24.1.9 Tunnels, Tunnel Descriptions, Tunnel Analysis

Chapter Contents (Back)
Tunnel Detection. Tunnel Analysis. SAR. Radar.

Perissin, D.[Daniele], Wang, Z.Y.[Zhi-Ying], Lin, H.[Hui],
Shanghai subway tunnels and highways monitoring through Cosmo-SkyMed Persistent Scatterers,
PandRS(73), No. 1, September 2012, pp. 58-67.
Elsevier DOI 1210
Persistent Scatterers; Urban subsidence monitoring; Subways; Highways; Shanghai BibRef

Kang, Z.Z.[Zhi-Zhong], Zhang, L.Q.[Li-Qiang], Tuo, L.[Lei], Wang, B.Q.[Bao-Qian], Chen, J.L.[Jin-Lei],
Continuous Extraction of Subway Tunnel Cross Sections Based on Terrestrial Point Clouds,
RS(6), No. 1, 2014, pp. 857-879.
DOI Link 1412

Kang, Z.Z.[Zhi-Zhong], Tuo, L.[Lei], Zlatanova, S.,
Continuously Deformation Monitoring of Subway Tunnel Based On Terrestrial Point Clouds,
DOI Link 1209

Stent, S.[Simon], Gherardi, R.[Riccardo], Stenger, B.[Björn], Soga, K.[Kenichi], Cipolla, R.[Roberto],
Visual change detection on tunnel linings,
MVA(27), No. 3, April 2016, pp. 319-330.
Springer DOI 1604
And: A1, A2, A3, A5, Only:
Precise deterministic change detection for smooth surfaces,
Cameras BibRef

Guan, K.[Ke], Ai, B.[Bo], Zhong, Z.D.[Zhang-Dui], Lopez, C.F., Zhang, L.[Lei], Briso-Rodriguez, C., Hrovat, A., Zhang, B.[Bei], He, R.[Ruisi], Tang, T.[Tao],
Measurements and Analysis of Large-Scale Fading Characteristics in Curved Subway Tunnels at 920 MHz, 2400 MHz, and 5705 MHz,
ITS(16), No. 5, October 2015, pp. 2393-2405.
UHF radio propagation BibRef

Attard, L.[Leanne], Debono, C.J.[Carl James], Valentino, G.[Gianluca], di Castro, M.[Mario],
Tunnel inspection using photogrammetric techniques and image processing: A review,
PandRS(144), 2018, pp. 180-188.
Elsevier DOI 1809
Tunnel inspection, Image processing, Photogrammetry BibRef

Li, Y.X.[Yong-Xue], Zhao, M.[Min], Sun, D.[Dihua],
Fast enhancement algorithm of highway tunnel image based on constraint of imaging model,
IET-IPR(12), No. 10, October 2018, pp. 1730-1735.
DOI Link 1809

Cao, Z.[Zhen], Chen, D.[Dong], Shi, Y.F.[Yu-Feng], Zhang, Z.X.[Zhen-Xin], Jin, F.X.[Feng-Xiang], Yun, T.[Ting], Xu, S.[Sheng], Kang, Z.Z.[Zhi-Zhong], Zhang, L.Q.[Li-Qiang],
A Flexible Architecture for Extracting Metro Tunnel Cross Sections from Terrestrial Laser Scanning Point Clouds,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902

Sun, H.[Haili], Xu, Z.G.[Zhen-Gwen], Yao, L.B.[Lian-Bi], Zhong, R.F.[Ruo-Fei], Du, L.M.[Li-Ming], Wu, H.B.[Hang-Bin],
Tunnel Monitoring and Measuring System Using Mobile Laser Scanning: Design and Deployment,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003

Chuang, T.Y.[Tzu-Yi], Sung, C.C.[Cheng-Che],
Learning and SLAM based Decision Support Platform for Sewer Inspection,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003

Qu, Z., Chen, S., Liu, Y., Liu, L.,
Linear Seam Elimination of Tunnel Crack Images Based on Statistical Specific Pixels Ratio and Adaptive Fragmented Segmentation,
ITS(21), No. 9, September 2020, pp. 3599-3607.
Image edge detection, Feature extraction, Acceleration, Surface cracks, Image segmentation, crack extraction BibRef

