Advanced search
Publication Cover
GIScience & Remote Sensing Volume 60, 2023 - Issue 1
Submit an article Journal homepage
1,002
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Reconstruction of spatially continuous time-series land subsidence based on PS-InSAR and improved MLS-SVR in Beijing Plain area

Mingyuan Lyua Institute of Disaster Prevention, Sanhe, Hebei, China;b Hebei Key Laboratory of Earthquake Dynamics, Sanhe, Hebei, China;c College of Geospatial Information Science and Technology, Capital Normal University, Beijing, ChinaView further author information
,
Xiaojuan Lic College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaCorrespondence[email protected]
View further author information
,
Yinghai Kec College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaView further author information
,
Jiyi Jianga Institute of Disaster Prevention, Sanhe, Hebei, China;b Hebei Key Laboratory of Earthquake Dynamics, Sanhe, Hebei, ChinaView further author information
,
Lin Zhuc College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaView further author information
,
Lin Guoc College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaView further author information
,
Huili Gongc College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaView further author information
,
Beibei Chenc College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaView further author information
,
Zhihe Xua Institute of Disaster Prevention, Sanhe, Hebei, China;b Hebei Key Laboratory of Earthquake Dynamics, Sanhe, Hebei, ChinaView further author information
,
Ke Zhangc College of Geospatial Information Science and Technology, Capital Normal University, Beijing, China;d Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Capital Normal University, Beijing, ChinaView further author information
&
Zhanpeng Wangc College of Geospatial Information Science and Technology, Capital Normal University, Beijing, ChinaView further author information
 show all
Article: 2230689 | Received 07 Dec 2022, Accepted 22 Jun 2023, Published online: 13 Jul 2023

References

  • Abushandi, E., and A. Abualkishik. 2020. “Shoreline Erosion Assessment Modelling for Sohar Region: Measurements, Analysis, and Scenario.” Scientific Reports 10:1–22. https://doi.org/10.1038/s41598-020-61033-y.
  • Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti. 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. https://doi.org/10.1109/TGRS.2002.803792.
  • Bui, L. K., P. V. Le, P. D. Dao, N. Q. Long, H. V. Pham, H. H. Tran, and L. Xie. 2021. “Recent Land Deformation Detected by Sentinel-1A InSar Data (2016–2020) Over Hanoi, Vietnam, and the Relationship with Groundwater Level Change.” GIScience & Remote Sensing 58 (2): 161–179. https://doi.org/10.1080/15481603.2020.1868198.
  • Cao L. 2003. “Support vector machines experts for time series forecasting.“ Neuro computing 51:321–339. https://doi.org/10.1016/S0925-2312(02)00577-5.
  • Cao, N., H. Lee, and H. C. Jung. 2016. “A Phase-Decomposition-Based PSInSar Processing Method.” IEEE Transactions on Geoscience and Remote Sensing 54 (2): 1074–1090. https://doi.org/10.1109/TGRS.2015.2473818.
  • Chen, B., H. Gong, Y. Chen, K. Lei, C. Zhou, Y. Si, X. Li, Y. Pan, and M. Gao. 2021. “Investigating Land Subsidence and Its Causes Along Beijing High-Speed Railway Using Multi-Platform InSar and a Maximum Entropy Model.” International Journal of Applied Earth Observations & Geoinformation 96:102284. https://doi.org/10.1016/j.jag.2020.102284.
  • Chen, W., H. Gong, B. Chen, K. Liu, M. Gao, and C. Zhou. 2017a. “Spatiotemporal Evolution of Land Subsidence Around a Subway Using InSar Time-Series and the Entropy Method.” GIScience & Remote Sensing 54 (1): 78–94. https://doi.org/10.1080/15481603.2016.1257297.
  • Chen, B., H. Gong, Y. Chen, X. Li, and X. Zhao. 2020. “Land Subsidence and Its Relation with Groundwater Aquifers in Beijing Plain of China.” Science of the Total Environment 735:139111. https://doi.org/10.1016/j.scitotenv.2020.139111.
  • Chen, B., H. Gong, X. Li, K. Lei, L. Zhu, M. Gao, and C. Zhou. 2017b. “Characterization and Causes of Land Subsidence in Beijing, China.” International Journal of Remote Sensing 38:808–826. https://doi.org/10.1080/01431161.2016.1259674.
