Monitoring land subsidence through improved CAESAR algorithm in time-series InSAR processing

References

• Alam MS, Kumar D, Chatterjee RS. 2022. Improving the capability of integrated DInSAR and PSI approach for better detection, monitoring, and analysis of land surface deformation in underground mining environment. Geocarto Int. 37(12):3607–3641.
   Web of Science ®Google Scholar
• Ansari H, De Zan F, Adam N, Goel K, Bamler R. 2016. Sequential estimator for distributed scatterer interferometry. In: Proceedings of IGARSS 2016. Beijing, China: IEEE.
   Google Scholar
• Berardino P, Fornaro G, Lanari R, Sansosti E. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans Geosci Remote Sens. 40:2375–2383.
   Web of Science ®Google Scholar
• Cao N, Lee H, Jung HC. 2015. Mathematical framework for phase-triangulation algorithms in distributed-scatterer interferometry. IEEE Geosci Remote Sens Lett. 12:1838–1842.
   Web of Science ®Google Scholar
• Cao N, Lee H, Jung HC. 2016. A phase-decomposition-based PSInSAR processing method. IEEE Trans Geosci Remote Sens. 54(2):1074–1090.
   Web of Science ®Google Scholar
• Chen Y, Li Z, Penna NT. 2017. Interferometric synthetic aperture radar atmospheric correction using a GPS-based iterative tropospheric decomposition model. Remote Sens Environ. 204:109–121.
   Web of Science ®Google Scholar
• Chen Y, Tan K, Yan S, Zhang K, Zhang H, Liu X, Li H, Sun Y. 2019. Monitoring land surface displacement over Xuzhou (China) in 2015-2018 through PCA-based correction applied to SAR interferometry. Remote Sens. 11:1494.
   Google Scholar
• Costantini F, Mouratidis A, Schiavon G, Sarti F. 2016. Advanced InSAR techniques for deformation studies and for simulating the PS-assisted calibration procedure of Sentinel-1 data: case study from Thessaloniki (Greece), based on the Envisat/ASAR archive. Int J Remote Sens. 37(4):729–744.
   Web of Science ®Google Scholar
• Ding X, Li Z, Zhu J, Feng G, Long J. 2008. Atmospheric effects on InSAR measurements and their mitigation. Sensors. 8(9):5426–5448. doi: 10.3390/s8095426.
   PubMed Web of Science ®Google Scholar
• Du Z, Ge L, Ng A, Li X. 2018. Investigation on mining subsidence over Appin-West Cliff Colliery using time-series SAR interferometry. Int J Remote Sens. 39(5):1528–1547.
   Web of Science ®Google Scholar
• Ferretti A, Prati C, Rocca F. 2000. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Trans Geosci Remote Sens. 38:2202–2212.
   Web of Science ®Google Scholar
• Ferretti A, Fumagalli A, Novali F, Prati C, Rocca F, Rucci A. 2011. A new algorithm for processing interferometric data-stacks: squeeSAR. IEEE Trans Geosci Remote Sens. 49:3460–3470.
   Web of Science ®Google Scholar
• Fornaro G, Verde S, Reale D, Pauciullo A. 2015. CAESAR: an approach based on covariance matrix decomposition to improve multibaseline-multitemporal interferometric SAR processing. IEEE Trans Geosci Remote Sens. 53(4):2050–2065.
   Web of Science ®Google Scholar
• He Q, Zhang Y, Wu H, Luo Y. 2021. Mining subsidence monitoring with modified time-series SAR interferometry method based on the multi-level processing strategy. IEEE Access. 9:106039–106048. doi: 10.1109/ACCESS.2021.3099633.
   Web of Science ®Google Scholar
• Hooper A. 2008. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophys Res Lett. 35: l16302.
   Web of Science ®Google Scholar
• Hu B, Zhou J, Wang J, Chen Z, Wang D, Xu S. 2009. Risk assessment of land subsidence at Tianjin coastal area in China. Environ Earth Sci. 59(2):269–276. doi: 10.1007/s12665-009-0024-6.