Xiong, L.J.[Lei-Jin], Zhang, D.L.[Ding-Li], Zhang, Y.[Yu],
Water leakage image recognition of shield tunnel via learning deep feature representation,
JVCIR(71), 2020, pp. 102708.
Elsevier DOI 2009
Shield tunnel, Water leakage, Deep learning, Image recognition BibRef

Qu, Z.[Zhong], Zhong, Y.L.[Yu-Lu], Liu, L.[Ling],
A method of lining seam elimination with angle adaptation and rectangular mark for road tunnel concrete lining images,
IET-IPR(15), No. 9, 2021, pp. 2056-2067.
DOI Link 2106

Singh, S.K.[Sarvesh Kumar], Banerjee, B.P.[Bikram Pratap], Raval, S.[Simit],
Three-Dimensional Unique-Identifier-Based Automated Georeferencing and Coregistration of Point Clouds in Underground Mines,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109

Jia, D.F.[Dong-Feng], Zhang, W.P.[Wei-Ping], Liu, Y.P.[Yan-Ping],
Systematic Approach for Tunnel Deformation Monitoring with Terrestrial Laser Scanning,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109

Liu, B.[Bin], Ren, Y.X.[Yu-Xiao], Liu, H.C.[Han-Chi], Xu, H.[Hui], Wang, Z.[Zhengfang], Cohn, A.G.[Anthony G.], Jiang, P.[Peng],
GPRInvNet: Deep Learning-Based Ground-Penetrating Radar Data Inversion for Tunnel Linings,
GeoRS(59), No. 10, October 2021, pp. 8305-8325.
Image reconstruction, Dielectrics, Data models, Permittivity, Feature extraction, Geometry, Deep learning, Deep neural networks, tunnel lining detection BibRef

Cao, Z.[Zhen], Chen, D.[Dong], Peethambaran, J.[Jiju], Zhang, Z.X.[Zhen-Xin], Xia, S.B.[Shao-Bo], Zhang, L.Q.[Li-Qiang],
Tunnel Reconstruction With Block Level Precision by Combining Data-Driven Segmentation and Model-Driven Assembly,
GeoRS(59), No. 10, October 2021, pp. 8853-8872.
Monitoring, Strain, Image segmentation, Deformable models, Solid modeling, Mathematical model, tunnel segmentation BibRef

Peng, M.[Ming], Wang, D.Y.[Deng-Yi], Liu, L.[Liu], Shi, Z.M.[Zhen-Ming], Shen, J.[Jian], Ma, F.[Fuan],
Recent Advances in the GPR Detection of Grouting Defects behind Shield Tunnel Segments,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112

Puntu, J.M.[Jordi Mahardika], Chang, P.Y.[Ping-Yu], Lin, D.J.[Ding-Jiun], Amania, H.H.[Haiyina Hasbia], Doyoro, Y.G.[Yonatan Garkebo],
A Comprehensive Evaluation for the Tunnel Conditions with Ground Penetrating Radar Measurements,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112

Bendris, B.[Bianca], Becerra, J.C.[Julián Cayero],
Design and Experimental Evaluation of an Aerial Solution for Visual Inspection of Tunnel-like Infrastructures,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201

Kim, J.R.[Jung-Rack], Lin, S.Y.[Shih-Yuan], Oh, J.W.[Jong-Woo],
The Survey of Lava Tube Distribution in Jeju Island by Multi-Source Data Fusion,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202

Kong, F.[Fanchao], Lu, D.[Dechun], Ma, Y.D.[Yi-Ding], Li, J.L.[Jian-Li], Tian, T.[Tao],
Analysis and Intelligent Prediction for Displacement of Stratum and Tunnel Lining by Shield Tunnel Excavation in Complex Geological Conditions: A Case Study,
ITS(23), No. 11, November 2022, pp. 22206-22216.
Excavation, Tunneling, Rocks, Strain, Soil, Predictive models, Torque, Complex stratum conditions, prediction of stratum displacement BibRef

Huang, Y.C.[Yu-Cheng], Liu, F.[Fang], Wang, J.[Jie], Zhang, S.[Sulong], Tang, Q.[Qiang],
A Photogrammetric System for Tunnel Underbreak and Overbreak Detection,
ITS(23), No. 11, November 2022, pp. 22217-22226.
Rocks, Excavation, Image recognition, Costs, Monitoring, Mathematical models, Labeling, Overbreak and underbreak, connected area labelling BibRef

