Abstract
Land subsidence is a worldwide geological environment problem, which can bring about lasting and serious harm to linear engineering and urban construction. In this paper, land subsidence along the linear engineering was monitored and analyzed by the Synthetic Aperture Radar (SAR) images, high-precision leveling results, groundwater level monitoring data. Combined with Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) technology, spatial analysis technology of geographic information system and contribution rate method, the spatial and temporal evolution characteristics, influencing factors, and the contribution rate of each factor to land subsidence along the Lunan high-speed railway from 2016 to 2018 were researched. The accuracy of subsidence results by InSAR monitoring was verified by the linear fitting method and root mean square error method. The influence of uneven subsidence on linear engineering was discussed based on the evaluation results of subsidence gradient zoning. The results indicate that the maximum accumulated subsidence along the Lunan high-speed railway is 499 mm. Multiple subsidence center areas have been formed in the study area, with the maximum subsidence rate exceeding -55 mm/yr. The maximum subsidence gradient and curvature radius of the Lunan high-speed railway meet the requirements of line smoothness when the train speed is 350 km/h. The coal mining, compressible layer thickness, and changes in groundwater level are positively correlated with land subsidence, the total contribution rate to land subsidence is more than 90%. The research results provide scientific support for the prevention and control of land subsidence along the linear engineering.
Similar content being viewed by others
References
Abidin HZ, Andreas H, Djaja R, Darmawan D, Gamal M (2008) Land subsidence characteristics of Jakarta between 1997 and 2005, as estimated using GPS surveys. GPS Solutions 12(1):23–32, DOI: https://doi.org/10.1007/s10291-007-0061-0
Bawden GW, Thatcher W, Stein RS, Hudnut KW, Peltzer G (2001) Tectonic contraction across Los Angeles after removal of groundwater pumping effects. Nature 412(6849):812–815, DOI: https://doi.org/10.1038/35090558
Berardino P, Fornaro G, Lanari R, Sansosti E (2002) A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing 40(11):2375–2383, DOI: https://doi.org/10.1109/TGRS.2002.803792
Biot MA (1941) General theory of three-dimensional consolidation. Journal of Applied Physics 12(2):155–164, DOI: https://doi.org/10.1063/1.1712886
Castellazzi P, Garfias J, Martel R, Brouard C, Rivera A (2017) InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico. International Journal of Applied Earth Observation and Geoinformation 63:33–44, DOI: https://doi.org/10.1016/j.jag.2017.06.011
Chaussard E, Wdowinski S, Cabral-Cano E, Amelung F (2014) Land subsidence in central Mexico detected by ALOS InSAR time-series. Remote Sensing of Environment 140:94–106, DOI: https://doi.org/10.1016/j.rse.2013.08.038
Corbau C, Simeoni U, Zoccarato C, Mantovani G, Teatini P (2019) Coupling land use evolution and subsidence in the Po Delta, Italy: Revising the past occurrence and prospecting the future management challenges. Science of the Total Environment 654:1196–1208, DOI: https://doi.org/10.1016/j.scitotenv.2018.11.104
Cui ZD (2018) Land subsidence induced by the engineering environmental effect. Springer Nature Singapore, Singapore
Ding M, Heiser M, Huebl J, Fuchs S (2016) Regional vulnerability assessment for debris flows in China — A CWS approach. Landslides 13(3):537–550, DOI: https://doi.org/10.1007/s10346-015-0578-1
Ding PP, Jia C, Di ST, Wang LL, Bian C, Yang X (2020) Analysis and prediction of land subsidence along significant linear engineering. Bulletin of Engineering Geology and the Environment 70(10):5125–5139, DOI: https://doi.org/10.1007/s10064-020-01872-1
