Interferometric Synthetic Aperture Radar (InSAR) is an established technique which has been applied to Earth surface displacement analysis and topographic reconstruction. Two complex coherent SAR acquisitions of the same scene are combined to form an interferogram from which surface displacement or terrain measurements are made. The similarities between both SAR signals is captured in the coherence and its magnitude is determined by the spatial separation between acquiring antennas and the changes (if any) to the physical characteristics of the scattering target in the duration between both SAR acquisitions. Both of these products derivable from the interferometric process have been applied in this study with the aim of enhancing monitoring and assessing changes in the coastal environment, with emphasis on the coastal geomorphology. A combination of remote sensing data acquired for Montrose Bay, NE Scotland, has been used to analyze changes to the geomorphology of the beach and dune system in terms of sediment volume analysis, erosion and accretion processes and shoreline changes over a short-term period of 4 years. The interferometric coherence was applied to detect changes to the dune morphology, which have been actively eroding at the southern flank of the Bay. The interferometric analysis presented in this thesis was based on SAR data acquired by the Sentinel-1 SAR antenna and the results demonstrated the limitations of the sensor for terrain mapping and DEM reconstruction. In addition, the significance of the vegetation on the interferometric coherence was demonstrated. However, the results have shown that temporal baseline remained a significant consideration in the application of interferometric coherence in highly dynamic environments such as the coastal environment.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:743126 |
Date | January 2018 |
Creators | Udugbezi, Emmanuel |
Contributors | Cutler, Mark ; Kirkbride, Martin |
Publisher | University of Dundee |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://discovery.dundee.ac.uk/en/studentTheses/b127af25-c290-4fdf-ac44-96c77449fb59 |
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