Du, L.M.[Li-Ming], Zhong, R.F.[Ruo-Fei], Sun, H.[Haili], Pang, Y.[Yong], Mo, Y.[You],
Dislocation Detection of Shield Tunnel Based on Dense Cross-Sectional Point Clouds,
ITS(23), No. 11, November 2022, pp. 22227-22243.
Point cloud compression, Monitoring, Measurement by laser beam, Geophysical measurements, Data acquisition, longitudinal joint BibRef

Harseno, R.W.[Regidestyoko Wasistha], Lee, S.J.[Sung-Jin], Kee, S.H.[Seong-Hoon], Kim, S.[Sungmo],
Evaluation of Air-Cavities behind Concrete Tunnel Linings Using GPR Measurements,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212

Janiszewski, M.[Mateusz], Torkan, M.[Masoud], Uotinen, L.[Lauri], Rinne, M.[Mikael],
Rapid Photogrammetry with a 360-Degree Camera for Tunnel Mapping,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212

Li, J.C.[Jin-Cheng], Zhang, Z.X.[Zhen-Xin], Sun, H.[Haili], Xie, S.[Si], Zou, J.J.[Jian-Jun], Ji, C.Q.[Chang-Qi], Lu, Y.[Yue], Ren, X.X.[Xiao-Xu], Wang, L.[Liuzhao],
GL-Net: Semantic segmentation for point clouds of shield tunnel via global feature learning and local feature discriminative aggregation,
PandRS(199), 2023, pp. 335-349.
Elsevier DOI 2305
Semantic segmentation, Shield tunnel, Point clouds, Sample imbalance, Deep learning BibRef

Ragione, G.D.[Gianluigi Della], Rocca, A.[Alfredo], Perissin, D.[Daniele], Bilotta, E.[Emilio],
Volume Loss Assessment with MT-InSAR during Tunnel Construction in the City of Naples (Italy),
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306

Dabove, P.[Paolo], Colombero, C.[Chiara], Quaroni, A.S.[Andrea Salerno],
Towards the Monitoring of Underground Caves Using Geomatics and Geophysical Techniques: 3D Analyses and Seismic Response,
IJGI(12), No. 5, 2023, pp. xx-yy.
DOI Link 2306

Ye, J.M.[Jia-Ming], Che, D.[Defu], Ma, B.D.[Bao-Dong], Liu, Q.[Quan], Qiu, K.[Kehan], Shang, X.X.[Xiang-Xiang],
Construction Method for a Three-Dimensional Tunnel General Monomer Model Based on Parallel Pathfinding,
IJGI(12), No. 7, 2023, pp. xx-yy.
DOI Link 2308

Wang, B.X.[Bao-Xian], Dong, Z.H.[Zhi-Hao], Wang, Y.Z.[Yu-Zhao], Qin, S.[Shoupeng], Tan, Z.[Zhao], Zhao, W.G.[Wei-Gang], Ren, W.X.[Wei-Xin], Wang, J.[Junfang],
Visual Inspection Method for Subway Tunnel Cracks Based on Multi-Kernel Convolution Cascade Enhancement Learning,
IEICE(E106-D), No. 10, October 2023, pp. 1715-1722.
WWW Link. 2310

Wang, Z.[Zihan], Xu, X.Y.[Xiang-Yang], He, X.[Xuhui], Wei, X.J.[Xiao-Jun], Yang, H.[Hao],
A Method for Convergent Deformation Analysis of a Shield Tunnel Incorporating B-Spline Fitting and ICP Alignment,
RS(15), No. 21, 2023, pp. 5112.
DOI Link 2311

Rutkowski, W.[Wojciech], Lipecki, T.[Tomasz],
Use of the iPhone 13 Pro LiDAR Scanner for Inspection and Measurement in the Mineshaft Sinking Process,
RS(15), No. 21, 2023, pp. 5089.
DOI Link 2311

Kang, J.T.[Ji-Tong], Chen, N.[Ning], Li, M.[Mei], Mao, S.J.[Shan-Jun], Zhang, H.Y.[Hao-Yuan], Fan, Y.B.[Ying-Bo], Liu, H.[Hui],
A Point Cloud Segmentation Method for Dim and Cluttered Underground Tunnel Scenes Based on the Segment Anything Model,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401