  • Chen, M., R. Tomás, Z. Li, M. Motagh, T. Li, L. Hu, H. Gong, X. Li, J. Yu, and X. Gong. 2016. “Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry.” Remote Sensing 8 (6): 468. https://doi.org/10.3390/rs8060468.
  • Dai, Z., J. Guldmann, and Y. Hu. 2018. “Spatial Regression Models of Park and Land-Use Impacts on the Urban Heat Island in Central Beijing.” Science of the Total Environment 626:1136–1147. https://doi.org/10.1016/j.scitotenv.2018.01.165.
  • Duan, L., H. Gong, B. Chen, C. Zhou, K. Lei, M. Gao, H. Yu, Q. Cao, and J. Cao. 2020. “An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network During the Past 15 Years.” Remote Sensing 12 (13): 2125. https://doi.org/10.3390/rs12132125.
  • Duan, P., K. Xie, T. Guo, and X. Huang. 2011. “Short-Term Load Forecasting for Electric Power Systems Using the PSO-SVR and FCM Clustering Techniques.” Energies 4 (1): 173–184. https://doi.org/10.3390/en4010173.
  • Ferretti, A., A. Fumagalli, F. Novali, C. Prati, F. Rocca, and A. Rucci. 2011. “A New Algorithm for Processing Interferometric Data-Stacks: SqueeSar.” IEEE Transactions on Geoscience and Remote Sensing 49 (9): 3460–3470. https://doi.org/10.1109/TGRS.2011.2124465.
  • Ferretti, A., C. Prati, and F. Rocca. 2000. “Nonlinear Subsidence Rate Estimation Using Permanent Scatterers in Differential SAR Interferometry.” IEEE Transactions on Geoscience and Remote Sensing 38 (5): 2202–2212. https://doi.org/10.1109/36.868878.
  • Foroughnia, F., S. Nemati, Y. Maghsoudi, and D. Perissin. 2019. “An Iterative PS-Insar Method for the Analysis of Large Spatio-Temporal Baseline Data Stacks for Land Subsidence Estimation.” International Journal of Applied Earth Observation and Geoinformation 74:248–258. https://doi.org/10.1016/j.jag.2018.09.018.
  • Gao, M., H. Gong, B. Chen, X. Li, C. Zhou, M. Shi, Y. Si, Z. Chen, and G. Duan. 2018. “Regional Land Subsidence Analysis in Eastern Beijing Plain by InSar Time Series and Wavelet Transforms.” Remote Sensing 10 (3): 365. https://doi.org/10.3390/rs10030365.
  • Gao, M., H. Gong, X. Li, B. Chen, C. Zhou, M. Shi, L. Guo, Z. Chen, Z. Ni, and G. Duan 2019. “Land Subsidence and Ground Fissures in Beijing Capital International Airport (BCIA): Evidence from Quasi-PS InSar Analysis.” Remote Sensing, 11, 1466. https://doi.org/10.3390/rs11121466.
  • Garg, S., M. Motagh, J. Indu, and V. Karanam. 2022. “Tracking Hidden Crisis in India’s Capital from Space: Implications of Unsustainable Groundwater Use.” Scientific Reports 12 (1): 651. https://doi.org/10.1038/s41598-021-04193-9.
  • Gong, H., Y. Pan, L. Zheng, X. Li, L. Zhu, C. Zhang, Z. Huang, Z. Li, H. Wang, and C. Zhou. 2018. “Long-Term Groundwater Storage Changes and Land Subsidence Development in the North China Plain (1971-2015).” Hydrogeology Journal 26 (5): 1417–1427. https://doi.org/10.1007/s10040-018-1768-4.
  • Guo L, Gong, H, Li, J., Zhu, L, Xue, A., Liao, L., Zhou, J., et al . 2020. “Understanding Uneven Land Subsidence in Beijing, China, Using a Novel Combination of Geophysical Prospecting and InSAR.“ Geophysical Research Letters 47 (16). https://doi.org/10.1029/2020GL088676.
  • Herrera-Garcia, G., P. Ezquerro, R. Tomas, M. Bejar-Pizarro, J. Lopez-Vinielles, M. Rossi, R. M. Mateos, et al. 2021. “Mapping the Global Threat of Land Subsidence.” Science: Advanced Materials and Devices 371 (6524): 34–36. https://doi.org/10.1126/science.abb8549.
