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Title: Monitoring landslides in the Three Gorges Region : understanding the relationship between the formation of landslides and Three Gorges Project
Author: Sun, L.
ISNI:       0000 0004 8498 9417
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
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Landslides in the Three Gorges Region are investigated using mainly Earth Observation satellite data in order to shed light on the relationship between landslides and the hydrological driving factors, i.e. water level variations of the Three Gorges Reservoir and/or local rainfall. Conventional DInSAR techniques have been routinely used in the past for deformation mapping including landslide activities. However, several difficulties arise when attempting to apply DInSAR in areas with steep slopes and rugged topography, high humidity and dense vegetation cover such as the Three Gorges Region. In addition to these difficulties, it is shown that the maximum detectable displacement gradient of DInSAR is exceeded in the case study even when using the 1 m resolution TerraSAR-X Spotlight data. A sub-Pixel Offset Tracking approach (sPOT) is proposed to monitor slow-moving landslides in densely vegetated steep terrain. A detailed statistical analysis is carried out on the deformation measurements derived from natural scatterers and these measurements are compared against motion derived from a small network of corner reflectors. Using high-resolution TerraSAR-X data, the proposed sPOT approach has been shown of being capable of measuring centimetre-level landslide rates by using natural scatterers in densely vegetated terrain in line with measurements derived from corner reflectors. The TanDEM-X Coregistered Single look Slant range Complex data are employed to produce a 6 m resolution DEM. The impact of using different sources of DEMs is assessed on deformation measurements via offset tracking and DInSAR. Three SAR image modes (Stripmap, Spotlight and Staring Spotlight) from TerraSAR-X are employed to assess the potential and limitation of offset tracking and DInSAR on displacement measurements. Finally, the relationship between landslide occurrence and possible hydrological driving factors is assessed to infer possible landslide mechanisms. The reservoir drawdown is identified as the main triggering factor of landslides, and rainfall likely plays a secondary role.
Supervisor: Muller, J.-P. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available