Sarmiento, Christiany Mattioli and Inacio, Franklin Daniel and 
                         Coltri, Priscila Pereira and Ferreira, Rute Costa and Alves, 
                         Marcelo de Carvalho",
          affiliation = "{} and {} and {} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Din{\^a}mica fenol{\'o}gica da cultura da soja e sua 
                         correla{\c{c}}{\~a}o com vari{\'a}veis espectrais",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "7264--7271",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Soybeans are the main agricultural product exported in Brazil and 
                         its production is mostly concentrated in the state of Mato Grosso. 
                         Due to the importance of culture at local, regional and global 
                         level, it is necessary to monitor its agricultural production. 
                         Monitoring and forecasting of soybeans are determinant factors for 
                         the agricultural market and can be achieved through methods of 
                         estimating productivity using robust and accurate techniques 
                         throughout the crop cycle. More recent studies have used satellite 
                         imagery to evaluate large areas at lower costs. This paper 
                         describes the development of a geographic database for 
                         visualization and analysis of temporal profiles of vegetative 
                         development and precipitation in comparison with the productivity 
                         corresponding to the crop of 2012/2013 in agglomerates producing 
                         soybeans in the state of Mato Grosso. Data collected in the field 
                         regarding the productivity of each plot were analyzed, images of 
                         satellites of high temporal resolution, referring to accumulated 
                         precipitation every 3 hours by means of 3B42RT products, corrected 
                         by the MERGE technique, NDVI and EVI vegetation indices from 
                         MOD13Q1 and MYD13Q1 products, obtained by the MODIS sensor, Terra 
                         and Aqua satellites, respectively, and evapotranspiration data, 
                         obtained through the products MOD16A2, MODIS sensor, Terra 
                         satellite. Through the results it was observed that there is a 
                         strong positive and negative correlation 56 days after the 
                         planting date.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59969",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMFDB",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMFDB",
           targetfile = "59969.pdf",
                 type = "Agricultura e silvicultura",
        urlaccessdate = "27 abr. 2024"
}