  • Hooper, A. 2008. “A Multi-Temporal InSar Method Incorporating Both Persistent Scatterer and Small Baseline Approaches.” Geophysical Research Letters 35 (16). https://doi.org/10.1029/2008GL034654.
  • Hu, L., K. Dai, C. Xing, Z. Li, R. Tomás, B. Clark, X. Shi, et al. 2019. “Land Subsidence in Beijing and Its Relationship with Geological Faults Revealed by Sentinel-1 InSar Observations.” International Journal of Applied Earth Observation and Geoinformation 82:101886. https://doi.org/10.1016/j.jag.2019.05.019.
  • Ikuemonisan, F. E., V. C. Ozebo, and O. B. Olatinsu. 2020. “Geostatistical Evaluation of Spatial Variability of Land Subsidence Rates in Lagos, Nigeria.” Geodesy and Geodynamics 11 (5): 316–327. https://doi.org/10.1016/j.geog.2020.04.001.
  • Kampes, B. M. 2005. “Displacement parameter estimation using Permanent Scatterer Interferometry”. Ph.D. thesis, Technische Universiteit Delft.
  • Karanam, V., S. Garg, M. Motagh, and K. Jain. 2021. “The Risk of Coal Fires and Land Subsidence in Jharia Coalfields, India, Analysed Using Remote Sensing Techniques.” EGU General Assembly 2021, Online EGU21–14419. https://doi.org/10.5194/egusphere-egu21-14419. 19-30 Apr 2021.
  • Li, F., H. Gong, B. Chen, C. Zhou, and L. Guo. 2020. “Analysis of the Contribution Rate of the Influencing Factors to Land Subsidence in the Eastern Beijing Plain, China Based on Extremely Randomized Trees (ERT) Method.” Remote Sensing 12 (18): 2963. https://doi.org/10.3390/rs12182963.
  • Li, Y., H. Gong, L. Zhu, and X. Li. 2017. “Measuring Spatiotemporal Features of Land Subsidence, Groundwater Drawdown, and Compressible Layer Thickness in Beijing Plain, China.” Water 9:64–64. https://doi.org/10.3390/w9010064.
  • Liu, Y., H. Fan, L. Wang, and H. Zhuang. 2021. “Monitoring of Surface Deformation in a Low Coherence Area Using Distributed Scatterers InSar: Case Study in the Xiaolangdi Basin of the Yellow River, China.” Bulletin of Engineering Geology and the Environment 80 (1): 25–39. https://doi.org/10.1007/s10064-020-01929-1.
  • Lu, C., and C. Chang. 2014. “A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression.” Scientific World Journal 1–8. https://doi.org/10.1155/2014/624017.
  • Lyu, M., Y. Ke, L. Guo, X. Li, L. Zhu, H. Gong, and C. Constantinos. 2020. “Change in Regional Land Subsidence in Beijing After South-To-North Water Diversion Project Observed Using Satellite Radar Interferometry.” GIScience & Remote Sensing 57 (1): 140–156. https://doi.org/10.1080/15481603.2019.1676973.
  • Lyu, M., Y. Ke, X. Li, L. Zhu, L. Guo, and H. Gong. 2020. “Detection of Seasonal Deformation of Highway Overpasses Using the PS-Insar Technique: A Case Study in Beijing Urban Area.” Remote Sensing 12 (18): 3071. https://doi.org/10.3390/rs12183071.
  • Ng, A. H., L. Ge, X. Li, and K. Zhang. 2012. “Monitoring Ground Deformation in Beijing, China with Persistent Scatterer SAR Interferometry.” Journal of Geodesy 86 (6): 375–392. https://doi.org/10.1007/s00190-011-0525-4.
  • Park, S. W., and S. H. Hong. 2021. “Nonlinear Modeling of Subsidence from a Decade of InSar Time Series.” Geophysical Research Letters 48 (3): e2020GL090970. https://doi.org/10.1029/2020GL090970.
  • Qin, H., C. B. Andrews, F. Tian, G. Cao, Y. Luo, J. Liu, and C. Zheng. 2018. “Groundwater-Pumping Optimization for Land-Subsidence Control in Beijing Plain, China.” Hydrogeology Journal 26 (4): 1061–1081. https://doi.org/10.1007/s10040-017-1712-z.
