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Open AccessArticle

An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network during the Past 15 Years

by 1,2,3, 1,2,3,*, 1,2,3, 1,2,3, 4, 1,2, 1,2,3, 1,2,3 and 1,2,3
1
Key Laboratory of the Ministry of Education Land Subsidence Mechanism and Prevention, Capital Normal University, Beijing 100048, China
2
College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
3
Observation and Research Station of Groundwater and Land Subsidence in Beijing-Tianjin-Hebei Plain, MNR, Beijing 100048, China
4
Beijing Institute of Hydrogeology and Engineering Geology, Beijing 100195, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(13), 2125; https://doi.org/10.3390/rs12132125
Received: 19 May 2020 / Revised: 30 June 2020 / Accepted: 30 June 2020 / Published: 2 July 2020
Land subsidence threatens the stable operation of urban rail transit, including subways. Obtaining deformation information during the entire life-cycle of a subway becomes a necessary means to guarantee urban safety. Restricted by sensor life and cost, the single-sensor Multi-temporal Interferometric Synthetic Aperture Radar (MTI) technology has been unable to meet the needs of long-term sequence, high-resolution deformation monitoring, especially of linear objects. The multi-sensor MTI time-series fusion (MMTI-TSF) techniques has been proposed to solve this problem, but rarely mentioned. In this paper, an improved MMTI-TSF is systematically explained and its limitations are discussed. Taking the Beijing Subway Network (BSN) as a case study, through cross-validation and timing verification, we find that the improved MMTI-TSF results have higher accuracy (R2 of 98% and, Root Mean Squared Error (RMSE) of 4mm), and compared with 38 leveling points, the fitting effect of the time series is good. We analyzed the characteristics of deformation along the BSN over a 15-year periods. The results suggest that there is a higher risk of instability in the eastern section of Beijing Subway Line 6 (L6). The land subsidence characteristics along the subway lines are related to its position from the subsidence center, and the edge of the subsidence center presents a segmented feature. View Full-Text
Keywords: MTI; land subsidence; multi-sensor; time-series fusion; beijing subway network; cross-validation MTI; land subsidence; multi-sensor; time-series fusion; beijing subway network; cross-validation
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MDPI and ACS Style

Duan, L.; Gong, H.; Chen, B.; Zhou, C.; Lei, K.; Gao, M.; Yu, H.; Cao, Q.; Cao, J. An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network during the Past 15 Years. Remote Sens. 2020, 12, 2125. https://doi.org/10.3390/rs12132125

AMA Style

Duan L, Gong H, Chen B, Zhou C, Lei K, Gao M, Yu H, Cao Q, Cao J. An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network during the Past 15 Years. Remote Sensing. 2020; 12(13):2125. https://doi.org/10.3390/rs12132125

Chicago/Turabian Style

Duan, Li; Gong, Huili; Chen, Beibei; Zhou, Chaofan; Lei, Kunchao; Gao, Mingliang; Yu, Hairuo; Cao, Qun; Cao, Jin. 2020. "An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network during the Past 15 Years" Remote Sens. 12, no. 13: 2125. https://doi.org/10.3390/rs12132125

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