   Web of Science ®Google Scholar
• Jiang M, Ding X, Hanssen RF, Malhotra R, Chang L. 2015. Fast statistically homogeneous pixel selection for covariance matrix estimation for multitemporal InSAR. IEEE Trans Geosci Remote Sens. 53:1213–1224.
   Web of Science ®Google Scholar
• Jiang M, Ding X, He X, Li Z, Shi G. 2016. FaSHPS-InSAR technique for distributed scatterers: a case study over the lost hills oil field, California. Chinese J Geophys. 59(10):3592–3603.
   Google Scholar
• Jiang M, Guarnieri AM. 2020. Distributed scatterer interferometry with the refinement of spatiotemporal coherence. IEEE Trans Geosci Remote Sens. 58(6):3977–3987.
   Web of Science ®Google Scholar
• Li B, Li G, Na J, Tu L, Fan J, Wu Y. 2022. Identification of surface deformation caused by geothermal resource extraction using SBAS time-series technology. Bull Surv Mapp. (2):43–49.
   Google Scholar
• Li T. 2014. Deformation monitoring by multi-temporal InSAR with both point and distributed scatterers [PhD dissertation]. Chengdu, China: Southwest Jiaotong University.
   Google Scholar
• Li T, Zhang H, Fan H, Zheng C, Liu J. 2021. Position inversion of goafs in deep coal seams based on DS-InSAR Data and the probability integral methods. Remote Sens. 13:2898.
   Google Scholar
• Liu G, Luo X, Chen Q, Huang D, Ding X. 2008. Detecting land subsidence in Shanghai by PS-networking SAR interferometry. Sensors. 8(8):4725–4741. doi: 10.3390/s8084725.
   PubMed Web of Science ®Google Scholar
• Liu J, Wang Y, Li Y, Dang L, Liu X, Zhao H, Yan S. 2019. Underground coal fires identification and monitoring using time-series InSAR with persistent and distributed scatterers: a case study of Miquan coal fire zone in Xinjiang, China. IEEE Access. 7:164492–164506. doi: 10.1109/ACCESS.2019.2952363.
   Web of Science ®Google Scholar
• Liu L, Xue C. 2019. Explanatory comment on the geography and construction of Xiongxian county from historic documents. Archit J. (S1):164–168.
   Google Scholar
• Liu X. 2018. Study on ground subsidence monitoring in mining area based on multi spaceborne SAR images [PhD dissertation]. Xuzhou, China: China University of Mining & Technology.
   Google Scholar
• Liu Y, Fan H, Wang L, Zhuang H. 2020. Monitoring of surface deformation in a low coherence area using distributed scatterers InSAR: case study in the Xiaolangdi Basin of the Yellow River, China. Bull Eng Geol Environ. 80(1):25–39. doi: 10.1007/s10064-020-01929-1.
   Web of Science ®Google Scholar
• Liu Y, Zhao C, Zhang Q, Yang C, Zhang J. 2018. Land subsidence in Taiyuan, China, monitored by InSAR technique with multisensor SAR datasets from 1992 to 2015. IEEE J Sel Topics Appl Earth Observ Remote Sens. 11(5):1509–1519.
   Web of Science ®Google Scholar
• Lu L, Fan H, Liu J, Liu JL, Yin J. 2019. Time series mining subsidence monitoring with temporarily coherent points interferometry synthetic aperture radar: a case study in Peixian, China. Environ Earth Sci. 78(15):461. doi: 10.1007/s12665-019-8475-x.
   Web of Science ®Google Scholar
• Mora O, Mallorqui JJ, Broquetas A. 2003. Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images. IEEE Trans Geosci Remote Sens. 41:2243–2253.
   Web of Science ®Google Scholar
• Pang Z, Kong Y, Pang J, Hu S, Wang J. 2017. Geothermal resources and development in Xiongan New Area. Bull Chinese Acad Sci. 32(11):1224–1230.
   Google Scholar
• Parizzi A,Brcic R. 2011. Adaptive InSAR Stack Multilooking Exploiting Amplitude Statistics: A Comparison Between Different Techniques and Practical Results. IEEE Geosci Remote Sensing Lett. 8(3):441–445. doi: 10.1109/LGRS.2010.2083631.
