@InProceedings{OrtizKamp:2017:MaFrIn,
               author = "Ortiz, Gustavo Prouvot and Kampel, Milton",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Mapeamento da frente interna da Corrente do Brasil com o uso de 
                         imagens orbitais de temperatura da superf{\'{\i}}cie do mar e 
                         concentra{\c{c}}{\~a}o de clorofila-a",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3146--3151",
         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 = "The article presents a dataset comprehending 1,094 Brazil Current 
                         inner fronts mapped from January-2011 to September-2015, using Sea 
                         Surface Temperature (SST) and Chlorophyll-a (Cl-a) orbital images, 
                         over the Esp{\'{\i}}rito Santo, Campos, Santos and northern 
                         Pelotas Basins, SW Atlantic. 319 fronts were mapped in Summer, 264 
                         in Autumn, 308 in Winter and 203 in Spring. The resulting frontal 
                         density fields indicate higher frontal spatial stability over 
                         three areas under the influence of semi-permanent eddies: (i) 
                         S{\~a}o Tom{\'e} Eddy, (ii) Cabo Frio Eddy and (iii) Shelf break 
                         eddy near S{\~a}o Sebasti{\~a}o Island. The Vit{\'o}ria Eddy 
                         signal was observed at the Winter frontal density field. The 
                         frontal occurrence distribution profiles, extracted from four 
                         radial transects, show different variability and position patterns 
                         over the study area. That present extensive Brazil Current fronts 
                         dataset can be used to feed descriptive statistical models or as a 
                         training dataset for a machine learning algorithm in order to 
                         improve the knowledge about the Brazil Current characteristics.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59865",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLSBS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLSBS",
           targetfile = "59865.pdf",
                 type = "Oceanografia e sistemas costeiros",
        urlaccessdate = "27 abr. 2024"
}