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dc.contributorGuerrero Castex, Ignacio
dc.contributorUniversitat Jaume I
dc.contributorPebesma, Edzer
dc.contributorPainho, Marco
dc.contributor.authorHausen, Eias
dc.date.accessioned2016-06-28T07:18:13Z
dc.date.available2016-06-28T07:18:13Z
dc.date.issued2016-03-07
dc.identifier.urihttp://hdl.handle.net/10234/161172
dc.descriptionTreball Final del Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi: SIW013. Curs acadèmic 2015-2016ca_CA
dc.description.abstractHyperspectral Imaging is a technique that collects information from the electromagnetic spectrum, storing the value of the spectrum band for each pixel of the image. This technique stands out for the contiguous wide range of wavelengths it covers; leading to the ability of accurate surface and material distinction. The big volumes of Hyperspectral Images datasets, which are called data cubes as the band value represent the third dimension, have been a barrier against exploiting the full potential of these images where there is no standardized way in storing them. On top of that, the classical relational databases proved to be an inconvenient storage space for such images. Array databases have been a serious choice for storing scientific and big volumes of data, and they represent a promising suitable environment for hyperspectral images. We aim to study the efficiency of storing hyperspectral images on an arraydatabase by suggesting a convenient data model. Furthermore, in order to examine the feasibility of this model, we make a comparison with two relational databases using specific measurements in performance and query complexityca_CA
dc.format.extent63 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherUniversitat Jaume Ica_CA
dc.rightsAttribution-NonCommercial-NoDerivs 4.0 Spain*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMàster Universitari Erasmus Mundus en Tecnologia Geoespacialca_CA
dc.subjectErasmus Mundus University Master's Degree in Geospatial Technologiesca_CA
dc.subjectMáster Universitario Erasmus Mundus en Tecnología Geoespacialca_CA
dc.subjectArray Databaseca_CA
dc.subjectDatabase Comparisonca_CA
dc.subjectGeoTIFF Imagesca_CA
dc.subjectHyperspectral Imagingca_CA
dc.subjectHyperspectral Satellite Imagesca_CA
dc.subjectRaster Databaseca_CA
dc.subjectSatellite Images Storageca_CA
dc.subjectSciDBca_CA
dc.titleArray-database Model (SciDB) for Standardized Storing of Hyperspectral Satellite Imagesca_CA
dc.typeinfo:eu-repo/semantics/masterThesisca_CA
dc.educationLevelEstudios de Postgradoca_CA
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA


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Attribution-NonCommercial-NoDerivs 4.0 Spain
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