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dc.contributor.authorNikolaidis, A.en
dc.contributor.authorStylianou, S.en
dc.contributor.authorGeorgiou, Georgios C.en
dc.contributor.authorHadjimitsis, D.en
dc.contributor.authorAkylas, Evangelosen
dc.creatorNikolaidis, A.en
dc.creatorStylianou, S.en
dc.creatorGeorgiou, Georgios C.en
dc.creatorHadjimitsis, D.en
dc.creatorAkylas, Evangelosen
dc.date.accessioned2019-12-02T10:37:10Z
dc.date.available2019-12-02T10:37:10Z
dc.date.issued2014
dc.identifier.isbn978-1-62841-276-5
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/57335
dc.description.abstractArcGIS® is a well known standard on Geographical Information Systems, used over the years for various remote sensing procedures. During the last decade, Rixen (2003) and Azcarate (2011) presented the DINEOF (Data Interpolating Empirical Orthogonal Functions) method, a EOF-based technique to reconstruct missing data in satellite images. The recent results of the DINEOF method in various experimental trials (Wang and Liu, 2013en
dc.description.abstractNikolaidis et al., 2013en
dc.description.abstract2014) showed that this computationally affordable method leads to effective reconstruction of missing data from geophysical fields, such as chlorophyll-a, sea surface temperatures or salinities and geophysical fields derived from satellite data. Implementing the method in a GIS system will lead to a complete and integrated approach, enhancing its applicability. The inclusion of statistical tools within the GIS, will multiply the effectiveness, providing interoperability with other sources in the same application environment. This may be especially useful in studies where various different kinds of data are of interest. For this purpose, we have implemented a new GIS toolbox that aims at automating the usage of the algorithm, incorporating the DINEOF codes provided by GHER (GeoHydrodynamics and Environment Research Group of University of Liege) into the ArcGIS® as an example for the effectiveness and simplicity of the toolbox. A case-study of filling the chlorophyll-A missing data in the Mediterranean Sea area, for a 16-day period is considered. More specifically, we focus on chlorophyll-A MODIS satellite data collected by CNR-ISAC (Italian National Research Council, Institute of Atmospheric Sciences and Climate), from the respective products of MyOcean2 organization, that provides free online access to Level 3, with 1 km resolution. All the daily products with an initial level of only 27% data coverage were successfully reconstructed over the Mediterranean Sea. © 2014 SPIE.en
dc.publisherSPIEen
dc.sourceProceedings of SPIE - The International Society for Optical Engineeringen
dc.source2nd International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2014en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84906901886&doi=10.1117%2f12.2069691&partnerID=40&md5=c5eb1cbfa199132e967cabd57b229ca0
dc.subjectAlgorithmsen
dc.subjectStatistical mechanicsen
dc.subjectGeophysicsen
dc.subjectMediterranean Seaen
dc.subjectSatellite imageryen
dc.subjectDINEOFen
dc.subjectEmpirical Orthogonal Functionen
dc.subjectRemote Sensingen
dc.subjectdata reconstructionen
dc.subjectApplication environmenten
dc.subjectArcGISen
dc.subjectChlorophyllen
dc.subjectGeographic information systemsen
dc.subjectNational Research Councilen
dc.subjectSea surface temperature (SST)en
dc.titleNew toolbox in ArcGIS for the reconstruction of missing satellite data using DINEOF algorithm: A case study of reconstruction of Chlorophyll-A gaps over the Mediterranean Seaen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1117/12.2069691
dc.description.volume9229
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeConference Objecten
dc.description.notes<p>Conference code: 107331</p>en
dc.contributor.orcidGeorgiou, Georgios C. [0000-0002-7451-224X]
dc.gnosis.orcid0000-0002-7451-224X


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