   Web of Science ®Google Scholar
• Pepe A, Yang Y, Manzo M, Lanari R. 2015. Improved EMCF-SBAS processing chain based on advanced techniques for the noise-filtering and selection of small baseline multi-look DInSAR interferograms. IEEE Trans Geosci Remote Sens. 53(8):4394–4417.
   Web of Science ®Google Scholar
• Robertson L, Andrew D, McNairn H, Hosseini M, Mitchell S, Abelleyra D, Verón S, Cosh MH. 2020. Synthetic aperture radar (SAR) image processing for operational space-based agriculture mapping. Int J Remote Sens. 41(18):7112–7144.
   Web of Science ®Google Scholar
• Sun Q, Jiang L, Jiang M, Lin H, Ma P, Wang H. 2018. Monitoring coastal reclamation subsidence in Hong Kong with distributed scatterer interferometry. Remote Sens. 10:1738.
   Google Scholar
• Verde S, Reale D, Pauciullo A, Fornaro G. 2018. Improved small baseline processing by means of CAESAR eigen-interferograms decomposition. ISPRS J Photogramm Remote Sens. 139:1–13. doi: 10.1016/j.isprsjprs.2018.02.019.
   Web of Science ®Google Scholar
• Wang H, Wang Y, Jiao X, Qian G. 2014. Risk management of land subsidence in Shanghai. Desalination Water Treat. 52:1122–1129.
   Web of Science ®Google Scholar
• Wang M, Li T, Jiang L. 2016. Monitoring reclaimed lands subsidence in Hong Kong with InSAR technique by persistent and distributed scatterers. Nat Hazards. 82(1):531–543. doi: 10.1007/s11069-016-2196-1.
   Web of Science ®Google Scholar
• Wang Y, Zhu X. 2016. Robust estimators for multipass SAR interferometry. IEEE Trans Geosci Remote Sens. 54(2):968–980.
   Web of Science ®Google Scholar
• Xia J, Zhang Y. 2017. Water resource and pollution safeguard for Xiongan New Area construction and its sustainable development. Bull Chinese Acad Sci. 32(11):1199–1205.
   Google Scholar
• Xu X, Zhao D, Ma C, Lian D. 2021. Monitoring subsidence deformation of Suzhou subway using InSAR timeseries analysis. IEEE Access. 9:3400–3416. doi: 10.1109/ACCESS.2020.3047574.
   Web of Science ®Google Scholar
• Yazici BV, Gormus ET. 2021. Investigating persistent scatterer InSAR (PSInSAR) technique efficiency for landslides mapping: a case study in Artvin dam area, in Turkey. Geocarto Int. 37(8):2293–2311.
   Web of Science ®Google Scholar
• Yu Z, Huang G, Zhang C, Zhao X. 2021. SBAS-InSAR deformation reconstruction based on low-rank matrix completion in Southern Zibo, China. Arabian J Geosci. 14(4):1–9.
   Google Scholar
• Zhang L, Ding X, Lu Z. 2011. Ground settlement monitoring based on temporarily coherent points between two SAR acquisitions. ISPRS J Photogramm Remote Sens. 66(1):146–152. doi: 10.1016/j.isprsjprs.2010.10.004.
   Web of Science ®Google Scholar
• Zhang Y, Li M, Wu H, Liu B, Kang Y, He Q. 2019. Ground subsidence monitoring over full territory of Jiangsu province with InSAR. Sci Surv Mapp. 44(6):114–120.
   Google Scholar
• Zhang Y, Liu B, Wu H, Cheng X, Kang YH. 2018. Ground subsidence in Xiong’an new area from 2012 to 2016 monitored by InSAR technique. J Earth Sci Environ. 40(5):652–662.
   Google Scholar
• Zhang Y, Wu H, Kang Y, Zhu C. 2016. Ground subsidence in the Beijing-Tianjin-Hebei region from 1992 to 2014 revealed by multiple SAR stacks. Remote Sens. 8:675.
   Google Scholar
• Zhang Y, Wu H, Li M, Kang Y, Lu Z. 2021. Investigating ground subsidence and the causes over the whole Jiangsu province, China using sentinel-1 SAR data. Remote Sens. 13(2):179.
   Google Scholar