@InProceedings{CarlosMartBarb:2019:SiSeCo,
               author = "Carlos, Felipe Menino and Martins, Vitor de Souza and Barbosa, 
                         Cl{\'a}udio Clemente Faria",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Iowa State 
                         University} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Sistema semi-autom{\'a}tico de corre{\c{c}}{\~a}o 
                         atmosf{\'e}rica para multi-sensores orbitais",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "1508--1511",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Python, 6SV, Corre{\c{c}}{\~a}o atmosf{\'e}rica, Python, 6SV, 
                         Atmospheric correction.",
             abstract = "A acur{\'a}cia da corre{\c{c}}{\~a}o atmosf{\'e}rica para o 
                         monitoramento de sistemas aqu{\'a}ticos {\'e} extremamente 
                         importante, por estes ambientes apresentarem reflect{\^a}ncia 
                         espectral normalmente baixa. Alguns estudos vem mostrando que a 
                         aplica{\c{c}}{\~a}o do modelo 6SV de corre{\c{c}}{\~a}o 
                         atmosf{\'e}rica, apresenta bons resultados para estes ambientes. 
                         Por{\'e}m a usabilidade e automatiza{\c{c}}{\~a}o deste modelo 
                         s{\~a}o baixas, por necessitar de recursos n{\~a}o presentes nos 
                         metadados das imagens, al{\'e}m da baixa intuitividade na 
                         utiliza{\c{c}}{\~a}o. Com o objetivo de facilitar a 
                         aplica{\c{c}}{\~a}o deste modelo e de acelerar o procedimento de 
                         corre{\c{c}}{\~a}o atmosf{\'e}rica em imagens dos sensores 
                         Sentinel- 2/MSI, Landsat-8/OLI e Sentinel-3/OLCI desenvolveu-se um 
                         sistema na linguagem de programa{\c{c}}{\~a}o Python, junto a 
                         alguns pacotes auxiliares. Os resultados obtidos atrav{\'e}s do 
                         programa foram validados por pesquisadores e alunos de 
                         p{\'o}s-gradua{\c{c}}{\~a}o do Laborat{\'o}rio de 
                         Instrumenta{\c{c}}{\~a}o de Sistemas Aqu{\'a}ticos 
                         (http://www.dpi.inpe.br/labisa/). ABSTRACT: The accuracy of the 
                         atmospheric correction for the monitoring of aquatic systems is 
                         extremely important because these environments have normally low 
                         spectral reflectance. Some studies have shown that the application 
                         of the 6SV model of atmospheric correction present good results 
                         for these environments. However, the usability and automation of 
                         this model are low, because it requires resources not present in 
                         the metadata of the images, besides the low intuitiveness in the 
                         use. In order to facilitate the application of this model and to 
                         accelerate the procedure of atmospheric correction in images of 
                         the Sentinel-2 / MSI, Landsat-8 / OLI, and Sentinel-3 / OLCI 
                         sensors, a system was developed in the Python programming language 
                         with some auxiliary packages. The results obtained through the 
                         program were validated by researchers and graduate students of the 
                         Laboratory of Instrumentation of Aquatic Systems 
                         (http://www.dpi.inpe.br/labisa/).",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3UA4FG2",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3UA4FG2",
           targetfile = "97884.pdf",
                 type = "Sensoriamento remoto de {\'a}guas interiores",
        urlaccessdate = "27 abr. 2024"
}