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		<citationkey>GomesSatQueVinFer:2016:AvExPo</citationkey>
		<title>Gerenciamento de nuvem de pontos em SGBD: avaliando a extensao PointCloud para PostgreSQL</title>
		<year>2016</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Gomes, Vitor C. F.,</author>
		<author>Sato, Luciane Yumie,</author>
		<author>Queiroz, Gilberto Ribeiro de,</author>
		<author>Vinhas, Lúbia,</author>
		<author>Ferreira, Karine Reis,</author>
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		<affiliation>Instituto de Estudos Avançados (IEAv)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>vitor@ieav.cta.br</electronicmailaddress>
		<electronicmailaddress>lusato@dsr.inpe.br</electronicmailaddress>
		<electronicmailaddress>gilberto.queiroz@inpe.br</electronicmailaddress>
		<electronicmailaddress>lubia.vinhas@inpe.br</electronicmailaddress>
		<electronicmailaddress>karine.ferreira@inpe.br</electronicmailaddress>
		<conferencename>Brazilian Symposium on GeoInformatics, 17 (GEOINFO)</conferencename>
		<conferencelocation>Campos do Jordão, SP</conferencelocation>
		<date>27-30 nov. 2016</date>
		<booktitle>Anais</booktitle>
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		<abstract>The potential observed in various applications and the advancement of technologies for point cloud data acquisition has increased the availability of this type of geospatial data. With increasing volume, new challenges arise in the efficient management of this information. Recently, the Database Management System PostgreSQL has supported this data type through the extension PointCloud. This paper explores this extension, through the analysis of its capabilities and its use in an experimental set of LiDAR data. Performance tests and disk usage metrics are collected for different compression methods. In addition, we present performance testing and disk usage metrics collected for different compression methods. RESUMO: O potencial observado em diversas aplicações e o avanço das tecnologias de aquisição de nuvem de pontos têm aumentado a disponibilidade desse tipo de dado geoespacial. Com o aumento do volume, novos desafios surgem quanto ao gerenciamento eficiente dessas informaçõs. Recentemente, o Sistema Gerenciador de Banco de Dados PostgreSQL tem gerenciado esse tipo de dado atraves da extensão PointCloud. Este trabalho explora essa extensão, através da análise de suas capacidades e do seu uso em um conjunto experimental de dados LiDAR. Alem disso, apresentamos testes de desempenho e métricas de utilização de disco coletadas para diferentes métodos de compressão.</abstract>
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