@InProceedings{GinoNegrSouz:2021:AnDeBa,
               author = "Gino, Vin{\'{\i}}cius L. S. and Negri, Rog{\'e}rio G. and 
                         Souza, Felipe N.",
          affiliation = "{Universidade Estadual Paulista (UNESP)} and {Universidade 
                         Estadual Paulista (UNESP)} and {Universidade Estadual Paulista 
                         (UNESP)}",
                title = "Anomaly detection based method for spatio-temporal dynamics 
                         mapping in dam mining regions",
            booktitle = "Anais...",
                 year = "2021",
               editor = "Vinhas, Lubia (INPE) and Gra{\c{c}}a, Alan J. Salom{\~a}o 
                         (UERJ)",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 22. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Remote Sensing technologies and Machine Learning methods rise as a 
                         potential combination to assemble new environmental monitoring 
                         applications. In this context, the presented work proposes a new 
                         method that exploits anomaly detection models applied to Remote 
                         Sensing imagery to identify the spatio-temporal changes over the 
                         Earths surface. The potential of the introduced approach is shown 
                         in a study case concerning the analysis of the landscape changes 
                         using One-Class SVM and Isolation Forest methods in Landsat and 
                         Sentinel images for Brumadinho and Mariana regions, Brazil, after 
                         its recent dam collapses.",
  conference-location = "On-line",
      conference-year = "29 nov. a 02 dez. 2021",
                 issn = "2179-4847",
             language = "en",
                  ibi = "8JMKD3MGPDW34P/45U7KGB",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34P/45U7KGB",
           targetfile = "Gino_anomaly.pdf",
        urlaccessdate = "16 jun. 2024"
}