%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.16.22.42
%2 sid.inpe.br/marte2/2017/10.27.16.22.43
%@isbn 978-85-17-00088-1
%F 59372
%T Análise e Processamento Automático de Grandes Volumes de Dados Ambientais (Big Earth Observation Data Sets)
%D 2017
%A Cunha, John Elton de Brito Leite,
%A Rufino, Iana Alexandra Alves,
%A Galvão, Carlos de Oliveira,
%A Perreira, Thiago Emmanuel,
%A Brasileiro, Francisco Vilar,
%A Perreira, Esdras Vidal,
%@electronicmailaddress john.e.cunha@gmail.com
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 7459-7466
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X Hydrology and water resources demand monitoring land use and cover, related to the impacts of climate and human action. However, very often data for such monitoring and sequent analysis are from spatial scales that cannot be fully collected by field survey. Remote sensing techniques and data are suitable to those needs, since include land use/land cover changes detection in different scales (from local to continental landscapes). This paper presents an intercontinental initiative: the EUBrazil Cloud Connect project, developed by European and Brazilian partners. The main goal is to provide a cloud computing infrastructure to use tools for multi-temporal analysis and trend analysis of huge remote sensing databases to understand the main current drivers of land use changes. SEBAL (Surface Energy Balance Algorithm for Land) algorithm has been processed for a long time series (more than 30 years of satellite images) covering the whole Brazilian semi-arid area. Web services for visualization, analysis and deployment for decision makers and researchers are used.
%9 Análise de séries temporais de imagens de satélite
%@language pt
%3 59372.pdf