Du Z, Ge L, Ng AH, Zhu Q, Yang X, Li L (2018) Correlating the subsidence pattern and land use in Bandung, Indonesia with both Sentinel-1/2 and ALOS-2 satellite images. International Journal of Applied Earth Observation and Geoinformation 67:54–68, DOI: https://doi.org/10.1016/j.jag.2018.01.001
Duan G, Gong H, Liu H, Zhang Y, Chen B, Lei K (2016) Monitoring and analysis of land subsidence along Beijing-Tianjin inter-city railway. Journal of the Indian Society of Remote Sensing 44(6):915–931, DOI: https://doi.org/10.1007/s12524-016-0556-7
Eldrandaly KA, Abu-Zaid MS (2011) Comparison of six GIS-based spatial interpolation methods for estimating air temperature in western Saudi Arabia. Journal of Environmental Informatics 18(1):38–45, DOI: https://doi.org/10.3808/jei.201100197
Ferretti A, Prati C, Rocca F (2000) Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing 38(51):2202–2212, DOI: https://doi.org/10.1109/36.868878
Guo L, Gong H, Zhu F, Zhu L, Zhang Z, Zhou C, Gao M, Sun Y (2019) Analysis of the spatiotemporal variation in land subsidence on the Beijing Plain, China. Remote Sensing 11(10), DOI: https://doi.org/10.3390/rs11101170
Hsieh C, Shih T, Hu J, Tung H, Huang M, Angelier J (2011) Using differential SAR interferometry to map land subsidence: A case study in the pingtung plain of SW Taiwan. Natural Hazards 58(3): 1311–1332, DOI: https://doi.org/10.1007/s11069-011-9734-7
Hu B, Chen J, Zhang X (2019) Monitoring the land subsidence area in a coastal urban area with InSAR and GNSS. Sensors 19(14), DOI: https://doi.org/10.3390/s19143181
Hu RL, Yue ZQ, Wang LC, Wang SJ (2004) Review on current status and challenging issues of land subsidence in China. Engineering Geology 76(1–2):65–77, DOI: https://doi.org/10.1016/j.enggeo.2004.06.006
Hung W, Hwang C, Chang C, Yen J, Liu C, Yang W (2010) Monitoring severe aquifer-system compaction and land subsidence in Taiwan using multiple sensors: Yunlin, the southern Choushui River Alluvial Fan. Environmental Earth Sciences 59(7):1535–1548, DOI: https://doi.org/10.1007/s12665-009-0139-9
Jia C, Zhang Y, Han J, Xu X (2017) Susceptibility area regionalization of land subsidence based on extenics theory. Cluster Computing 20(1):53–66, DOI: https://doi.org/10.1007/s10586-016-0720-4
Lanari R, Mora O, Manunta M, Mallorqui JJ, Berardino P, Sansosti E (2004) A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing 42(7):1377–1386, DOI: https://doi.org/10.1109/TGRS.2004.828196
Liosis N, Marpu PR, Pavlopoulos K, Ouarda TBMJ (2018) Ground subsidence monitoring with SAR interferometry techniques in the rural area of Al Wagan, UAE. Remote Sensing of Environment 216: 276–288, DOI: https://doi.org/10.1016/j.rse.2018.07.001
Manunta M, Marsella M, Zeni G, Sciotti M, Atzori S, Lanari R (2008) Two-scale surface deformation analysis using the SBAS-DInSAR technique: A case study of the city of Rome, Italy. International Journal of Remote Sensing 29(6):1665–1684, DOI: https://doi.org/10.1080/01431160701395278
Rahmati O, Golkarian A, Biggs T, Keesstra S, Mohammadi F, Daliakopoulos IN (2019) Land subsidence hazard modeling: Machine learning to identify predictors and the role of human activities. Journal of Environmental Management 236:466–480, DOI: https://doi.org/10.1016/j.jenvman.2019.02.020
Schmidt DA, Burgmann R (2003) Time-dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometric synthetic aperture radar data set. Journal of Geophysical Research-Solid Earth 108(2416B9), DOI: https://doi.org/10.1029/2002JB002267
Smith R, Knight R (2019) Modeling land subsidence using insar and airborne electromagnetic data. Water Resources Research 55(4): 2801–2819, DOI: https://doi.org/10.1029/2018WR024185
