@InProceedings{LucenaEsMaZaViFeQu:2020:BrDaCu,
               author = "Lucena, Felipe Rafael de S{\'a} Menezes and Escobar-Silva, Elton 
                         Vicente and Marujo, Rennan de Freitas Bezerra and Zaglia, Matheus 
                         Cavassan and Vinhas, Lubia and Ferreira, Karine Reis and Queiroz, 
                         Gilberto Ribeiro de",
          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)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Brazil Data Cube Cloud Coverage (BDC3) Viewer",
            booktitle = "Anais...",
                 year = "2020",
               editor = "Carneiro, Tiago Garcia de Senna (UFOP) and Felgueiras, Carlos 
                         Alberto (INPE)",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 21. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "banon.",
             abstract = "Remotely sensed Earth Observation (EO) data have exceeded a large 
                         scale and are increasingly available for different communities and 
                         thematic applications. In this matter, EO Data Cubes (EODC) are a 
                         promising solution to efficiently manage big EO data, enabling its 
                         access, processing and analysis. As final products, EODC provides 
                         analysis-ready data (ARD) for vegetation and land use and land 
                         cover (LULC) studies, for environmental monitoring urban growth 
                         studies, among others. One of the most used pre- selection 
                         criteria for image retrieval of big EO data is the average cloud 
                         cover statistic. This paper describes our initiative in the 
                         implementation of an on- demand view-based tool for cloud coverage 
                         embedded on the Brazil Data Cube (BDC) project based on the 
                         SpatioTemporal Asset Catalog (STAC).",
  conference-location = "On-line",
      conference-year = "30 nov. a 03 dez. 2020",
                 issn = "2179-4847",
             language = "en",
                  ibi = "8JMKD3MGPDW34P/43PR3A2",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34P/43PR3A2",
           targetfile = "s11.pdf",
                 type = "Geoinforma{\c{c}}{\~a}o",
        urlaccessdate = "28 abr. 2024"
}