- 1.
Bai S J. 2017. Application of InSAR Technology in Deformation Monitoring Along Subway. Beijing: China University of Geosciences (Beijing): 1-2
- 2.
Duan G Y, Liu H H, Gong H L and Chen B B. 2017. Evolution characteristics of uneven land subsidence along Beijing-Tianjin inter-city railway. Geomatics and Information Science of Wuhan University, 42(12): 1847-1853
- 3.
Fan Z L and Zhang Y H. 2019. Research progress on intelligent algorithms based ground subsidence prediction. Geomatics and Spatial Information Technology, 42(5): 183-188
- 4.
Ferretti A, Prati C and Rocca F. 2000. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 38(5): 2202-2212
- 5.
Ferretti A, Prati C and Rocca F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8-20
- 6.
Ge D Q, Zhang L, Wang Y, Li M and Liu B. 2014. Monitoring subsidence on Shanghai metro line 10 during construction and operation using high-resolution InSAR. Shanghai Land and Resources, 35(4): 62-67
- 7.
Guan L, Tang W, Dai H Y and Jia Z H. 2019. Monitoring ground subsidence in Zhengzhou city based on SBAS-InSAR technology. Beijing Surveying and Mapping, 33(4): 462-467
- 8.
Hochreiter S and Schmidhuber J. 1997. Long short-term memory. Neural Computation, 9(8): 1735-1780
- 9.
Jia X, Gong H L, Chen B B and Duan G Y. 2014. Impact of uneven land subsidence on operation of Beijing subway line 15. Remote Sensing Information, 29(6): 58-63
- 10.
Jiang D C, Zhang Y H, Zhang J X, Wu H A and Kang Y H. 2017. Uneven land subsidence along Tianjin subway lines monitored by InSAR technology. Remote Sensing Information, 32(6): 27-32
- 11.
Li H X, Zhao X H, Chi H Y and Zhang J J. 2009. Prediction and analysis of land subsidence based on improved BP neural network model. Journal of Tianjin University, 42(1): 60-64
- 12.
Lin H, Ma P F and Wang W X. 2017. Urban infrastructure health monitoring with spaceborne multi-temporal synthetic aperture radar interferometry. Acta Geodaetica et Cartographica Sinica, 46(10): 1421-1433
- 13.
Liu H R. 2016. Study on the Influence Applied to Surrounding Environment Induced by the Shield Construction of Zhengzhou Metro. Zhengzhou: Henan University of Technology: 28-45
- 14.
Liu M K. 2014. The Research of Urban Village Reconstruction in Zhengzhou City. Wuhan: Central China Normal University: 11-28
- 15.
Liu Q, Yue G S, Ding X B, Yang K, Feng G C and Xiong Z Q. 2019. Temporal and spatial characteristics analysis of deformation along Foshan subway using time series InSAR. Geomatics and Information Science of Wuhan University, 44(7): 1099-1106
- 16.
Perissin D, Wang Z Y and Lin H. 2012. Shanghai subway tunnels and highways monitoring through Cosmo-SkyMed Persistent Scatterers. ISPRS Journal of Photogrammetry and Remote Sensing, 73: 58-67
- 17.
Qin X Q, Yang M S, Wang H M, Yang T L, Lin J X and Liao M S. 2016. Application of high-resolution PS-InSAR in deformation characteristics probe of urban rail transit. Acta Geodaetica et Cartographica Sinica, 45(6): 713-721
- 18.
Wang B C, Zhu L, Pan D, Guo L F and Peng P. 2020. Research on temporal and spatial evolution law of land subsidence in Zhengzhou. Remote Sensing for Land and Resources, 32(3): 143-148
- 19.
Wang H Q, Feng G C, Xu B, Yu Y P, Li Z W, Du Y N and Zhu J J. 2017. Deriving spatio-temporal development of ground subsidence due to subway construction and operation in delta regions with PS-InSAR data: a case study in Guangzhou, China. Remote Sensing, 9(10): 1004
- 20.
Wang H Q and Li S M. 2013. Estimating of sunshine percentage using the cloud classification data from FY-2C. Journal of Remote Sensing, 17(5): 1295-1310
- 21.
Wang S H and Zhu B Q. 2021. Time series prediction for ground settlement in portal section of mountain tunnels. Chinese Journal of Geotechnical Engineering, 43(5): 813-821
- 22.
Wang Y M, Luo X J, Yu B, Hao R C and Zhang S J. 2019. Monitoring ground subsidence in Zhengzhou with InSAR. Science of Surveying and Mapping, 44(9): 100-106
- 23.
Wu S B, Le Y Y, Zhang L and Ding X L. 2020. Multi-temporal InSAR for urban deformation monitoring: progress and challenges. Journal of Radars, 9(2): 277-294
- 24.
Xi L T. 2020. Research on Monitoring Data Forecasting Method of Mining-Induced Overburden Deformation Based on LSTM. Xi’an: Xi’an University of Science and Technology: 26-52
- 25.
Zhang J S and Liu K. 2021. Land subsidence monitoring in Zhengzhou based on sentinel-1 A data. Shanxi Architecture, 47(6): 72-75
- 26.
Zhu X X, Chen M, Gong H L, Li X J, Yu J, Zhu L, Zhou Y Y and Li Y. 2018. The subsidence monitoring along Beijing subway network based on MT-InSAR. Journal of Geo-Information Science, 20(12): 1810-1819