Monitoring of 3D large surface deformation in coal mines through the integration of synthetic aperture radar pixel offset tracking and probability integration function model

Monitoring of 3D large surface deformation in coal mines through the integration of synthetic aperture radar pixel offset tracking and probability integration function model

Bingqian ChenDa Jiang Jian Zhang Jian Gao Xueting Fan 

School of Geography, Geomatics and Urban-Rural Planning, Jiangsu Normal University, Xuzhou 221116, China

Hunan Province Key Laboratory of Coal Resources Clean-utilization and Mine Environment Protection, Xiangtan 411201, China

Henan Surveying and Mapping Engineering Institute, Zhengzhou 450046, China

Provincial Geomatics Centre of Jiangsu, Nanjing 210013, China

Corresponding Author Email: 
bqccumt@gmail.com
Page: 
507-519
|
DOI: 
https://doi.org/10.3166/I2M.17.507-519
Received: 
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Accepted: 
|
Published: 
30 September 2018
| Citation

OPEN ACCESS

Abstract: 

Considering the severity of surface deformation in coal mines and the limitation of the popular deformation monitoring technique interferometric synthetic aperture radar (InSAR), this paper attempts to measure the large deformation caused by coal mining and disclose the ground deformation law in an all-round way. For this purpose, the pixel offset tracking (POT) was integrated with the probability integration function model (PIFM) to track the 3D large deformation of the surface based on SAR image amplitude information. Firstly, the line of sight (LOS) deformation was acquired by the POT, while the vertical, east-west and south-north deformations were estimated by the PIFM based on the LOS deformation. After that, the proposed method was applied to monitor the surface deformation of Daliuta mine lot in China’s Shaanxi Province, and the results on 3D large deformation were compared against those obtained by the GPS station. It is found that the root means square error (RMSE) was 16.5 cm in the vertical direction, 12.2cm in the east-west horizontal direction, and 13.4m in the north-south horizontal direction, indicating the proposed method is accurate and reliable. The research findings shed new light on hazard monitoring in coal mines.

Keywords: 

interferometric synthetic aperture radar (InSAR), large deformation, deformation monitoring, pixel offset tracking (POT), probability integration function model (PIFM)

1. Introduction
2. Method
3. Experiment
4. Conclusions
Acknowledgment

This work was funded by the Natural Science Foundation of China (No. 41702375), the Basic Research Project of Jiangsu Province (Natural Science Foundation, No. BK20160218) and Hunan Province Key Laboratory Foundation of Coal Resources Clean-utilization and Mine Environment Protection (No. E21801). The authors would also like to thank the German Aerospace Centre for providing the images (TerraSAR-X Science Plan, No. LAN1425 and LAN1173) over the study area. This work was also funded by the Jiangsu Provincial Bureau of Surveying Mapping and Geoinformation Research Project under Grant No. JSCHKY201803.

  References

Abdikan S., Arikan M., Sanli F. B. (2014). Monitoring of coal mining subsidence in peri-urban area of Zonguldak city (NW Turkey) with persistent scatterer interferometry using ALOS-PALSAR. Environmental Earth Sciences, Vol. 71, No. 9, pp. 4081-4089. https://doi.org/10.1007/s12665-013-2793-1

Bateson L., Cigna F., Boon D., Sowter A. (2015). The application of the Intermittent SBAS (ISBAS) InSAR method to the South Wales Coalfield, UK. International Journal of Applied Earth Observation and Geoinformation, Vol. 34, No. 1, pp. 249-257. https://doi.org/10.1016/j.jag.2014.08.018

Chen B. Q., Deng K. Z., Fan H. D., Hao M. (2013). Monitoring large-scale deformation in mining area by D-InSAR and 3D laser scanning technology integration. International Journal of Mining Science and Technology, Vol. 23, No. 4, pp. 555-561. https://doi.org/10.1016/j.ijmst.2013.07.014

Fan H. D., Deng K. Z., Ju C. (2011). Land subsidence monitoring by D-InSAR technique. Mining Science and Technology (China), Vol. 21, No. 6, pp. 869-872. https://doi.org/10.1016/j.mstc.2011.05.030

Fan H. D., Gu W., Qin Y., Xue J. Q., Chen B. Q. (2014). A model for extracting large deformation mining subsidence using D-InSAR technique and probability integral method. Transactions of Nonferrous Metals Society of China, Vol. 24, No. 4, pp. 1242-1247. https://doi.org/10.1016/S1003-6326(14)63185-X

Fialko Y., Simons M., Agnew D. (2001). The complete (3‐D) surface displacement field in the epicentral area of the 1999 Mw7. 1 Hector Mine earthquake, California, from space geodetic observations. Geophysical Research Letters, Vol. 28, No. 16, pp. 3663-3066. https://doi.org/10.1029/2001GL013174

