Determination of Ground Subsidence by Sentinel-1 SAR Data (2018-2020) over Binh Duong Quarries, Vietnam
Main Article Content
Abstract
Mining-induced subsidence is often determined by field survey methods, e.g., using total station or global navigation satellite system (GNSS) technology. The advantage of these methods is high accuracy, but they are usually employed in a small-scale areas. Radar technology has been developed and applied to determine surface subsidence over a large area at a few millimeters accuracy. In this paper, 24 Sentinel-1B SAR images are used with the Permanent Scatter Interferometry (PSInSAR) method to determine the land subsidence of the Tan My-Thuong Tan quarries and surrounding areas in Binh Duong province, Vietnam. The results are compared with the average annual subsidence of 20 GNSS surveying points from January 2018 to March 2020. The correlation coefficient of annual average land subsidence of the two methods is bigger than 0.8, indicating the feasibility of applying the InSAR Sentinel-1 data processed by the PSInSAR method to determine the mining-induced subsidence of ground surfaces over quarries and surrounding areas.
Keywords:
GNSS, PSInSAR, radar time series, Sentinel-1, subsidence.
References
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I. Trisirisatayawong, InSAR Time-Series Analysis of Land Subsidence in Bangkok, Thailand, International Journal of Remote Sensing, Vol. 34, No. 8, 2013, pp. 2969-2982, https://doi.org/10. 1080/01431161.2012.756596.
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H. Andreas, K. Zhang, Mapping Land Subsidence in Jakarta, Indonesia Using Persistent Scatterer Interferometry (PSI) Technique with ALOS PALSAR, International Journal of Applied Earth Observation and Geoinformation, Vol. 1, No. 12, 2012, p. 232-242, https://doi.org/10.1016/j.jag. 2012.01.018.
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No. 12, pp. 1-16, 2016, https://doi.org/10.3390/s1612 2182.
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[7] E. Chaussard, S. Wdowinski, E. C. Cano,
F. Amelung, Land Subsidence in Central Mexico Detected by ALOS InSAR Time-Series, Remote Sensing of Environment, Vol. 140, 2014,
pp. 94-106, https://doi.org/10.1016/j.rse.2013.08.038.
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J. M. Nicolas, Time Series Analysis of Mexico City Subsidence Constrained by Radar Interferometry, Journal of Applied Geophysics, 2009, Vol. 69,
No. 1, pp. 1-15, https://doi.org/10.1016/j.jappgeo.2009. 02.006.
[13] G. Liu, X. Luo, Q. Chen, D. Huang, X. Ding, Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry, Sensors, Vol. 8, No. 8, 2008, pp. 4725-4741, https://doi.org/10. 3390/s8084725.
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A. Effendi, H.Z. Abidin, Land Subsidence Detection Using JERS-1 SAR Interferometry, The 22nd Asian Conference on Remote Sensing, 2001.
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[16] L. V. Trung, N. C. Tang, Assessment of Capacity of Using Sentinel-1 Images in Monitoring Land Subsidence in Ho Chi Minh City. Science & Technology Development Journal-Science of The Earth & Environment, Vol. 2, No. 2, 2018
pp. 19-25, https://doi.org/10.32508/stdjsee.v2i2.490.
[17] B. X. Nam, T. V. Anh, B. K. Luyen, N. Q. Long, L. T. T. Ha, G. Ropesh. Mining-Induced Land Subsidence Detection by Persistent Scatterer InSAR and Sentinel-1: Application to Phugiao Quarries, Vietnam. Lecture Notes in Civil Engineering Book Series, Vol. 108, 2021,
pp. 1, Springer, Cham, https://doi.org/10.1007/ 978-3-030-60269-72.
[18] A. Sowter, M. B. C. Amat, F. Cigna, S. Marsh,
A. Athab, L. Alshammari, Mexico City Land Subsidence in 2014-2015 with Sentinel-1 IW TOPS: Results Using The Intermittent SBAS (ISBAS) Technique. International Journal of Applied Earth Observation and Geoinformation, Vol. 52, 2016, pp. 230-242, https://doi.org/ 10.1016/j.jag. 2016.06.015.
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[20] J. Baek, S. W. Kim, H. J. Park, H. S. Jung,
K. D. Kim, J. W. Kim, Analysis of Ground Subsidence in Coal Mining Area Using SAR Interferometry, Geosciences Journal, Vol. 12.
No. 3, 2008, pp. 277-284, https://doi.org/10.1007/s12303-008-0028-3.
[21] J. He, G. Liu, H. Yue, Monitoring Ground Subsidence in Mining Area Using Spaceborne InSAR Technology, 2009 Joint Urban Remote Sensing Event, IEEE, 2009, pp. 1-6, https://doi.org/10. 1109/URS.2009.5137668.
[22] X. Diao, K. Wu, D. Hu, L. Li, D. Zhou, Combining Differential SAR Interferometry and The Probability Integral Method for Three-Dimensional Deformation Monitoring of Mining Areas. International Journal of Remote Sensing, Vol. 37, No. 21, 2016, pp. 5196-5212, https://doi.org/10.1080/01431161.20 16.1230284.
[23] C. Ma, X. Cheng, Y. Yang, X. Zhang, Z. Guo,
Y. Zou, Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of The Small Baseline Subset - Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China. Remote Sensing, Vol. 8, No. 11, 2016, pp. 951, https://doi.org/10.3390/ rs8110951.
[24] A. Hooper, K. Spaans, D. Bekaert, M. C. Cuenca, M. Arıkan, A. Oyen, StaMPS/MTI Manual, Delft Institute of Earth Observation and Space Systems Delft University of Technology, Kluyverweg,
Vol. 1, 2010, pp 1-17.
[25] D. Blasco, M. Foumelis, C. Stewart,
A. Hooper, Measuring Urban Subsidence in The Rome Metropolitan Area (Italy) with Sentinel-1 Snap-Stamps Persistent Scatterer Interferometry, Remote Sensing, 2019, Vol. 11, No. 2, pp. 129, https://doi.org/10.3390/rs11020129.