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dc.contributor.authorDuffy, J
dc.date.accessioned2019-03-11T10:48:55Z
dc.date.issued2019-03-04
dc.description.abstractMonitoring coastal environments is a challenging task. This is because of both the logistical demands involved with in-situ data collection and the dynamic nature of the coastal zone, where multiple processes operate over varying spatial and temporal scales. Remote sensing products derived from spaceborne and airborne platforms have proven highly useful in the monitoring of coastal ecosystems, but often they fail to capture fine scale processes and there remains a lack of cost-effective and flexible methods for coastal monitoring at these scales. Proximal sensing technology such as lightweight drones and kites has greatly improved the ability to capture fine spatial resolution data at user-dictated visit times. These approaches are democratising, allowing researchers and managers to collect data in locations and at defined times themselves. In this thesis I develop our scientific understanding of the application of proximal sensing within coastal environments. The two critical review pieces consolidate disparate information on the application of kites as a proximal sensing platform, and the often overlooked hurdles of conducting drone operations in challenging environments. The empirical work presented then tests the use of this technology in three different coastal environments spanning the land-sea interface. Firstly, I use kite aerial photography and uncertainty-assessed structure-from-motion multi-view stereo (SfM-MVS) processing to track changes in coastal dunes over time. I report that sub-decimetre changes (both erosion and accretion) can be detected with this methodology. Secondly, I used lightweight drones to capture fine spatial resolution optical data of intertidal seagrass meadows. I found that estimations of plant cover were more similar to in-situ measures in sparsely populated than densely populated meadows. Lastly, I developed a novel technique utilising lightweight drones and SfM-MVS to measure benthic structural complexity in tropical coral reefs. I found that structural complexity measures were obtainable from SfM-MVS derived point clouds, but that the technique was influenced by glint type artefacts in the image data. Collectively, this work advances the knowledge of proximal sensing in the coastal zone, identifying both the strengths and weaknesses of its application across several ecosystems.en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.identifier.urihttp://hdl.handle.net/10871/36373
dc.publisherUniversity of Exeteren_GB
dc.rights.embargoreasonUnpublished work containeden_GB
dc.titleCoastal Eye: Monitoring Coastal Environments Using Lightweight Dronesen_GB
dc.typeThesis or dissertationen_GB
dc.contributor.advisorAnderson, Ken_GB
dc.contributor.advisorShutler, Jen_GB
dc.contributor.advisorWitt, Men_GB
dc.contributor.advisorLand, Pen_GB
dc.publisher.departmentGeographyen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dc.type.degreetitlePhD in Physical Geographyen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnameDoctoral Thesisen_GB
dcterms.dateAccepted2019-03-11
exeter.funder::Natural Environment Research Council (NERC)en_GB
rioxxterms.versionNAen_GB
rioxxterms.licenseref.startdate2019-03-07
rioxxterms.typeThesisen_GB


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