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dc.contributor.authorZerrouki, Nabil
dc.contributor.authorHarrou, Fouzi
dc.contributor.authorSun, Ying
dc.date.accessioned2018-05-14T13:37:07Z
dc.date.available2018-05-14T13:37:07Z
dc.date.issued2018-04-06
dc.identifier.citationZerrouki N, Harrou F, Sun Y (2018) Statistical Monitoring of Changes to Land Cover. IEEE Geoscience and Remote Sensing Letters: 1–5. Available: http://dx.doi.org/10.1109/LGRS.2018.2817522.
dc.identifier.issn1545-598X
dc.identifier.issn1558-0571
dc.identifier.doi10.1109/LGRS.2018.2817522
dc.identifier.urihttp://hdl.handle.net/10754/627864
dc.description.abstractAccurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data. This approach integrates the multivariate exponentially weighted moving average (MEWMA) chart with support vector machines (SVMs) for accurate and reliable detection of changes to land cover. Here, we utilize the MEWMA scheme to identify features corresponding to changed regions. Unfortunately, MEWMA schemes cannot discriminate between real changes and false changes. If a change is detected by the MEWMA algorithm, then we execute the SVM algorithm that is based on features corresponding to detected pixels to identify the type of change. We assess the effectiveness of this approach by using the remote-sensing change detection database and the SZTAKI AirChange benchmark data set. Our results show the capacity of our approach to detect changes to land cover.
dc.description.sponsorshipThis work was supported by the Office of Sponsored Research (OSR), King Abdullah University of Science and Technology under Award OSR-2015-CRG4-2582.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8332536/
dc.subjectClassification
dc.subjectFeature extraction
dc.subjectland-cover change (LCC) detection
dc.subjectMODIS
dc.subjectMonitoring
dc.subjectmultivariate monitoring chart
dc.subjectRemote sensing
dc.subjectremote sensing
dc.subjectSupport vector machines
dc.subjectVegetation mapping
dc.titleStatistical Monitoring of Changes to Land Cover
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journalIEEE Geoscience and Remote Sensing Letters
dc.contributor.institutionLCPTS, Faculty of Electronics and Computer Science, University of Sciences and Technology Houari Boumédienne, Algiers 16000, Algeria, and also with the DIIM Laboratory, Center for Development of Advanced Technology, Algiers 16303, Algeria.
kaust.personHarrou, Fouzi
kaust.personSun, Ying
kaust.grant.numberOSR-2015-CRG4-2582
dc.date.published-online2018-04-06
dc.date.published-print2018-06


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