Strozzi T, Caduff R, Wegmueller U, Raetzo H, Hauser M (2017) Widespread surface subsidence measured with satellite SAR interferometry in the Swiss alpine range associated with the construction of the gotthard base tunnel. Remote Sensing of Environment 190:1–12, DOI: https://doi.org/10.1016/j.rse.2016.12.007
Strozzi T, Delaloye R, Poffet D, Hansmann J, Loew S (2011) Surface subsidence and uplift above a headrace tunnel in metamorphic basement rocks of the Swiss Alps as detected by satellite SAR interferometry. Remote Sensing of Environment 115(6):1353–1360, DOI: https://doi.org/10.1016/j.rse.2011.02.001
Suganthi S, Elango L (2020) Estimation of groundwater abstraction induced land subsidence by SBAS technique. Journal of Earth System Science 129(1), DOI: https://doi.org/10.1007/s12040-019-1298-z
Wang H, Jia L, Steffen H, Wu P, Jiang L, Hsu H, Xiang L, Wang Z, Hu B (2013) Increased water storage in North America and Scandinavia from GRACE gravity data. Nature Geoscience 6(1):38–42, DOI: https://doi.org/10.1038/NGEO1652
Wempen JM (2020) Application of DInSAR for short period monitoring of initial subsidence due to longwall mining in the mountain west United States. International Journal of Mining Science and Technology 30(1SI):33–37, DOI: https://doi.org/10.1016/j.ijmst.2019.12.011
Yalvac S (2020) Validating InSAR-SBAS results by means of different GNSS analysis techniques in medium-and high-grade deformation areas. Environmental Monitoring and Assessment 192(2), DOI: https://doi.org/10.1007/s10661-019-8009-8
Yan Y, DOIn M, Lopez-Quiroz P, Tupin F, Fruneau B, Pinel V, Trouve E (2012) Mexico city subsidence measured by insar time series: Joint analysis using PS and SBAS Approaches. IEEE Journal of Selected Topics in Applied Earth 5(4):1312–1326, DOI: https://doi.org/10.1109/JSTARS.2012.2191146
Yu H, Gong H, Chen B, Liu K, Gao M (2020a) Analysis of the influence of groundwater on land subsidence in Beijing based on the geographical weighted regression (GWR) model. Science of the Total Environment 738(139405), DOI: https://doi.org/10.1016/j.scitotenv.2020.139405
Yu Q, Wang Q, Yan X, Yang T, Song S, Yao M, Zhou K, Huang X (2020b) Ground deformation of the chongming east shoal reclamation area in shanghai based on SBAS-InSAR and laboratory tests. Remote Sensing 12(6), DOI: https://doi.org/10.3390/rs12061016
Zebker HA, Rosen PA, Hensley S (1997) Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. Journal of Geophysical Research Solid Earth 102(B4):7547–7563, DOI: https://doi.org/10.1029/96JB03804
Zhang J, Huang H, Bi H (2015) Land subsidence in the modern Yellow River Delta based on InSAR time series analysis. Natural Hazards 75(3):2385–2397, DOI: https://doi.org/10.1007/s11069-014-1434-7
Zhang Y, Yan X, Yang T, Wu J, Wu J (2020a) Three-dimensional numerical investigation of pore water pressure and deformation of pumped aquifer systems. Groundwater 58(2):278–290, DOI: https://doi.org/10.1111/gwat.12909
Zhang L, Zhang X, Wu J, Zhao D, Fu H (2020b) Rockburst prediction model based on comprehensive weight and extension methods and its engineering application. Bulletin of Engineering Geology and the Environment 79(9):4891–4903, DOI: https://doi.org/10.1007/s10064-020-01861-4
Zhou C, Gong H, Chen B, Li X, Li J, Wang X, Gao M, Si Y, Guo L, Shi M, Duan G (2019) Quantifying the contribution of multiple factors to land subsidence in the Beijing Plain, China with machine learning technology. Geomorphology 335:48–61, DOI: https://doi.org/10.1016/j.geomorph.2019.03.017
Acknowledgments
We would like to acknowledge the financial support from the National Natural Science Foundation of China (Grant No.: 42007234).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ding, P., Jia, C., Di, S. et al. Analysis and Evaluation of Land Subsidence along Linear Engineering Based on InSAR Data. KSCE J Civ Eng 25, 3477–3491 (2021). https://doi.org/10.1007/s12205-021-0201-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12205-021-0201-z