%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16c/2020/12.15.13.30
%2 sid.inpe.br/mtc-m16c/2020/12.15.13.30.08
%@issn 2179-4847
%T Brazil Data Cube Cloud Coverage (BDC3) Viewer
%D 2020
%A Lucena, Felipe Rafael de Sá Menezes,
%A Escobar-Silva, Elton Vicente,
%A Marujo, Rennan de Freitas Bezerra,
%A Zaglia, Matheus Cavassan,
%A Vinhas, Lubia,
%A Ferreira, Karine Reis,
%A Queiroz, Gilberto Ribeiro de,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress felipe.lucena@inpe.br
%@electronicmailaddress elton.silva@inpe.br
%@electronicmailaddress rennan.marujo@inpe.br
%@electronicmailaddress matheus.zaglia@inpe.br
%@electronicmailaddress lubia.vinhas@inpe.br
%@electronicmailaddress karine.ferreira@inpe.br
%@electronicmailaddress gilberto.queiroz@inpe.br
%E Carneiro, Tiago Garcia de Senna (UFOP),
%E Felgueiras, Carlos Alberto (INPE),
%B Simpósio Brasileiro de Geoinformática, 21 (GEOINFO)
%C On-line
%8 30 nov. a 03 dez. 2020
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%S Anais
%K banon.
%X 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).
%9 Geoinformação
%@language en
%3 s11.pdf