  • Rahmati, O., A. Golkarian, T. Biggs, S. Keesstra, F. Mohammadi, and I. N. Daliakopoulos. 2019. “Land Subsidence Hazard Modeling: Machine Learning to Identify Predictors and the Role of Human Activities.” Journal of Environmental Management 236:466–480. https://doi.org/10.1016/j.jenvman.2019.02.020.
  • Shen, H., X. Li, Q. Cheng, C. Zeng, G. Yang, H. Li, and L. Zhang. 2015. “Missing Information Reconstruction of Remote Sensing Data: A Technical Review.” IEEE Transactions on Geoscience and Remote Sensing 3 (3): 61–85. https://doi.org/10.1109/MGRS.2015.2441912.
  • Shi, L., H. Gong, B. Chen, and C. Zhou. 2020. “Land Subsidence Prediction Induced by Multiple Factors Using Machine Learning Method.” Remote Sensing 12 (24): 4044. https://doi.org/10.3390/rs12244044.
  • Shi, M., H. Gong, M. Gao, B. Chen, S. Zhang, and C. Zhou. 2020. “Recent Ground Subsidence in the North China Plain, China, Revealed by Sentinel-1A Datasets.” Remote Sensing 12 (21): 3579. https://doi.org/10.3390/rs12213579.
  • Wang J, Deng Y, Xu N, Yang T, Yan X, Wang H, Huang X, Liu X and Pei X. 2020. “Numerical simulation of land subsidence caused by subway train vibration using PFC.“ Proceedings of the International Association of Hydrological Sciences 382:559–564. https://doi.org/10.5194/piahs-382-559-2020.
  • Xu, S., X. An, X. Qiao, L. Zhu, and L. Li. 2013. “Multi-Output Least-Squares Support Vector Regression Machines.” Pattern Recognition Letters 34 (9): 1078–1084. https://doi.org/10.1016/j.patrec.2013.01.015.
  • Xu, D., Y. Shi, I. W. Tsang, Y. Ong, C. Gong, and X. Shen 2019. “Survey on Multi-Output Learning.” IEEE Transactions on Neural Networks and Learning Systems, 1–21. https://doi.org/10.1109/TNNLS.2019.2945133.
  • Yang, Q., Y. Ke, D. Zhang, B. Chen, H. Gong, M. Lv, L. Zhu, and X. Li 2018. “Multi-Scale Analysis of the Relationship Between Land Subsidence and Buildings: A Case Study in an Eastern Beijing Urban Area Using the PS-Insar Technique.” Remote Sensing, 10(7), 1006. https://doi.org/10.3390/rs10071006.
  • Yasrebi, J., M. Saffari, H. Fathi, N. Karimian, and R. Gazni. 2009. “Evaluation and Comparison of Ordinary Kriging and Inverse Distance Weighting Methods for Prediction of Spatial Variability of Some Soil Chemical Parameters.” Research Journal of Biological Sciences 4:93–102. https://doi.org/10.5556/j.tkjm.42.2011.385-394.
  • Zha, Y., J. Gao, and S. Ni. 2003. “Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery.” International Journal of Remote Sensing 24 (3): 583–594. https://doi.org/10.1080/01431160304987.
  • Zhang, Y., H. Gong, Z. Gu, R. Wang, X. Li, and W. Zhao. 2014. “Characterization of Land Subsidence Induced by Groundwater Withdrawals in the Plain of Beijing City, China.” Hydrogeology Journal 22:397–409. https://doi.org/10.1007/s10040-013-1069-x.
  • Zhou, C., H. Gong, B. Chen, X. Li, J. Li, X. Wang, M. Gao, et al. 2019. “Quantifying the Contribution of Multiple Factors to Land Subsidence in the Beijing Plain, China with Machine Learning Technology.” Geomorphology 335:48–61. https://doi.org/10.1016/j.geomorph.2019.03.017.
  • Zhu, L., H. Gong, X. Li, R. Wang, B. Chen, Z. Dai, and P. Teatini. 2015. “Land Subsidence Due to Groundwater Withdrawal in the Northern Beijing Plain, China.” Engineering Geology 193:243–255. https://doi.org/10.1016/j.enggeo.2015.04.020.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.