Articles | Volume 19, issue 10
https://doi.org/10.5194/nhess-19-2229-2019
https://doi.org/10.5194/nhess-19-2229-2019
Research article
 | 
10 Oct 2019
Research article |  | 10 Oct 2019

InSAR technique applied to the monitoring of the Qinghai–Tibet Railway

Qingyun Zhang, Yongsheng Li, Jingfa Zhang, and Yi Luo

Related authors

Monitoring and analysis of Woda landslide stability (China) combined with InSAR, GNSS and meteorological data
Bingquan Li, Wenliang Jiang, Yongsheng Li, Yi Luo, Haitao Qian, Yanchao Wang, Qisong Jiao, Qingyun Zhang, Zihan Zhou, and Jingfa Zhang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-101,https://doi.org/10.5194/nhess-2021-101, 2021
Manuscript not accepted for further review
Short summary
Three-dimensional deformation field analysis of the 2016 Kumamoto Mw 7.1 earthquake
Qingyun Zhang, Jingfa Zhang, Yongsheng Li, Bingqun Li, Quancai Xie, Sanming Luo, and Qingzun Ma
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-408,https://doi.org/10.5194/nhess-2020-408, 2021
Preprint withdrawn

Related subject area

Databases, GIS, Remote Sensing, Early Warning Systems and Monitoring Technologies
Impact of topography on in situ soil wetness measurements for regional landslide early warning – a case study from the Swiss Alpine Foreland
Adrian Wicki, Peter Lehmann, Christian Hauck, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 23, 1059–1077, https://doi.org/10.5194/nhess-23-1059-2023,https://doi.org/10.5194/nhess-23-1059-2023, 2023
Short summary
Earthquake building damage detection based on synthetic-aperture-radar imagery and machine learning
Anirudh Rao, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, and Sang-Ho Yun
Nat. Hazards Earth Syst. Sci., 23, 789–807, https://doi.org/10.5194/nhess-23-789-2023,https://doi.org/10.5194/nhess-23-789-2023, 2023
Short summary
Assessing riverbank erosion in Bangladesh using time series of Sentinel-1 radar imagery in the Google Earth Engine
Jan Freihardt and Othmar Frey
Nat. Hazards Earth Syst. Sci., 23, 751–770, https://doi.org/10.5194/nhess-23-751-2023,https://doi.org/10.5194/nhess-23-751-2023, 2023
Short summary
Quantifying unequal urban resilience to rainfall across China from location-aware big data
Jiale Qian, Yunyan Du, Jiawei Yi, Fuyuan Liang, Nan Wang, Ting Ma, and Tao Pei
Nat. Hazards Earth Syst. Sci., 23, 317–328, https://doi.org/10.5194/nhess-23-317-2023,https://doi.org/10.5194/nhess-23-317-2023, 2023
Short summary
Comparison of machine learning techniques for reservoir outflow forecasting
Orlando García-Feal, José González-Cao, Diego Fernández-Nóvoa, Gonzalo Astray Dopazo, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci., 22, 3859–3874, https://doi.org/10.5194/nhess-22-3859-2022,https://doi.org/10.5194/nhess-22-3859-2022, 2022
Short summary

Cited articles

Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E.: A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms, IEEE T. Geosci. Remote, 40, 2375–2383, https://doi.org/10.1109/TGRS.2002.803792, 2002. 
Biggs, J., Wright, T., Lu Z., and Parsons, B.: Multi-interferogram method for measuring interseismic deformation: Denali Fault, Alaska, Geophys. J. Roy. Astro. Soc., 170, 1165001179, https://doi.org/10.1111/j.1365-246X.2007.03415.x, 2007. 
Brown, J., Hinkel, K. M., and Nelson, F. E.: The Circumpolar Activelayer Monitoring (CALM) Program: Research Designs and Initial Results, Polar Geogr., 24, 166–258, https://doi.org/10.1080/10889370009377698, 2000. 
Chang, Z. Q., Liu, X. M., Xue, T. F., and Yang, R. R.: Investigating ground subsidence in Beijing by using interferogram stacking InSAR, IEEE International Conference on Spatial Data Mining & Geographical Knowledge Services, 29 June–1 July, Fuzhou, China, https://doi.org/10.1109/ICSDM.2011.5969068, 2011. 
Chen, F. L., Lin, H., Li, Z., and Zhou, J. M.: Interaction between permafrost and infrastructure along the Qinghai-Tibet Railway detected via jointly analysis of C- and L-band small baseline SAR interferometry, Remote Sens. Environ., 123, 532–540, https://doi.org/10.1016/j.rse.2012.04.020, 2012. 
Download
Short summary
Before the opening of the railway, the deformation of the Qinghai–Tibet Railway was very small and considered stable. After opening, the overall stability of the railway section was good. The main deformation areas are concentrated in the areas where railway lines turn and geological disasters are concentrated. In order to ensure the safety of railway operation, it is necessary to carry out long-term time series observation along the Qinghai–Tibet Railway.
Altmetrics
Final-revised paper
Preprint