{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T05:50:19Z","timestamp":1778392219189,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T00:00:00Z","timestamp":1605052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["61302157"],"award-info":[{"award-number":["61302157"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["61363075"],"award-info":[{"award-number":["61363075"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["51834006"],"award-info":[{"award-number":["51834006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National High Technology Research and Development Program (\u201c863\u201dProgram) of China","award":["2012AA12A308"],"award-info":[{"award-number":["2012AA12A308"]}]},{"name":"Yue Qi Young Scholars Program of China University of Mining &amp; Technology, Beijing","award":["800015Z1117"],"award-info":[{"award-number":["800015Z1117"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The identification of underground geohazards is always a difficult issue in the field of underground public safety. This study proposes an interactive visualization framework for underground geohazard recognition on urban roads, which constructs a whole recognition workflow by incorporating data collection, preprocessing, modeling, rendering and analyzing. In this framework, two proposed sampling point selection methods have been adopted to enhance the interpolated accuracy for the Kriging algorithm based on ground penetrating radar (GPR) technology. An improved Kriging algorithm was put forward, which applies a particle swarm optimization (PSO) algorithm to optimize the Kriging parameters and adopts in parallel the Compute Unified Device Architecture (CUDA) to run the PSO algorithm on the GPU side in order to raise the interpolated efficiency. Furthermore, a layer-constrained triangulated irregular network algorithm was proposed to construct the 3D geohazard bodies and the space geometry method was used to compute their volume information. The study also presents an implementation system to demonstrate the application of the framework and its related algorithms. This system makes a significant contribution to the demonstration and understanding of underground geohazard recognition in a three-dimensional environment.<\/jats:p>","DOI":"10.3390\/ijgi9110668","type":"journal-article","created":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T19:08:28Z","timestamp":1605121708000},"page":"668","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Three-Dimensional Visualization Framework for Underground Geohazard Recognition on Urban Road-Facing GPR Data"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8620-4623","authenticated-orcid":false,"given":"Zhenwu","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benting","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Software and IoT Engineering, Jiangxi University of Finance &amp;Economics, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4212-8582","authenticated-orcid":false,"given":"Mengjie","family":"Han","sequence":"additional","affiliation":[{"name":"School of Technology and Business Studies, Dalarna University, 79188 Falun, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hadimlioglu, I.A., King, S.A., and Starek, M.J. (2020). FloodSim: Flood Simulation and Visualization Framework Using Position-Based Fluids. ISPRS Int. J. Geo. Inf., 9.","DOI":"10.3390\/ijgi9030163"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wielebski, \u0141., Medy\u0144ska-Gulij, B., \u0141ukasz, H., and Dickmann, F. (2020). Time, Spatial, and Descriptive Features of Pedestrian Tracks on Set of Visualizations. ISPRS Int. J. Geo. Inf., 9.","DOI":"10.3390\/ijgi9060348"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"456","DOI":"10.3390\/ijgi2020456","article-title":"Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization","volume":"2","author":"Dalyot","year":"2013","journal-title":"ISPRS Int. J. Geo. Inf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"408","DOI":"10.3390\/ijgi3020408","article-title":"The Application of WebGIS Tools for Visualizing Coastal Flooding Vulnerability and Planning for Resiliency: The New Jersey Experience","volume":"3","author":"Lathrop","year":"2014","journal-title":"ISPRS Int. J. Geo. Inf."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Wang, W., Hu, C., Chen, N., Xiao, C., and Jia, S. (2016). Spatio-Temporal Risk Assessment Process Modeling for Urban Hazard Events in Sensor Web Environment. ISPRS Int. J. Geo. Inf., 5.","DOI":"10.3390\/ijgi5110203"},{"key":"ref_6","first-page":"130","article-title":"Analysis of Reasons for Urban Road Collapse and Prevention and Control Countermeasures in Recent Decade of China","volume":"61","author":"Hu","year":"2016","journal-title":"Highway"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"489","DOI":"10.9711\/KTAJ.2017.19.3.489","article-title":"Determination of priorities for management to reduce collapse accident of open excavation and road sink in urban areas","volume":"19","author":"Seong","year":"2017","journal-title":"J. Korean Tunn. Undergr. Space Assoc."},{"key":"ref_8","first-page":"789","article-title":"Application of 3D GIS in urban underground space planning","volume":"31","author":"Cong","year":"2009","journal-title":"Chin. J. Geotech. Eng."},{"key":"ref_9","first-page":"105","article-title":"Ground-penetrating radar investigations for urban roads","volume":"159","author":"Evans","year":"2006","journal-title":"Proc. Inst. Civ. Eng. Munic. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"84","DOI":"10.2136\/vzj2009.0188","article-title":"Visualizing Unsaturated Flow Phenomena Using High-Resolution Reflection Ground Penetrating Radar","volume":"10","author":"Haarder","year":"2011","journal-title":"Vadose Zone J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"397","DOI":"10.3997\/1873-0604.2010028","article-title":"Definition of buried archaeological remains with a new 3D visualization technique of a ground-penetrating radar data set in Temple Augustus in Ankara, Turkey","volume":"8","author":"Kadioglu","year":"2010","journal-title":"Near Surf. Geophys."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"183","DOI":"10.3997\/1873-0604.2016010","article-title":"Visualization of buried anti-tank landmines and soil pollution: Analyses using ground penetrating radar method with attributes and petrographical methods","volume":"14","author":"Kadioglu","year":"2016","journal-title":"Near Surf. Geophys."},{"key":"ref_13","first-page":"946","article-title":"Ground-penetrating radar attribute analysis for visualization of subsurface archaeological structures","volume":"31","author":"Khwanmuang","year":"2012","journal-title":"Geophysicists"},{"key":"ref_14","first-page":"277","article-title":"Research on 3d visualization of underground pipeline","volume":"28","author":"Li","year":"2003","journal-title":"Editor. Board Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1061\/(ASCE)0887-3801(2009)23:6(348)","article-title":"Modeling and Visualization of Underground Structures","volume":"23","author":"Li","year":"2009","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1002\/ppp.594","article-title":"Application of ground-penetrating radar imagery for three-dimensional visualization of near-surface structures in ice-rich permafrost, Barrow, Alaska","volume":"18","author":"Munroe","year":"2007","journal-title":"Permafr. Periglac. Process."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1016\/j.conbuildmat.2012.05.026","article-title":"Condition assessment of concrete structures using a new analysis method: Ground-penetrating radar computer-assisted visual interpretation","volume":"38","author":"Tarussov","year":"2013","journal-title":"Constr. Build. Mater."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.autcon.2014.05.004","article-title":"A semi-automatic processing and visualization tool for ground-penetrating radar pavement thickness data","volume":"45","author":"Solla","year":"2014","journal-title":"Autom. Constr."},{"key":"ref_19","first-page":"1332","article-title":"Subterranean pipeline real-time design in three dimensional system","volume":"36","author":"Wang","year":"2008","journal-title":"J. Tongji Univ."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wen, F., Wen, L., Juan, Y., Yang, P., and Yu, T. (2019, January 12\u201314). 3D visualization of urban underground pipelines by using SuperMap. Proceedings of the 5th International Conference on Energy Materials and Environment Engineering, Kuala Lumpur, Malaysia.","DOI":"10.1088\/1757-899X\/569\/3\/032001"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1007\/s12145-019-00394-z","article-title":"3D geological modeling and visualization of above-ground and underground integration taking the Unicorn Island in Tianfu new area as an example","volume":"12","author":"Hao","year":"2019","journal-title":"Earth Sci. Inform."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s12145-018-0350-x","article-title":"A virtual globe-based integration and visualization framework for aboveground and underground 3D spatial objects","volume":"11","author":"Chen","year":"2018","journal-title":"Earth Sci. Inform."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.ndteint.2018.11.015","article-title":"Automated visualization of concrete bridge deck condition from GPR data","volume":"102","author":"Dinh","year":"2019","journal-title":"NDT E Int."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"5666","DOI":"10.1109\/TGRS.2020.2968208","article-title":"3-D Multistatic Ground Penetrating Radar Imaging for Augmented Reality Visualization","volume":"58","author":"Pereira","year":"2020","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1542","DOI":"10.1016\/j.mejo.2014.09.004","article-title":"The development of a multi-channel GPR system for roadbed damage detection","volume":"45","author":"Xu","year":"2014","journal-title":"Microelectron. J."},{"key":"ref_26","first-page":"709","article-title":"Multi-distance measures weighted Kriging method for deformation stability analysis of steep slopes","volume":"40","author":"Liu","year":"2009","journal-title":"J. Hydraul. Eng."},{"key":"ref_27","first-page":"2881","article-title":"A combined indicator-ordinary Kriging method for estimating thicknesses of discontinuous geological strata","volume":"35","author":"Li","year":"2014","journal-title":"Rock Soil Mech."},{"key":"ref_28","first-page":"343","article-title":"Bayesian Collocated CoKriging","volume":"14","author":"Niu","year":"2002","journal-title":"J. Comput. Aided Des. Comput. Graph."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/j.solener.2018.06.105","article-title":"Spatial prediction using kriging ensemble","volume":"171","author":"Yang","year":"2018","journal-title":"Sol. Energy"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.scitotenv.2020.137290","article-title":"Empirical Bayesian kriging implementation and usage","volume":"722","author":"Gribov","year":"2020","journal-title":"Sci. Total. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1155\/2014\/573694","article-title":"Optimization of Spot-Welded Joints Combined Artificial Bee Colony Algorithm with Sequential Kriging Optimization","volume":"6","author":"Fang","year":"2015","journal-title":"Adv. Mech. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1108\/AEAT-06-2018-0157","article-title":"A novel improvement of Kriging surrogate model","volume":"91","author":"He","year":"2019","journal-title":"Aircr. Eng. Aerosp. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.mechmachtheory.2013.06.003","article-title":"Global optimization of reliability design for large ball mill gear transmission based on the Kriging model and genetic algorithm","volume":"69","author":"Zhang","year":"2013","journal-title":"Mech. Mach. Theory"},{"key":"ref_34","first-page":"567","article-title":"Kriging Interpolation Method Optimized by Support Vector Machine and Its Application in Oceanic Data","volume":"34","author":"Wang","year":"2011","journal-title":"Trans. Atmos. Sci."},{"key":"ref_35","first-page":"303","article-title":"Reconstruction of three-dimensional temperature field based on least-square method and Kriging interpolation","volume":"36","author":"Yan","year":"2014","journal-title":"J. Shenyang Univ. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/s00366-018-0590-x","article-title":"Gradient-enhanced kriging for high-dimensional problems","volume":"35","author":"Bouhlel","year":"2018","journal-title":"Eng. Comput."},{"key":"ref_37","first-page":"784","article-title":"Sampling data selection algorithm for Kriging method based on ground penetrating radar data","volume":"38","author":"Wang","year":"2017","journal-title":"J. Harbin Eng. Univ."},{"key":"ref_38","first-page":"642","article-title":"Property, classification and key technologies of three-dimensional geological data visualization","volume":"30","author":"Wu","year":"2011","journal-title":"Geol. Bull. China"},{"key":"ref_39","first-page":"54","article-title":"Research of three-dimensional geological modeling and visualization method","volume":"34","author":"Wu","year":"2014","journal-title":"Sci. China Ser. D Earth Sci."},{"key":"ref_40","first-page":"26","article-title":"Comparing Research on 3 D Modeling Technology & Its Implement Methods","volume":"32","author":"Bi","year":"2010","journal-title":"J. Wuhan Univ. Technol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2004","DOI":"10.3724\/SP.J.1001.2008.02004","article-title":"Construction Method and Actualizing Techniques of 3D Visual Model for Geological Faults","volume":"19","author":"Zhu","year":"2008","journal-title":"J. Softw."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Liu, H., and Wu, C. (2019). Developing a Scene-Based Triangulated Irregular Network (TIN) Technique for Individual Tree Crown Reconstruction with LiDAR Data. Forests, 11.","DOI":"10.3390\/f11010028"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1166\/sl.2014.3104","article-title":"High Accuracy Regular Grid Digital Elevation Model Modeling Based on 3D Triangulated Irregular Network Using Total Station Measured Points","volume":"12","author":"Chen","year":"2014","journal-title":"Sens. Lett."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"11051","DOI":"10.1007\/s11042-016-3465-4","article-title":"Filtering LiDAR data based on adjacent triangle of triangulated irregular network","volume":"76","author":"Quan","year":"2016","journal-title":"Multimed. Tools Appl."},{"key":"ref_45","unstructured":"Longtin, M.J. (2014, January 8\u201312). Efficient representation of dense elevation grids via triangulated irregular networks. Proceedings of the Fall Simulation Interoperability Workshop, Orlando, FL, USA."},{"key":"ref_46","first-page":"1493","article-title":"Three-dimensional morphological analysis method for geological interfaces based on tin and its application","volume":"44","author":"Mao","year":"2013","journal-title":"J. Cent. South Univ."},{"key":"ref_47","first-page":"345","article-title":"Optimized method of building underwater terrain navigation database based on triangular irregular network","volume":"23","author":"Wang","year":"2015","journal-title":"J. Chin. Inert. Technol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1228002","DOI":"10.3788\/AOS201434.1228002","article-title":"A Novel Algorithm Based on Triangulated Irregular Network for Edge Detection from LiDAR Data","volume":"34","author":"Xuan","year":"2014","journal-title":"Acta Opt. Sin."},{"key":"ref_49","first-page":"146","article-title":"Layer-Constrained Triangulated Irregular Network Algorithm Based on Ground Penetrating Radar Data and Its Application","volume":"27","author":"Wang","year":"2018","journal-title":"J. Beijing Inst. Technol."},{"key":"ref_50","first-page":"24","article-title":"Effects of the factors for spatial correlation analysis on Kriging estimation in reservoir modeling","volume":"28","author":"Liu","year":"2004","journal-title":"J. Univ. Pet. China Nat. Sci. Ed."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/S1006-1266(07)60090-X","article-title":"Application of Log Kriging on Estimated Reserves of the 10-9 Ore Body of Lutangba in the Gejiu Tin Deposits","volume":"17","author":"Deng","year":"2007","journal-title":"J. China Univ. Min. Technol."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Reyment, R.A., and Davis, J.C. (1988). Statistics and Data Analysis in Geology, Wiley.","DOI":"10.2307\/2531613"},{"key":"ref_53","unstructured":"Kennedy, J., and Eberhart, R.C. (December, January 27). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Network, Perth, Australia."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/11\/668\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:32:10Z","timestamp":1760178730000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/11\/668"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,11]]},"references-count":53,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["ijgi9110668"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9110668","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,11]]}}}