{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T18:55:34Z","timestamp":1765306534726,"version":"3.46.0"},"reference-count":51,"publisher":"Environmental and Engineering Geophysical Society","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Accurate location and depth determination of underground pipes, especially the attribute recognition, are of great importance yet remake a challenging issue in municipal environments. Single-trace phase difference analysis remains a bottleneck due to its inherent and strong randomness in object identification. This paper developed a multi-trace phase difference analysis framework for ground-penetrating radar (GPR) data based on K-means cluster analysis technique and the theory of region of interest (ROI), which could serve as a new criterion for successful pipe attribute recognition. After improving signal-to-noise ratio of GPR data by using the preprocessing techniques, the connected components algorithms (CCA) based on image segmentation and morphological operation is performed to delineate the ROI. The K-means cluster analysis technique is further employed to efficiently extract the multi-trace phase statistical features for comprehensively evaluating the attributes of ROI. We verify this proposed framework by simulated GPR signals, laboratory data and field datasets. Results demonstrate that the proposed method can not only facilitate the attribute recognition of pipes, but also reduce the interpretation ambiguity of the pipe material even in the field site environment. Specifically, if the phase difference of pipe turns out to be even multiples of \u03c0, the target can be automatically identified as metallic-category pipes, whereas odd multiples of \u03c0, point to non-metallic-category pipes with a lower permittivity than that of the background. This criterion presents promising applicability in subsurface pipeline identification and attributes recognition, especially in constructing a more appropriate initial model of GPR full waveform inversion for survey in pipes.<\/jats:p>","DOI":"10.32389\/jeeg20-030","type":"journal-article","created":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T10:10:06Z","timestamp":1625739006000},"page":"117-132","source":"Crossref","is-referenced-by-count":3,"title":["Attribute Recognition of Buried Pipes Based on Multi-Trace Phase Features Using K-means Clustering for GPR Data Interpretation"],"prefix":"10.32389","volume":"26","author":[{"given":"Deshan","family":"Feng","sequence":"first","affiliation":[{"name":"1 School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China,"},{"name":"2 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Changsha, 410083, China,"}]},{"given":"Xun","family":"Wang","sequence":"additional","affiliation":[{"name":"1 School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China,"},{"name":"2 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Changsha, 410083, China,"}]},{"given":"Hua","family":"Zhang","sequence":"additional","affiliation":[{"name":"1 School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China,"},{"name":"2 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Changsha, 410083, China,"}]},{"given":"Jun","family":"Yang","sequence":"additional","affiliation":[{"name":"3 Guangzhou Municipal Engineering Design Research Institute Co., Ltd., Guangzhou, 510060, China"}]},{"given":"Zhongming","family":"Yuan","sequence":"additional","affiliation":[{"name":"3 Guangzhou Municipal Engineering Design Research Institute Co., Ltd., Guangzhou, 510060, China"}]},{"given":"Lujun","family":"Zhang","sequence":"additional","affiliation":[{"name":"3 Guangzhou Municipal Engineering Design Research Institute Co., Ltd., Guangzhou, 510060, China"}]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[{"name":"3 Guangzhou Municipal Engineering Design Research Institute Co., Ltd., Guangzhou, 510060, China"}]},{"given":"Bin","family":"Zhang","sequence":"additional","affiliation":[{"name":"1 School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China,"},{"name":"2 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Changsha, 410083, China,"}]}],"member":"2613","published-online":{"date-parts":[[2021,7,7]]},"reference":[{"key":"2025120913514340300_i1083-1363-26-2-117-Allred1","doi-asserted-by":"crossref","unstructured":"Allred,\n              B.J.