Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29137
DC FieldValueLanguage
dc.contributor.authorDoukari, Michaela-
dc.contributor.authorPapakonstantinou, Apostolos-
dc.contributor.authorBatsaris, Marios-
dc.contributor.authorTopouzelis, Kostas-
dc.date.accessioned2023-05-02T06:30:06Z-
dc.date.available2023-05-02T06:30:06Z-
dc.date.issued2018-01-01-
dc.identifier.citationProceedings of SPIE - The International Society for Optical Engineeringen_US
dc.identifier.isbn9781510621176-
dc.identifier.issn0277786X-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/29137-
dc.description.abstractThe collection of detailed and accurate information about marine habitats and flora species is crucial for mapping, monitoring and management of marine and coastal environments. Remote sensing is widely used to collect information at marine environments, while in recent years the potential use of UAS for mapping is examined. The aim of this paper is the creation of a prediction model for the optimal flight windows of UAS, using the programming language R. The methodology examines several limitations of UAS data acquisition over coastal areas, related to environmental conditions, mainly due to weather and sea state. A theoretical protocol that summarizes the parameters that affect the quality of aerial data acquisition, was created. These parameters are related to the weather conditions (wind, temperature, clouds etc.) and oceanographic phenomena (waves, turbidity, sun glint etc.), prevailing in the study area during the UAV flight. The protocol for the collection of accurate and reliable geospatial information in coastal and marine areas using UAS will be a useful mapping tool for the coastal zone mapping. The produced prediction model will act as a versatile computation approach to different input variables and therefore can be used widely. The input variables of this model refer to weather conditions prevailing in the area of interest and measurements of oceanographic parameters. The result of the prediction model is the optimal flight windows for the collection of accurate and qualitative marine information, in a region of interest.en_US
dc.language.isoenen_US
dc.titlePreview of a protocol for UAV data collection in coastal areasen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of the Aegeanen_US
dc.subject.categoryOther Engineering and Technologiesen_US
dc.journalsSubscriptionen_US
dc.countryGreeceen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceSixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018)en_US
dc.identifier.doi10.1117/12.2326010en_US
dc.identifier.scopus2-s2.0-85052698039en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85052698039en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.relation.volume10773en_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.orcid0000-0002-6464-2008-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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