Li, C.[Cheng], Pan, W.B.[Wen-Bo], Yuan, X.[Xiwen], Huang, W.Y.[Wen-Yu], Yuan, C.[Chao], Wang, Q.[Quandong], Wang, F.Y.[Fu-Yuan],
High-Precision Map Construction in Degraded Long Tunnel Environments of Urban Subways,
RS(16), No. 5, 2024, pp. 809.
DOI Link 2403

Chen, Q.[Qiong], Kang, Z.Z.[Zhi-Zhong], Cao, Z.[Zhen], Xie, X.W.[Xiao-Wei], Guan, B.[Bowen], Pan, Y.X.[Yu-Xi], Chang, J.[Jia],
Combining Cylindrical Voxel and Mask R-CNN for Automatic Detection of Water Leakages in Shield Tunnel Point Clouds,
RS(16), No. 5, 2024, pp. 896.
DOI Link 2403

Liang, C.[Ce], Zhu, J.[Jun], Zhang, J.[Jinbin], Zhu, Q.[Qing], Lu, J.Y.[Jing-Yi], Lai, J.B.[Jian-Bo], Wu, J.L.[Jian-Lin],
A Knowledge-Guided Intelligent Analysis Method of Geographic Digital Twin Models: A Case Study on the Diagnosis of Geometric Deformation in Tunnel Excavation Profiles,
IJGI(13), No. 3, 2024, pp. 78.
DOI Link 2404

Zhou, Y., Dong, Z., Tong, P., Yang, B.,
Evaluation of Tunnel Excavation Combining Terrestrial Laser Scanning Point Clouds and Design Models,
ISPRS21(B2-2021: 271-276).
DOI Link 2201

Qu, J., Zhong, L.,
Research on Rapid Identification of Water Ponding in Tunnels Based on Multi-frame Fusion and Improved SSD Algorithm,
edge detection, feature extraction, image enhancement, image fusion, image reconstruction, image resolution, inspection, Improved SSD algorithm BibRef

Panella, F., Roecklinger, N., Vojnovic, L., Loo, Y., Boehm, J.,
Cost-benefit Analysis of Rail Tunnel Inspection for Photogrammetry And Laser Scanning,
DOI Link 2012

Meng, Y., Wu, H., Niu, B.,
A Method to Improve the Lining Images Quality in Complex Tunnel Scenes,
Histograms, Image segmentation, Adaptive equalizers, Image quality, Image edge detection, tunnel detection, image high frequency suppression BibRef

Foucher, P., Charbonnier, P., Noël, T., Fosse, Y., Hébert, J.F.,
Scanning Tunnels With Two Very High-resolution Laser Devices and A Stacker,
DOI Link 1912

Doulamis, A., Doulamis, N., Protopapadakis, E., Voulodimos, A.,
Combined Convolutional Neural Networks and Fuzzy Spectral Clustering for Real Time Crack Detection in Tunnels,
Inspection, Feature extraction, Convolutional neural networks, Manipulators, Real-time systems, tunnel inspection BibRef

Kunzel, J., Werner, T., Eisert, P., Waschnewski, J.,
Automatic Analysis of Sewer Pipes Based on Unrolled Monocular Fisheye Images,
cameras, feature extraction, image classification, inspection, mechanical engineering computing, neural nets, pipes, BibRef

Moisan, E., Heinkele, C., Charbonnier, P., Foucher, P., Grussenmeyer, P., Guillemin, S., Koehl, M.,
Dynamic 3D Modeling of A Canal-tunnel Using Photogrammetric And Bathymetric Data,
DOI Link 1805

Li, Y.R.[Yong-Rong], Feng, Q.[Qiang], Zhang, N.[Ning], Tian, H.[Hui], Yang, Y.[Ying], Jin, J.J.[Jun-Jie], Li, Y.[Ying], Zhang, L.Y.[Li-Yun],
A New Application of Photogrammetry in the Underground Pipe Network Survey,
ISPRS16(B5: 871-874).
DOI Link 1610

Liu, C.[Chun], Li, Z.N.[Zheng-Ning], Zhou, Y.[Yuan],
Robust Parallel Motion Estimation And Mapping With Stereo Cameras In Underground Infrastructure,
ISPRS16(B1: 675-679).
DOI Link 1610