Fielding E. J., Lundgren P. R., Taymaz T., Yolsal‐Çevikbilen S., Owen S. E. (2013). Fault‐slip source models for the 2011 M 7.1 van earthquake in turkey from SAR interferometry, pixel offset tracking, GPS, and Seismic waveform analysis. Seismological Research Letters, Vol. 84, No. 4, pp. 579-593. https://doi.org/10.1785/0220120164

Greif V., Vlcko J. (2011). Monitoring of post-failure landslide deformation by the PS-InSAR technique at Lubietova in central Slovakia. Environmental Earth Sciences, Vol. 66, No. 6, pp. 1585-1595. https://doi.org/10.1007/s12665-011-0951-x

Huang J., Deng K., Fan H., Yan S. (2016). An improved pixel-tracking method for monitoring mining subsidence. Remote Sensing Letters, Vol. 7, No. 8, pp. 731-740. https://doi.org/10.1080/2150704X.2016.1183177

Li P. X., Tan Z. X., Yan L. L., Deng K. Z. (2011). Time series prediction of mining subsidence based on a SVM. Mining Science and Technology (China), Vol. 21, No. 4, pp. 557-567. https://doi.org/10.1016/j.mstc.2011.02.025

Li Z. W., Yang Z. F., Zhu J. J., Hu J., Wang Y. J., Li P. X., Chen G. L. (2015). Retrieving three-dimensional displacement fields of mining areas from a single InSAR pair. Journal of Geodesy, Vol. 89, No. 1, pp. 17-32. https://doi.org/10.1007/s00190-014-0757-1

Litwiniszyn J. (1974). Stochastic methods in mechanics of granular bodies. Stochastic Methods in Mechanics of Granular Bodies, pp. 5-9. https://doi.org/10.1007/978-3-7091-2836-7_1

Manconi A., Casu F., Ardizzone F., Bonano M., Cardinali M., Luca D. C., Gueguen E., Marchesini I., Parise M., Vennari C., Lanari R., Guzzetti F. (2014). Brief communication: Rapid mapping of landslide events: The 3 December 2013 Montescaglioso landslide, Italy. Nat Hazard Earth Sys., Vol. 14, No. 7, pp. 1835-1841. https://doi.org/10.5194/nhess-14-1835-2014

Massonnet D., Rossi M., Carmona C., Adragna F., Peltzer G., Feigl K., Rabaute T. (1993). The displacement field of the Landers earthquake mapped by radar interferometry. Nature, Vol. 364, No. 6433, pp. 138-142. https://doi.org/10.1038/364138a0

Song J. J., Han C. J., Li P., Zhang J. W., Liu D. Y., Jiang M. D., Zheng L., Zhang J. K., Song J. Y. (2012). Quantitative prediction of mining subsidence and its impact on the environment. International Journal of Mining Science and Technology, Vol. 22, No. 1, pp. 69-73. https://doi.org/10.1016/j.ijmst.2011.07.008

Strozzi T., Luckman A., Murray T., Wegmuller U., Werner C. L. (2002). Glacier motion estimation using SAR offset-tracking procedures. IEEE Trans Geosci Remote Sens, Vol. 40, No. 11, pp. 2384-2391. http://dx.doi.org/10.1109/TGRS.2002.805079

Wang J., Peng X. G., Xu C. H. (2011). Coal mining GPS subsidence monitoring technology and its application. Mining Science and Technology (China), Vol. 21, No. 4, pp. 463-467. https://doi.org/10.1016/j.mstc.2011.06.001

Wang X. F., Wang Y. J., Huang T. (2008). Extracting mining subsidence land from remote sensing images based on domain knowledge. Journal of China University of Mining and Technology, Vol. 18, No. 2, pp. 168-171. https://doi.org/10.1016/S1006-1266(08)60036-X

Yang C., Zhang Q., Zhao C. (2010). Monitoring mine collapse by D-InSAR. Mining Science and Technology, Vol. 20, No. 5, pp. 696-700. https://doi.org/10.1016/S1674-5264(09)60265-9

Zhao C., Lu Z., Zhang Q. (2013). Time-series deformation monitoring over mining regions with SAR intensity-based offset measurements. Remote Sensing Letters, Vol. 4, No. 5, pp. 436-445. https://doi.org/10.1080/2150704X.2012.746482

Zhao C., Lu Z., Zhang Q. (2014). Mining collapse monitoring with SAR imagery data: A case study of Datong mine, China. Journal of Applied Remote Sensing, Vol. 8, No. 1, pp. 083574-083574, 2014. https://doi.org/10.1117/1.JRS.8.083574