Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/19051
DC FieldValueLanguage
dc.contributor.authorThemistocleous, Kyriacos-
dc.date.accessioned2020-09-23T06:21:14Z-
dc.date.available2020-09-23T06:21:14Z-
dc.date.issued2019-06-27-
dc.identifier.citationSeventh International Conference on Remote Sensing and Geoinformation of the Environment, 2019, 18-21 March, Paphos, Cyprusen_US
dc.identifier.isbn978-151063061-1-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/19051-
dc.description.abstractTraditional NDVI techniques require NIR images from multispectral cameras in order to identify vegetation. Research indicates that RGB images from UAV platforms can provide a cost-efficient and near-real time survey with high temporal and spatial resolution. In this study, only RGB images taken with a 20MP camera mounted on a UAV glider were used to conduct a ground survey and generate a Digital Elevation Model (DEM). Over 7,000 UAV images with less than 5cm ground resolution were used in order to survey a 5km2 in the Alassa region in Cyprus in order to produce a DEM. The area was geo-referenced using ground control points. Due to extensive vegetation coverage, a RGB-based vegetation indice was used to mask the vegetation and produce a DEM using interpolation techniques. This study highlights a cost-effective technique to survey and model large areas with vegetation coverage.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© SPIEen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDEMen_US
dc.subjectMappingen_US
dc.subjectRGBen_US
dc.subjectSurveyingen_US
dc.subjectUAVsen_US
dc.subjectVegetationen_US
dc.titleDEM modeling using RGB-based vegetation indices from UAV imagesen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryCivil Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on Remote Sensing and Geoinformation of the Environmenten_US
dc.identifier.doi10.1117/12.2532748en_US
cut.common.academicyear2018-2019en_US
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.fulltextNo Fulltext-
item.openairetypeconferenceObject-
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:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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