Chapman, M.A.[Michael A.], Min, C.[Cao], Zhang, D.[Deijin],
Continuous Mapping Of Tunnel Walls In A Gnss-denied Environment,
ISPRS16(B3: 481-485).
DOI Link 1610

Zhu, N.N.[Ning-Ning], Jiaa, Y.H.[Yong-Hong], Luo, L.[Lun],
Tunnel Point Cloud Filtering Method Based On Elliptic Cylindrical Model,
ISPRS16(B1: 735-740).
DOI Link 1610

Protopapadakis, E.[Eftychios], Doulamis, N.[Nikolaos],
Image Based Approaches for Tunnels' Defects Recognition via Robotic Inspectors,
ISVC15(I: 706-716).
Springer DOI 1601

Moisan, E., Charbonnier, P., Foucher, P., Grussenmeyer, P., Guillemin, S., Koehl, M.,
Building a 3D Reference Model for Canal Tunnel Surveying Using Sonar and Laser Scanning,
DOI Link 1508

Albert, J.L., Charbonnier, P., Chavant, P., Foucher, P., Muzet, V., Prybyla, D., Perrin, T., Grussenmeyer, P., Guillemin, S., Koehl, M.,
Devising a Visual Inspection System for Canal Tunnels: Preliminary Studies,
DOI Link 1311

Charbonnier, P., Chavant, P., Foucher, P., Muzet, V., Prybyla, D., Perrin, T., Grussenmeyer, P., Guillemin, S.,
Accuracy Assessment of a Canal-Tunnel 3D Model by Comparing Photogrammetry and Laserscanning Recording Techniques,
DOI Link 1311

Clini, P., Nespeca, R., Bernetti, A.,
All-in-One Laser Scanning Methods for Surveying, Representing and Sharing Information on Archaeology. via Flaminia and the Furlo Tunnel Complex,
DOI Link 1311

Zhang, C., Arditi, D., Chen, Z.,
Documentation and Visualization of an As-Built Tunnel by Combining 3D Laser Scanning and Web Mapping,
DOI Link 1402

Li, J., Wan, Y., Gao, X.,
A New Approach for Subway Tunnel Deformation Monitoring: High-resolution Terrestrial Laser Scanning,
DOI Link 1209

Gonçalves, J.A., Mendes, R., Araújo, E., Oliveira, A., Boavida, J.,
Planar Projection of Mobile Laser Scanning Data In Tunnels,
DOI Link 1209

Roncella, R., Umili, G., Forlani, G.,
A Novel Image Acquisition and Processing Procedure for Fast Tunnel DSM Production,
DOI Link 1209

Chaiyasarn, K.[Krisada], Kim, T.K.[Tae-Kyun], Viola, F.[Fabio], Cipolla, R.[Roberto], Soga, K.[Kenichi],
Image mosaicing via quadric surface estimation with priors for tunnel inspection,

Seo, D.J.[Dong-Ju], Lee, J.C.[Jong Chool], Lee, Y.D.[Young-Do], Lee, Y.H.[Yong-Hee], Mun, D.Y.[Du-Yeoul],
Development of Cross Section Management System in Tunnel Using Terrestrial Laser Scanning Technique,
ISPRS08(B5: 573 ff).
PDF File. 0807

Qiu, D.W., Wu, J.G.,
Terrestrial Laser Scanning for the Deformation Monitoring of the Thermal Pipeline Traversed Subway Tunnel Engineering,
ISPRS08(B5: 491 ff).
PDF File. 0807

Zheng, J.Y.[Jiang Yu], Li, S.G.[Shi-Gang],
Employing a Fish-Eye for Scene Tunnel Scanning,
Springer DOI 0601

van Gosliga, R., Lindenbergh, R., Pfeifer, N.,
Deformation analysis of a bored tunnel by means of terrestrial laserscanning,
PDF File. 0609

Lindenbergh, R., Pfeifer, N., Rabbani, T.,
Accuracy analysis of the Leica HDS3000 and feasibility of tunnel deformation monitoring,
PDF File. 0509

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
General Urban Area Detection, Built-Up Area Detection .

Last update:Apr 18, 2024 at 11:38:49