How to effectively obtain metadata from remote sensing big data?

T.S. Körting*, L. Namikawa, L.M.G. Fonseca, C.A. Felgueiras

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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What can be considered big data when dealing with remote sensing imagery? In general terms, big data is defined as data requiring high management capabilities characterized by 3 V’s: Volume, Velocity and Variety. In the past, (e.g. 1975), considering the computational and databases resources available, a series of Landsat-1 imagery from the same region could be considered big data. Nowadays, several satellites are available, and they produce massive amounts of data. Certainly, an image data set obtained by a single satellite, for a
specific region and along time, fills the 3 V’s requirements to be considered big data as well. In order to deal with remote sensing big data, we propose to explore the generation of metadata based on the detection of simple features. Besides the intrinsic geographic information on every remote sensing scene, no additional metadata is usually considered. We propose basic image processing algorithms to detect basic well-known patterns, and include them as tags, such as cloud, shadow, stadium, vegetation, and water, according to what is detectable at each spatial resolution. In this work we show preliminary results using imagery from RapidEye sensor, with 5 meter spatial resolution, composed by two full coverages of Brazil with RapidEye multispectral imagery (around 40k scenes).
Original languageEnglish
Title of host publicationProceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands
EditorsN. Kerle, M. Gerke, S. Lefevre
Place of PublicationEnschede
PublisherUniversity of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)
Number of pages3
ISBN (Print)978-90-365-4201-2
Publication statusPublished - 14 Sep 2016
Externally publishedYes
Event6th International Conference on Geographic Object-Based Image Analysis, GEOBIA 2016: Solutions & Synergies - University of Twente Faculty of Geo-Information and Earth Observation (ITC), Enschede, Netherlands
Duration: 14 Sep 201616 Sep 2016
Conference number: 6


Conference6th International Conference on Geographic Object-Based Image Analysis, GEOBIA 2016
Abbreviated titleGEOBIA
Internet address


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