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		<isbn>978-85-17-0076-8</isbn>
		<label>1728</label>
		<citationkey>QueirozFVCCSMS:2015:SeWeEx</citationkey>
		<title>WTSS: um serviço web para extração de séries temporais de imagens de sensoriamento remoto</title>
		<format>Internet</format>
		<year>2015</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Queiroz, Gilberto Ribeiro,</author>
		<author>Ferreira, Karine Reis,</author>
		<author>Vinhas, Lúbia,</author>
		<author>Câmara, Gilberto,</author>
		<author>Costa, Raphael Willian,</author>
		<author>Souza, Ricardo Cartaxo Modesto,</author>
		<author>Maus, Victor Wegner,</author>
		<author>Sanchez, Alber,</author>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>gribeiro@dpi.inpe.br</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>wanderf@dsr.inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 17 (SBSR)</conferencename>
		<conferencelocation>João Pessoa</conferencelocation>
		<date>25-29 abr. 2015</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>7553-7560</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>This paper presents a lightweight web service named Web Time Series Service (WTSS) for handling remote sensing imagery as time series. The proposed web service bridges the gap between remote sensing applications and their data access pattern requirements through a simple and effective representation for time series data. Our main goal is to bring to remote sensing research community an easy way for accessing and consuming satellite imagery data in the form of time series, saving researchers time when dealing with a huge volume of data. As we demonstrate, this web service can be easily integrated into free and open source technologies such as R and web application for data analysis and visualization. We also discuss some lessons learned with our first WTSS research prototype built on the top of the multidimensional array database system SciDB when handling data from MODIS sensor.</abstract>
		<area>SRE</area>
		<type>Sistemas, gerenciamento e política de dados</type>
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