Local-scale assessment of the displacement pattern of a densely populated landslide, utilizing finite element software and terrestrial radar interferometry: a case study on Huangtupo landslide (P.R. China)
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Terrestrial radar interferometry with its manifold applications offers a great tool to measure the displacements of a slope. Nonetheless, it lacks in significance when it comes to distinguish between deep-situated movements and anthropogenic-induced movements in a densely populated area. This paper gives an approach to estimate displacement patterns and consequently the susceptibility of an active landslide, utilizing radar interferometry measurements, corrected by finite element software and ArcGIS. In the course of YANGTZE Project, a field campaign was carried out in 2013, measuring the overall displacements of the Huangtupo landslide (P.R. China), utilizing a ground-based synthetic aperture radar device. On purpose to calculate the limit of displacements referring to deep-situated movements, a two-dimensional finite element model of a significant geological cross section has been established. Subsequently, a displacement point data set obtained out of the radar interferometry measurements was revised by removing all events exceeding the calculated limit. The corrected data set displays events that are in the range of those, which belong into the margin of values that can refer to deep-situated movements. Finally, a point density map, interpolated out of this data set, shows up areas with a high density of displacements and thus the present displacement pattern during the field investigations. A comparison of this map to already existing GPS and satellite radar interferometry measurements showed up in suitable results of the used method.
KeywordsFinite element analysis Radar interferometry ArcGIS Huangtupo Susceptibility Three Gorges Dam
All studies were carried out as a part of the interdisciplinary “YANGTZE-Project” which is supported by the German Federal Ministry of Education and Research (BMBF). The authors want to thank the BMBF for the financial support. Special thanks go to Prof. Dr. Xiang Wei and his students of China University of Geosciences (Wuhan) for their support and organization while the field trips, as well as to all project partners of YANGTZE Project for their close collaboration.
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