This paper presents a novel method for extracting the land vertical displacement rates (VDRs) in Shanghai (China) using the multi-platform SAR images collected between 2009 and 2010, i.e., the ascending/descending COSMO-SkyMed (CSK) X-band images and the descending TerraSAR (TSX) X-band images. Different from the conventional approach the proposed method estimates the VDRs by multi-temporal interferometric SAR processing (i.e., temporarily coherent point InSAR, TCPInSAR) and the localized least square (LS) solution, through which the horizontal displacement rates (HDRs) can be also derived as the by-product. The three types of displacement rates in the radar line of sight (LOS) are first estimated by TCPInSAR with use of the ascending/descending CSK and descending TSX data. Both the VDRs and HDRs are then estimated by a localized LS method on the basis of the three types of LOS displacement rates derived by TCPInSAR. For comparison purposes, the VDRs for the single-platform SAR data are also obtained through dividing the LOS displacement rates by the cosine of the radar incidence angle. The analysis with the aid of GPS data shows the horizontal motion due to the geological settings in Shanghai cannot be ignored, and the VDRs derived from the single-platform data are not accurate and reliable without taking into account the horizontal motion. The experimental results indicate the TCPInSAR-LS method can be used to efficiently improve the accuracy in the VDRs by integrating the multi-platform SAR data and considering both horizontal and vertical motion, thus overcoming the disadvantages in the conventional approach. The improved VDRs in Shanghai range between −22.8 and 9.6 mm/year, while the relative east-west motion rates range between −7.2 and 6.2 mm/year, and the relative north–south motion is subtle and can be ignored. Analysis of the improved VDRs shows that a slightly uplifting area of about 70 km² appears in the west downtown of Shanghai, and a subsiding bowl appears in the Hongkou District of Shanghai. The validation indicates that the uplifting trend can be ascribed to the measures conducted by the Shanghai municipal government, i.e., decreasing the groundwater pumping volume and increasing the groundwater recharge volume.

Shanghai is a modern metropolis characterized by high urban density and anthropogenic ground motions. Although traditional deformation monitoring methods, such as GPS and spirit leveling, are reliable to millimeter accuracy, the sparse point subsidence information makes understanding large areas difficult. Multiple temporal space-borne synthetic aperture radar interferometry is a powerful high-accuracy (sub-millimeter) remote sensing tool for monitoring slow ground deformation for a large area with a high point density. In this paper, the Interferometric Point Target Time Series Analysis method is used to extract ground subsidence rates in Shanghai based on 31 C-Band and 35 X-Band synthetic aperture radar (SAR) images obtained by Envisat and COSMO SkyMed (CSK) satellites from 2007 to 2010. A significant subsidence funnel that was detected is located in the junction place between the Yangpu and the Hongkou Districts. A t-test is formulated to judge the agreements between the subsidence results obtained by SAR and by spirit leveling. In addition, four profile lines crossing the subsidence funnel area are chosen for a comparison of ground subsidence rates, which were obtained by the two different band SAR images, and show a good agreement.

Ground subsidence is one of the key factors damaging transportation facilities, e.g., road networks consisting of highways and railways. In this paper, we propose to apply the persistent scatterer synthetic aperture radar interferometry (PS-InSAR) approach that uses high-resolution TerraSAR-X (TSX) imagery to extract the regional scale subsidence rates (i.e., average annual subsidence in mm/year) along road networks. The primary procedures involve interferometric pair selection, interferogram generation, persistent scatterer (PS) detection, PS networking, phase parameterization, and subsidence rate estimation. The Xiqing District in southwest Tianjin (China) is selected as the study area. This district contains one railway line and several highway lines. A total of 15 TSX images covering this area between April 2009 and June 2010 are utilized to obtain the subsidence rates by using the PS-InSAR (PSI) approach. The subsidence rates derived from PSI range from −68.7 to −1.3 mm/year. These findings show a significantly uneven subsidence pattern along the road network. Comparison between the PSI-derived subsidence rates and the leveling data obtained along the highways shows that the mean and standard deviation (SD) of the discrepancies between the two types of subsidence rates are 0.1 and ±3.2 mm/year, respectively. The results indicate that the high-resolution TSX PSI is capable of providing comprehensive and detailed subsidence information regarding road networks with millimeter-level accuracy. Further inspections under geological conditions and land-use categories in the study area indicate that the observed subsidence is highly related to aquifer compression due to groundwater pumping. Therefore, measures should be taken to mitigate groundwater extraction for the study area.

Point-like targets are useful in providing surface deformation with the time series of synthetic aperture radar (SAR) images using the multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology. However, the spatial density of point-like targets is low, especially in non-urban areas. In this paper, a hierarchical MTInSAR method is proposed to increase the spatial density of deformation measurements by tracking both the point-like targets and the distributed targets with the temporal steadiness of radar backscattering. To efficiently reduce error propagation, the deformation rates on point-like targets with lower amplitude dispersion index values are first estimated using a least squared estimator and a region growing method. Afterwards, the distributed targets are identified using the amplitude dispersion index and a Pearson correlation coefficient through a multi-level processing strategy. Meanwhile, the deformation rates on distributed targets are estimated during the multi-level processing. The proposed MTInSAR method has been tested for subsidence detection over a suburban area located in Tianjin, China using 40 high-resolution TerraSAR-X images acquired between 2009 and 2010, and validated using the ground-based leveling measurements. The experiment results indicate that the spatial density of deformation measurements can be increased by about 250% and that subsidence accuracy can reach to the millimeter level by using the hierarchical MTInSAR method.

This paper presents a hierarchical approach to network construction and time series estimation in persistent scatterer interferometry (PSI) for deformation analysis using the time series of high-resolution satellite SAR images. To balance between computational efficiency and solution accuracy, a dividing and conquering algorithm (i.e., two levels of PS networking and solution) is proposed for extracting deformation rates of a study area. The algorithm has been tested using 40 high-resolution TerraSAR-X images collected between 2009 and 2010 over Tianjin in China for subsidence analysis, and validated by using the ground-based leveling measurements. The experimental results indicate that the hierarchical approach can remarkably reduce computing time and memory requirements, and the subsidence measurements derived from the hierarchical solution are in good agreement with the leveling data.

Keywords: SAR, PSI, Short Baseline, Highways and Railways, Subsidence Monitoring, TerraSAR-X, Analysis Ground subsidence is one of the key factors causing damages to transportation facilities, e.g., transportation network (TN) consists of highways and railways. For better exploration of TN subsidence, we propose to use the high resolution TerraSAR-X (TSX) persistent scatterer interferometry (PSI) approach to extract regional scale (RS) subsidence related to the TN. The primary procedures involve interferometric pair selection, interferogram generation, persistent scatterer (PS) detection, PS networking, phase parameterization and subsidence estimation. Xiqing district of southwest Tianjin (China) is selected as the study area, in which multiple highways and one railway line are located. 15 TSX images collected over this area between March, 2009 and June, 2010 are utilized to extract subsidence by the TSX PSI approach. The subsidence rate (SR) map shows that remarkably uneven subsidence occurs along and around the TN, and the SR ranges between –69 and –1.3 mm/yr. For validation purpose, the SR of the TN derived by PSI is compared with leveling data collected for the benchmarks deployed along the selected highways. The mean and root mean square error (RMSE) of discrepancies between two data sets are 0.1 and ±3.2 mm/yr, respectively. The numerical analysis indicates that the high resolution TSX PSI is able to reveal comprehensive and detailed subsidence related to the TN with a millimeter level accuracy.