@InProceedings{SimõesQueFerVinCâm:2016:ToSpPo,
               author = "Sim{\~o}es, Rolf Ezequiel de Oliveira and Queiroz, Gilberto 
                         Ribeiro de and Ferreira, Karine Reis and Vinhas, L{\'u}bia and 
                         C{\^a}mara, Gilberto",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "PostGIS-T: towards a spatiotemporal PostgreSQL database 
                         extension",
            booktitle = "Anais...",
                 year = "2016",
         organization = "Brazilian Symposium on GeoInformatics, 17. (GEOINFO)",
             abstract = "The temporal dimension of spatial data has been the subject of 
                         discussion in the literature for a long time. While there are 
                         numerous Database Management System (DBMS) solutions only for 
                         spatial dimension, we did not observe the same situation for 
                         spatiotemporal data. Considering this gap, our purpose is to 
                         design and implement an extension to the DBMS PostgreSQL that is 
                         based on a formal spatiotemporal algebra in order to incorporate 
                         representations of spatiotemporal data within the DBMS. The 
                         proposed extension can be used in a large range of applications. 
                         We intend that this extension be a reasonable framework to store 
                         and handling observational remote sensing data usually present in 
                         applications like animal migration researches, wildfires 
                         monitoring, vessel tracking for monitoring fishing, and the like. 
                         In this work, we show how to apply it in a case study based on 
                         spatiotemporal data collected from drifting buoys belonging to the 
                         NOOAs Global Drifter Program.",
  conference-location = "Campos do Jord{\~a}o, SP",
      conference-year = "27-30 nov. 2016",
             language = "en",
                  ibi = "8JMKD3MGP3W34P/3N2UAT8",
                  url = "http://urlib.net/ibi/8JMKD3MGP3W34P/3N2UAT8",
           targetfile = "rolf.pdf",
        urlaccessdate = "27 abr. 2024"
}