Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/18314
DC FieldValueLanguage
dc.contributor.authorAgapiou, Athos-
dc.date.accessioned2020-05-04T17:21:16Z-
dc.date.available2020-05-04T17:21:16Z-
dc.date.issued2020-02-01-
dc.identifier.citationRemote Sensing, 2020, vol. 12, no.3, pp. 579en_US
dc.identifier.issn2072-4292-
dc.descriptionThe author would like to acknowledge the “CUT Open Access Author Fund” for covering the open access publication fees of the paper.en_US
dc.description.abstractThe use of medium resolution, open access, and freely distributed satellite images, such as those of Landsat, is still understudied in the domain of archaeological research, mainly due to restrictions of spatial resolution. This investigation aims to showcase how the synergistic use of Landsat and Sentinel optical sensors can efficiently support archaeological research through object-based image analysis (OBIA), a relatively new scientific trend, as highlighted in the relevant literature, in the domain of remote sensing archaeology. Initially, the fusion of a 30mspatial resolution Landsat 8 OLI/TIRS Level-2 and a 10 m spatial resolution Sentinel 2 Level-1C optical images, over the archaeological site of "Nea Paphos" in Cyprus, are evaluated in order to improve the spatial resolution of the Landsat image. At this step, various known fusion models are implemented and evaluated, namely Gram-Schmidt, Brovey, principal component analysis (PCA), and hue-saturation-value (HSV) algorithms. In addition, all four 10mavailable spectral bands of the Sentinel 2 sensor, namely the blue, green, red, and near-infrared bands (Bands 2 to 4 and Band 8, respectively) were assessed for each of the different fusion models. On the basis of these findings, the next step of the study, focused on the image segmentation process, through the evaluation of different scale factors. The segmentation process is an important step moving from pixel-based to object-based image analysis. The overall results show that the Gram-Schmidt fusion method based on the near-infrared band of the Sentinel 2 (Band 8) at a range of scale factor segmentation to 70 are the optimum parameters for the detection of standing visible monuments, monitoring excavated areas, and detecting buried archaeological remains, without any significant spectral distortion of the original Landsat image. The new 10 m fused Landsat 8 image provides further spatial details of the archaeological site and depicts, through the segmentation process, important details within the landscape under examination.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relationERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environmenten_US
dc.relation.ispartofRemote Sensingen_US
dc.rights© by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectFusionen_US
dc.subjectImage segmentationen_US
dc.subjectArchaeological landscapesen_US
dc.subjectArchaeological proxiesen_US
dc.subjectLandsat 8en_US
dc.subjectSentinel 2en_US
dc.subjectObject-based image analysis (OBIA)en_US
dc.titleEvaluation of Landsat 8 OLI/TIRS level-2 and sentinel 2 level-1C fusion techniques intended for image segmentation of archaeological landscapes and proxiesen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationERATOSTHENES Centre of Excellenceen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsOpen Accessen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3390/rs12030579en_US
dc.identifier.scopus2-s2.0-85080882418-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85080882418-
dc.relation.issue3en_US
dc.relation.volume12en_US
cut.common.academicyear2019-2020en_US
dc.identifier.spage579en_US
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairetypearticle-
item.cerifentitytypePublications-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0001-9106-6766-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.journal.journalissn2072-4292-
crisitem.journal.publisherMDPI-
crisitem.project.funderEuropean Commission-
crisitem.project.grantnoH2020-WIDESPREAD-2018-01 / WIDESPREAD-01-2018-2019 Teaming Phase 2-
crisitem.project.fundingProgramH2020 Spreading Excellence, Widening Participation, Science with and for Society-
crisitem.project.openAireinfo:eu-repo/grantAgreeent/EC/H2020/857510-
Appears in Collections:Publications under the auspices of the EXCELSIOR H2020 Teaming Project/ERATOSTHENES Centre of Excellence
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