Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30826
DC FieldValueLanguage
dc.contributor.authorThemistocleous, Kyriacos-
dc.date.accessioned2023-11-20T12:16:54Z-
dc.date.available2023-11-20T12:16:54Z-
dc.date.issued2023-09-21-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/30826-
dc.description.abstractThis study seeks to establish a methodology in order to determine the rate of coastal erosion using temporal aerial and UAV images. Part of the methodology focuses on forecasting coastal erosion and mapping Posidonia oceanica. Initial results indicate that there may be a correlation between coastal erosion and other related dynamics, such as the presence of Posidonia oceanica. UAV images acquired using UAVS in the Spyros Beach area near Larnaca, Cyprus were compared with aerial photos provided by the Lands and Surveys Department of the Government of Cyprus in order to estimate coastal erosion. In this study, the results indicate that, instead of coastline erosion, the coastline is actually expanding at a constant rate over the forecasted period. The beach nourishment observed may be related to the reduction of Posidonia oceanica. This reduction of the Posidonia oceanica forms a natural breaker between the shoreline and the sea, leading to a reduction of wave energy which thereby results in an enhanced accumulation of sand at the beach.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.relationEXCELSIOR: ERATOSTHENES Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment : Teaming Phase1 GA 763643en_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectUnmanned aerial vehiclesen_US
dc.subjectSanden_US
dc.subjectPhotogrammetryen_US
dc.subjectCamerasen_US
dc.subjectImage segmentationen_US
dc.subjectImage processingen_US
dc.subjectPoint cloudsen_US
dc.subjectRGB color modelen_US
dc.subjectCoastal modelingen_US
dc.titleIdentification and forecasting of coastal erosion using aerial and UAV imagesen_US
dc.typeConference Papersen_US
dc.collaborationERATOSTHENES Centre of Excellenceen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryENGINEERING AND TECHNOLOGYen_US
dc.journalsOpen Accessen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationNon Peer Revieweden_US
dc.relation.conferenceNinth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprusen_US
dc.identifier.doihttps://doi.org/10.1117/12.2683057en_US
cut.common.academicyear2022-2023en_US
dc.identifier.spage1en_US
dc.identifier.epage8en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
crisitem.project.funderEuropean Commission-
crisitem.project.grantnoH2020-WIDESPREAD-04-2017-
crisitem.project.fundingProgramH2020-
crisitem.project.openAireinfo:eu-repo/grantAgreement/EC/H2020/763643-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-4149-8282-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:EXCELSIOR H2020 Teaming Project Publications
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