Advancing Arctic coastal erosion measurement and monitoring through UAV-SfM, satellite imagery, and object-based image analysis
| dc.contributor.advisor | Moorman, Brian | |
| dc.contributor.author | Clark, Andrew | |
| dc.contributor.committeemember | Bender, Darren | |
| dc.contributor.committeemember | McDermid, Greg | |
| dc.contributor.committeemember | Lichti, Derek | |
| dc.contributor.committeemember | Duguay, Claude | |
| dc.date | 2024-02 | |
| dc.date.accessioned | 2024-01-26T18:39:37Z | |
| dc.date.available | 2024-01-26T18:39:37Z | |
| dc.date.issued | 2024-01-25 | |
| dc.description.abstract | Arctic coasts are vast, representing 30-34% of Earth’s coastline and exhibit some of the highest rates of erosion in the World due to the presence of permafrost. Rates of erosion are expected to increase with warming air and water temperatures, reductions in Arctic sea ice extent and duration, sea level rise, and increased storm severity and frequency. Erosion of Arctic coasts can lead to rapid land loss threatening habitat, archaeologically significant sites, modern infrastructure, and communities. Rapid erosion and permafrost degradation also leads to the liberation of previously frozen sediment and organic carbon into the nearshore zone which affects marine ecosystems and contributes to ocean acidification. Further, the release of organic carbon from frozen sediment contribute to global greenhouse gas release which are not well understood nor included in current Earth System Models. This thesis focuses on the use of emerging technologies to further our understanding of Arctic coastal processes, specifically, volumetric erosion, and broad scale delineation of multiple shoreline proxies for monitoring and quantification of erosion. UAV-SfM provides aerial and DSM imagery at unprecedented spatial and temporal resolution that provides perspectives and quantitative measures that are unachievable using conventional methods and very high resolution satellite imagery enables broader scale multiple proxy analysis while image classifications derived from OBIA, or GEOBIA, provide opportunities to systematically create boundary features (i.e. shoreline proxies). Overall, this doctoral research develops and evaluates techniques that enhance our ability to make quantitative measures of Arctic coastal erosion, both planimetric and volumetric, that have implications locally, regionally, and globally. | |
| dc.identifier.citation | Clark, A. (2024). Advancing Arctic coastal erosion measurement and monitoring through UAV-SfM, satellite imagery, and object-based image analysis (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | |
| dc.identifier.uri | https://hdl.handle.net/1880/118085 | |
| dc.identifier.uri | https://doi.org/10.11575/PRISM/42929 | |
| dc.language.iso | en | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.institution | University of Calgary | |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | UAV-SfM | |
| dc.subject | Arctic coasts | |
| dc.subject | coastal erosion | |
| dc.subject | object-based image analysis | |
| dc.subject.classification | Remote Sensing | |
| dc.subject.classification | Physical Geography | |
| dc.title | Advancing Arctic coastal erosion measurement and monitoring through UAV-SfM, satellite imagery, and object-based image analysis | |
| dc.type | doctoral thesis | |
| thesis.degree.discipline | Geography | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Doctor of Philosophy (PhD) | |
| ucalgary.thesis.accesssetbystudent | I do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible. |