Science Service System

Summary of Proposal GEO0112

TitleMonitoring of urban landslides in the Three Gorges area using TerraSAR-X Spotlight and stripmap interferometry
Investigator Muller, Jan-Peter - University College London, Space and Climate Physics
Team Members
Prof. Rocca, Fabio - Politecnico di Milano, Elettronica ed Informazione
Prof. Zeng, Qiming - Peking University, Institute of Remote Sensing and GIS
Prof. Peng, Junhuan - Chongqing University, Surveying and Mapping
Ms., MSc candidate Larkin, Hayley - University College London, Mullard Space Science Laboratory
Dr. Li, Zhenhong - Glasgow University, School of Geographical and Earth Sciences
Mr. PhD Candidate Singleton, Andrew - Glasgow University, School of Geographical and Earth Sciences
Prof. Zhao, Yonghong - Peking University, Dept. Of Geophysics, School of Earth and Space Sciences
Mrs. PhD candidate Li, Xiaofan - Peking University, Dept. Of Geophysics, School of Earth and Space Sciences
Asso. Prof. Jiao, Jian - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Mr., PhD candidate Liang, Cunren - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Ms, PhD candidate Cui, Xiai - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Mr., PhD candidate Zhou, Xiao - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Mr., PhD candidate Wang, Qing - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Mr., PhD candidate Gao, Sheng - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Ms, PhD candidate Yun, Ye - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Ms, PhD candidate Song, Shujing - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
Ms, PhD candidate Zhang, Xiaojie - Peking University, Inst. Of Remote Sens. & GIS, School of Earth & Space Sci.
SummaryThe primary objective is the quantitative assessment of the potential of TerraSAR-X spotlight and strip mode data for the measurement of landslip of buildings in very dense urban areas using both natural corner reflectors (such as buildings) and artificial corner reflectors to be placed in the area which will respond both to TerraSAR-X and ENVISAT ascending as well as descending interferometric pairs. The Three Gorges area in China stretching some 600km from Chongqing mega-city in the west to Yichang in the east includes a number of new cities as well as older cities which have been substantially expanded and all of which are built on extremely steep slopes. With the rising water levels (from 135 to 175m) associated with the completion of the Three Gorges dam in 2008/9, the stability of the slopes may be susceptible to landslides. The Chinese government has spent a huge sum of money to try to provide defences along the riverbank to mitigate against the effects of the rising water levels. However, it is currently unknown what effects the volume and mass of water may have on the steep slopes both below the building lines, under them and above them. Monitoring such a vast area using traditional surveying techniques is uneconomic and it is better to target traditional instrumentation to areas which are demonstrated to be moving. SAR interferometry at 30m resolution is difficult to apply in this area due to the high rainfall rate, dense vegetative cover and lack of bare ground (as all such areas have been built on). dInSAR using TerraSAR-X at 1-3m resolution appears to offer the potential of measuring such deformation on an 11-day cycle continuously and applying atmospheric WV correction techniques based on GPS, permanent scatterer techniques developed for ERS/ENVISAT and corner reflectometry to measure the deformation of individual buildings. Through a combination of European and Chinese technology, Chinese local expertise and logistical support a detailed quantitative assessment will be made of the potential of TX-dInSAR to provide sufficient and necessary information to determine (a) where areas of deformation are happening fastest; (b) what rates are landslip occurring; (c) what individual buildings are at risk and (d) what areas need to be monitored using traditional survey benchmarks and strain-gauges and tiltometers. Deliverables will include a database of PS/CR locations over time, a 3D model of the local areas (derived from sub-metre electro-optical stereo data and TX where feasible) and inter-comparisons of TX-derived motion with in situ measurements. A local web-GIS will be created of these data-sets based on previous work at the PI and CoI institutes for sharing within the project team. This will eventually be operationalised by the local disaster support teams.

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