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dc.contributor.authorBoudriki Semlali, Badr Eddine
dc.contributor.authorEl Amrani, Chaker
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions
dc.identifier.citationBoudriki, B.; El Amrani, C. Big data and remote sensing: A new software of ingestion. "International Journal of Electrical and Computer Engineering", 1 Abril 2021, vol. 11, p. 1521-1530.
dc.description.abstractCurrently, remote sensing is widely used in environmental monitoring applications, mostly air quality mapping and climate change supervision. However, satellite sensors occur massive volumes of data in near-real-time, stored in multiple formats and are provided with high velocity and variety. Besides, the processing of satellite big data is challenging. Thus, this study aims to approve that satellite data are big data and proposes a new big data architecture for satellite data processing. The developed software is enabling an efficient remote sensing big data ingestion and preprocessing. As a result, the experiment results show that 86 percent of the unnecessary daily files are discarded with a data cleansing of 20 percent of the erroneous and inaccurate plots. The final output is integrated into the Hadoop system, especially the HDFS, HBase, and Hive, for extra calculation and processing.
dc.format.extent10 p.
dc.rightsAttribution-NonCommercial 3.0 Spain
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshBig data
dc.subject.otherBig data
dc.subject.otherData integration
dc.subject.otherData preprocessing
dc.subject.otherHadoop framework
dc.subject.otherSatellite sensors Data
dc.titleBig data and remote sensing: A new software of ingestion
dc.subject.lemacDades massives
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.authorBoudriki, B.; El Amrani, C.
local.citation.publicationNameInternational Journal of Electrical and Computer Engineering

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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial 3.0 Spain