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dc.contributor.authorGauci, Adam-
dc.contributor.authorDeidun, Alan-
dc.contributor.authorAbela, John-
dc.contributor.authorCachia, Ernest-
dc.contributor.authorDimech, Sean-
dc.date.accessioned2020-10-13T07:39:06Z-
dc.date.available2020-10-13T07:39:06Z-
dc.date.issued2020-
dc.identifier.citationGauci, A., Deidun, A., Abela, J., Cachia, E., & Dimech, S. (2020). Automatic benthic habitat mapping using inexpensive underwater drones. IGARSS 2020, IEEE International Geoscience and Remote Sensing Symposium, Hawaii, TH2.R20.5., 2213-2216.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/61635-
dc.description.abstractThe generation of benthic habitat maps relies either on direct in-situ observations made by SCUBA divers swimming in a rectilinear fashion, or on costly remote sensing techniques involving either ROVs or sonar technology. The recent commercialisation of off-the-shelf underwater drones has enhanced benthic mapping possibilities by providing a costeffective alternative. Despite still requiring ground truthing, such drones do not rely extensively on boat-support services. In this study, the applicability and feasibility of using an underwater high-resolution optical platform to automate the generation of benthic maps is investigated. A PowerVision PowerRay [1] was used to capture underwater imagery in an embayment along the north-east coast of the island of Malta (central Mediterranean). A Machine Learning method based on Self-Organizing Maps was then implemented to automate the classification process. Results produced from this technique were evaluated in terms of their accuracy through comparisons with a benthic habitat map of the same area that was generated through conventional means in a previous study.en_GB
dc.language.isoenen_GB
dc.publisherIEEEen_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectMarine benthic ecology -- Maltaen_GB
dc.subjectBenthic ecology -- Maltaen_GB
dc.subjectAutonomous underwater vehiclesen_GB
dc.subjectMarine resources conservationen_GB
dc.subjectImage analysis -- Data processingen_GB
dc.subjectPosidonia oceanicaen_GB
dc.titleAutomatic benthic habitat mapping using inexpensive underwater dronesen_GB
dc.typeconferenceObjecten_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.bibliographicCitation.conferencenameIGARSS 2020, IEEE International Geoscience and Remote Sensing Symposiumen_GB
dc.description.reviewedpeer-revieweden_GB
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