@InProceedings{AlmeidaGonUnaFreKle:2023:ClToEs,
               author = "Almeida, Luis Pedro and Gon{\c{c}}alves, Rafael Queiroz and Unas, 
                         Pedro and Freitas, Lais Pool S. and Klein, Antonio H. F.",
          affiliation = "{CoLAB + ATLANTIC} and {Universidade do Vale do Itaja{\'{\i}} 
                         (UNIVALI)} and {CoLAB + ATLANTIC} and {Universidade Federal do Rio 
                         Grande do Sul (UFRGS)} and {Universidade Federal de Santa Catarina 
                         (UFSC)}",
                title = "Cloud-based tool to estimate shallow water bathymetry using 
                         satellite optical imagery",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e156475",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 20. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Bathymetry, shallow water, satellite imagery, Google Earth 
                         Engine.",
             abstract = "Shallow water bathymetry is crucial for navigation and to 
                         understand complex underwater morphodynamic processes in coastal 
                         areas. Satellite derived bathymetry (SDB) is an useful 
                         methodological approach that have the potential to overcome 
                         limitations of traditional in-situ approaches, namely the limited 
                         spatial coverage and costs related with the repetitiveness. In the 
                         present work we present a new tool, the CASSIE Bathymetry module, 
                         that enables SDB, based on optical inversion approach, to be 
                         applied at any coastal region of the world. To implement this 
                         tool, user require a minimal training dataset of observed depths, 
                         that is used to calibrate the SDB algorithm and to estimate errors 
                         of the estimated depths. This new tool is freely accessible via 
                         www.cassiengine.org.",
  conference-location = "Florian{\'o}polis",
      conference-year = "02-05 abril 2023",
                 isbn = "978-65-89159-04-9",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/48TM3L5",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/48TM3L5",
           targetfile = "156475.pdf",
                 type = "Sistemas marinhos costeiros",
        urlaccessdate = "04 maio 2024"
}