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.
References
[1]
Liu, Y.; Zhang, X.L.; Wan, G.F.; Han, Q.D. The situation of land subsidence within Shanghai in recent years and its countermeasure (in Chinese). Chinese J. Geol. Hazard Control 1998, 9, 13–17.
[2]
Liu, Y. Preventive measures for land subsidence in Shanghai and their effects. Volcanol. Miner. Resour 2000, 21, 107–111.
[3]
Wang, Y.; Liao, M.S.; Li, D.R.; Wei, Z.X.; Fang, Z. Subsidence velocity retrieval from long-term coherent targets in radar interferometric stacks (in Chinese). Chinese J. Geophys 2007, 50, 598–604.
[4]
Liu, G.X.; Luo, X.J.; Chen, Q.; Huang, J.F.; Ding, X.L. Detecting land subsidence in Shanghai by PS-networking SAR interferometry. Sensors 2008, 8, 4725–4741.
[5]
Luo, X.J.; Huang, D.F.; Liu, G.X. On urban ground subsidence detection based on PS-DInSAR: A case study for Shanghai (in Chinese). Bull. Surv. Mapp 2009, 4, 4–8.
[6]
Damoah-Afari, P.; Ding, X.L.; Lu, Z.; Li, Z.W.; Makoto, O. Magnitude and Extent of Six Years of Land Subsidence in Shanghai Revealed by JERS-1 SAR Data. In Geoscience and Remote Sensing New Achievements; Pasquale, I., Daniele, R., Eds.; InTech: New York, NY, USA, 2010; pp. 477–496.
[7]
Wang, Z.Y.; Perissin, D.; Lin, H. Subway Tunnels Identification through Cosmo-SkyMed PSInSAR Analysis in Shanghai. Processing of IEEE Geoscience and Remote Sensing Symposium 2011, Vancouver, BC, Canada, 24–29 July 2011; pp. 1267–1270.
[8]
Leighton, J.M. Methodology and Results. GPS and PSI Integration for Monitoring Urban Land Motion. Ph.D. Thesis; University of Nottingham: Nottingham, UK, 2010.
Gabriel, A.K.; Goldstein, R.M.; Zebker, H.A. Mapping small elevation changes over large areas: Differential radar interferometry. J. Geophys. Res 1989, 94, 9183–9191.
[11]
Zebker, H.A.; Villaseno, J. Decorrelation in interferometric radar echoes. IEEE Trans. Geosci. Remote Sens 1992, 30, 950–959.
[12]
Zebker, H.A.; Rosen, P.A.; Hensley, S. Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. J. Geophys. Res 1997, 102, 7547–7563.
[13]
Sanchez, P.; Mallorquí, J.J.; Duque, S.; Monells, D. The coherent pixels technique (CPT): An advanced DInSAR technique for nonlinear deformation monitoring. Pure Appl. Geophys 2008, 165, 1167–1194.
[14]
Ferretti, A.; Prati, C.; Rocca, F. Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens 2011, 39, 8–20.
[15]
Berardino, P.; Fornaro, G.; Lanari, R. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans. Geosci. Remote Sens 2002, 40, 2375–2383.
[16]
Werner, C.; Wegmuller, U.; Strozzi, T.; Wiesmann, A. Interferometric Point Target Analysis for Deformation Mapping. Processing of IEEE Geoscience and Remote Sensing Symposium 2003, Toulouse, France, 21–25 July 2003; 7, pp. 4362–4364.
[17]
Kampes, B. The STUN Algorithm. In Radar Interferometry: Persistent Scatterer Technique; Springer: Dordrecht, The Netherlands, 2006; pp. 47–48.
[18]
Chen, Q.; Ding, X.L.; Liu, G.X. Method for optimum selection of common master acquisition for PS-DInSAR (in Chinese). Bull. Surv. Mapp 2007, 36, 395–399.
