Monitoring and Prediction of Railway Deformation based on DInSAR and Probability Integral Method

doi:10.13474/j.cnki.11-2246.2017.0023

测绘通报 ›› 2017, Vol. 0 ›› Issue (1): 106-111.doi: 10.13474/j.cnki.11-2246.2017.0023

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Monitoring and Prediction of Railway Deformation based on DInSAR and Probability Integral Method

ZHENG Meinan¹, LIU Yixuan^2,3, DENG Kazhong¹, ZHAO Chenliang⁴, FENG Jun⁵

1. School of Environmental Science and Spatial Informatics, China University of Mining & Technology, Xuzhou 221116, China;
2. Jiangsu Province Hydrology and Water Resources Investigation Bureau, Xuzhou 221006, China;
3. School of Resources and Geosciences, China University of Mining & Technology, Xuzhou 221116, China;
4. Dept. of Remote Sensing and Surveying and Mapping of the Third Surveying and Design Institute Ltd. Co., Tianjin 300000, China;
5. Shanxi Coal Geological Prospecting Institute 115, Datong 037000, China

Received:2016-06-14 Revised:2016-11-01 Online:2017-01-25 Published:2017-02-06

Abstract

Abstract: In order to obtain real-time dynamic deformation and deformation trend of railway above goaf,a method based on the combination of the Differential SAR Interferometry (DInSAR) technique and probability integral method was presented in this paper. Firstly,the DInSAR technology was used to monitor the goaf,and the monitor results were compared with leveling data.Then,the probability integral method parameters were calculated using DInSAR monitoring results, and modified the prediction parameters into sufficiency mining condition.Finally, the deformation of the railway was predicted using the modified parameters. The results verified the combination of both can effectively monitor and predict railways and other linear structures.

Key words: DInSAR, deformation monitor, probability integral method, goaf

CLC Number:

P237

ZHENG Meinan, LIU Yixuan, DENG Kazhong, ZHAO Chenliang, FENG Jun. Monitoring and Prediction of Railway Deformation based on DInSAR and Probability Integral Method[J]. 测绘通报, 2017, 0(1): 106-111.

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Monitoring and Prediction of Railway Deformation based on DInSAR and Probability Integral Method

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