First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry

Zhang, Jun; Qian, Rongyi; Ma, Zhenning; Lei, Xiaoqiong; Ling, Jianyu; Liu, Xu; Zhang, Guibin

doi:10.3390/rs17101686

Open AccessArticle

First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry

by

Jun Zhang

^1,2

,

Rongyi Qian

^1,2,3,*,

Zhenning Ma

^1,2,

Xiaoqiong Lei

⁴,

Jianyu Ling

^1,2,

Xu Liu

^1,2

and

Guibin Zhang

^1,2

¹

Key Laboratory of Intraplate Volcanoes and Earthquakes (China University of Geosciences, Beijing), Ministry of Education, Beijing 100083, China

²

School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China

³

School of Geological Engineering, Qinghai University, Xining 810016, China

⁴

National Institute of Nature Hazards, Ministry of Emergency Management of China, Beijing 100085, China

^*

Author to whom correspondence should be addressed.

Remote Sens. 2025, 17(10), 1686; https://doi.org/10.3390/rs17101686

Submission received: 24 March 2025 / Revised: 27 April 2025 / Accepted: 7 May 2025 / Published: 11 May 2025

(This article belongs to the Special Issue Advances in Remote Sensing and Geophysical Methods to the Earth’s Surface and Shallow Subsurface Characterization)

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Abstract

Preliminary tunnel surveys are essential for identifying geological hazards such as aquifers, faults, and karstic zones. While first-arrival tomography is effective for imaging shallow anomalies, traditional seismic sources face significant limitations in forested mountainous regions due to mobility, cost, and environmental impact. To address this, we deployed a seismic source delivered by an unmanned aerial vehicle (UAV) for a highway tunnel survey in Lijiang, China. The UAV system, paired with nodal geophones, enabled rapid, low-impact, and high-resolution data acquisition in rugged terrain. To enhance the weak far-offset refractions affected by near-surface attenuation, we applied supervirtual refraction interferometry (SVI), which significantly improved the signal-to-noise ratio and expanded the usable first-arrival dataset. The combined use of UAV excitation and SVI processing produced a high-precision P-wave velocity model through traveltime tomography, aligned well with borehole data. This model revealed the spatial distribution of weathered zones and bedrock interfaces, and allowed us to infer potential fracture zones. The results offer critical guidance for tunnel alignment and hazard mitigation in complex geological settings.

Keywords: UAV seismic source; first-arrival tomography; supervirtual interferometry; tunnel geological hazards; forested mountain geophysics

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MDPI and ACS Style

Zhang, J.; Qian, R.; Ma, Z.; Lei, X.; Ling, J.; Liu, X.; Zhang, G. First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry. Remote Sens. 2025, 17, 1686. https://doi.org/10.3390/rs17101686

AMA Style

Zhang J, Qian R, Ma Z, Lei X, Ling J, Liu X, Zhang G. First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry. Remote Sensing. 2025; 17(10):1686. https://doi.org/10.3390/rs17101686

Chicago/Turabian Style

Zhang, Jun, Rongyi Qian, Zhenning Ma, Xiaoqiong Lei, Jianyu Ling, Xu Liu, and Guibin Zhang. 2025. "First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry" Remote Sensing 17, no. 10: 1686. https://doi.org/10.3390/rs17101686

APA Style

Zhang, J., Qian, R., Ma, Z., Lei, X., Ling, J., Liu, X., & Zhang, G. (2025). First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry. Remote Sensing, 17(10), 1686. https://doi.org/10.3390/rs17101686

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First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry

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