Land Subsidence Monitoring of Yangtze River Delta with Time Series SAR Interferometry Using Multi-Sensor SAR Data
Xiao, Ruya; He, Xiufeng
Hohai University, CHINA
The urban build-up in the Yangtze River Delta area has given rise what may be the largest concentration of adjacent metropolitan areas in the world. It covers an area of 99600 km2 and is home to over 105 million people as of 2010, of which an estimated 80 million is urban. With the rapid economic development and urbanization, the urban ground stability is under threat. Repeat-pass satellite Synthetic Aperture Radar Interferometry (InSAR) is a rapidly evolving remote sensing technology for observing the Earth surface. Algorithms for time series analysis of SAR data have been developed to better address the major limitations of conventional InSAR since the late 1990s. The time series algorithms fall into two broad categories: persistent scatterer(PS) InSAR and the small baseline approach. By combining both PS and Small baseline method, signal can be extracted from more pixels overall, improving the spatial sampling. An algorithm that combines both PS and small baseline approaches was developed by Hooper. PS pixels are selected based on the method of Hooper 2007 and a full resolution small baseline method is applied to extract coherent distributed scattering targets. 3-D phase unwrapping is then applied to the combined data set and further processing for isolation of the deformation signal proceeds as for small baseline processing.
In our paper, we will be focused on using Time Series InSAR techniques with TerraSAR data for ground deformation monitoring in Yangtze River Delta using multi-sensor SAR data, i.e. EnviSAT, TerraSAR, ALOS and maybe RadarSAT, thus analyzing the ground instability and monitoring the activity of groundwater mining. The research will help to gain more insight into the deformation and its evolution in this region and to improve the overall accuracy and reliability of the InSAR technology.