Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9248
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dc.contributor.authorAgapiou, Athos-
dc.date.accessioned2017-01-26T07:15:01Z-
dc.date.available2017-01-26T07:15:01Z-
dc.date.issued2017-01-02-
dc.identifier.citationInternational Journal of Digital Earth, 2017, vol. 10, no. 1, pp. 85-102en_US
dc.identifier.issn17538955-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/9248-
dc.description.abstractThis paper aims to demonstrate results and considerations regarding the use of remote sensing big data for archaeological and Cultural Heritage management large scale applications. For this purpose, the Earth Engine© developed by Google© was exploited. Earth Engine© provides a robust and expandable cloud platform where several freely distributed remote sensing big data, such as Landsat, can be accessed, analysed and visualized. Two different applications are presented here as follows: the first one is based on the evaluation of multi-temporal Landsat series datasets for the detection of buried Neolithic tells (‘magoules’) in the area of Thessaly, in Greece using linear orthogonal equations. The second case exploits European scale multi-temporal DMSP-OLS Night-time Lights Time Series to visualize the impact of urban sprawl in the vicinity of UNESCO World Heritage sites and monuments. Both applications highlight the considerable opportunities that big data can offer to the fields of archaeology and Cultural Heritage, while the studies also demonstrate the great challenges that still are needed to be overcome in order to make the exploitation of big data process manageable and fruitful for future applications.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relationATHENA. Remote Sensing Science Center for Cultural Heritageen_US
dc.relation.ispartofInternational Journal of Digital Earthen_US
dc.rights© The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License , which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.en_US
dc.subjectArchaeologyen_US
dc.subjectBig dataen_US
dc.subjectCultural heritageen_US
dc.subjectEarth Engineen_US
dc.subjectOrthogonal equationsen_US
dc.subjectRemote sensingen_US
dc.subjectUrban sprawlen_US
dc.titleRemote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applicationsen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_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.doi10.1080/17538947.2016.1250829en_US
dc.relation.issue1en_US
dc.relation.volume10en_US
cut.common.academicyear2016-2017en_US
dc.identifier.spage85en_US
dc.identifier.epage102en_US
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1753-8955-
crisitem.journal.publisherTaylor & Francis-
crisitem.project.funderEC-
crisitem.project.grantnoH2020-TWINN-2015-CSA-
crisitem.project.fundingProgramH2020 Twinning-
crisitem.project.openAireinfo:eu-repo/grantAgreement/EC/H2020/691936-
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-
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