\n            ,\n\t\t\t\t\t\n       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Cybernetics,\n\t\t\t\t\t9(1)62\u2013\n\t\t\t\t\t66.","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"2025120913514340300_i1083-1363-26-2-117-Park1","doi-asserted-by":"crossref","unstructured":"Park,\n              B.\n            ,\n\t\t\t\t\t\tKim,J.,\n\t\t\t\t\t\tLee,J.,\n\t\t\t\t\t\tKang,M.S., and\n\t\t\t\t\t\tAn,Y.K.,\n\t\t\t\t\t\n          2018,\n\t\t\t\t\tUnderground object classification for urban roads using instantaneous phase analysis of Ground-Penetrating Radar (GPR) Data:\n\t\t\t\t\tRemote Sensing,\n\t\t\t\t\t10(9)1417.","DOI":"10.3390\/rs10091417"},{"key":"2025120913514340300_i1083-1363-26-2-117-Persico1","unstructured":"Persico,\n              R.\n            ,\n\t\t\t\t\t\tD'amico,S.,\n\t\t\t\t\t\tRizzo,E.,\n\t\t\t\t\t\tCapozzoli,L., and\n\t\t\t\t\t\tMicallef,A.,\n\t\t\t\t\t\n          2018,\n\t\t\t\t\tGround Penetrating Radar investigations in sites of cultural interest in Malta:\n\t\t\t\t\tGround Penetrating Radar,\n\t\t\t\t\t1,\n\t\t\t\t\t38\u2013\n\t\t\t\t\t61."},{"key":"2025120913514340300_i1083-1363-26-2-117-Prego1","doi-asserted-by":"crossref","unstructured":"Prego,\n              F.\n            ,\n\t\t\t\t\t\tSolla,M.,\n\t\t\t\t\t\tPuente,I., and\n\t\t\t\t\t\tArias,P.,\n\t\t\t\t\t\n          2017,\n\t\t\t\t\tEfficient GPR data acquisition to detect underground pipes:\n\t\t\t\t\tNDT & E International,\n\t\t\t\t\t91,\n\t\t\t\t\t22\u2013\n\t\t\t\t\t31.","DOI":"10.1016\/j.ndteint.2017.06.002"},{"key":"2025120913514340300_i1083-1363-26-2-117-Rashed1","doi-asserted-by":"crossref","unstructured":"Rashed,\n              M.A.\n            , and\n\t\t\t\t\t\tAl-Garni,M.A.,\n\t\t\t\t\t\n          2013,\n\t\t\t\t\tOn the application of GPR for locating underground utilities in urban areas:\n\t\t\t\t\tArabian Journal of Geosciences,\n\t\t\t\t\t6(9)3505\u2013\n\t\t\t\t\t3511.","DOI":"10.1007\/s12517-012-0588-4"},{"key":"2025120913514340300_i1083-1363-26-2-117-AlNuaimy3","doi-asserted-by":"crossref","unstructured":"Santos,\n              V.R.N.d.\n            ,\n\t\t\t\t\t\tAl-Nuaimy,W.,\n\t\t\t\t\t\tPorsani,J.L.,\n\t\t\t\t\t\tHirata,N.S.T., and\n\t\t\t\t\t\tAlzubi,H.S.,\n\t\t\t\t\t\n          2014,\n\t\t\t\t\tSpectral analysis of ground penetrating radar signals in concrete, metallic and plastic targets:\n\t\t\t\t\tJournal of Applied Geophysics,\n\t\t\t\t\t100,\n\t\t\t\t\t32\u2013\n\t\t\t\t\t43.","DOI":"10.1016\/j.jappgeo.2013.10.002"},{"key":"2025120913514340300_i1083-1363-26-2-117-Savelyev1","doi-asserted-by":"crossref","unstructured":"Savelyev,\n              T.G.\n            ,\n\t\t\t\t\t\tVan Kempen,L.,\n\t\t\t\t\t\tSahli,H.,\n\t\t\t\t\t\tSachs,J., and\n\t\t\t\t\t\tSato,M.,\n\t\t\t\t\t\n          2006,\n\t\t\t\t\tInvestigation of time\u2013frequency features for GPR landmine discrimination:\n\t\t\t\t\tIEEE Transactions on Geoscience and Remote Sensing,\n\t\t\t\t\t45(1)118\u2013\n\t\t\t\t\t129.","DOI":"10.1109\/TGRS.2006.885077"},{"key":"2025120913514340300_i1083-1363-26-2-117-Solla1","doi-asserted-by":"crossref","unstructured":"Solla,\n              M.\n            ,\n\t\t\t\t\t\tPuente,I.,\n\t\t\t\t\t\tLorenzo,H., and\n\t\t\t\t\t\tPrego,F.,\n\t\t\t\t\t\n          2017,\n\t\t\t\t\tGPR detection of underground pipes:\n\t\t\t\t\tin2017 9th International Workshop on Advanced Ground Penetrating Radar (Iwagpr),\n\t\t\t\t\t1\u2013\n\t\t\t\t\t6.","DOI":"10.1109\/IWAGPR.2017.7996073"},{"key":"2025120913514340300_i1083-1363-26-2-117-Sugak1","doi-asserted-by":"crossref","unstructured":"Sugak,\n              V.G.\n            , and\n\t\t\t\t\t\tSugak,A.V.,\n\t\t\t\t\t\n          2009,\n\t\t\t\t\tPhase spectrum of signals in ground-penetrating radar applications:\n\t\t\t\t\tIEEE Transactions on Geoscience and Remote Sensing,\n\t\t\t\t\t48(4)1760\u2013\n\t\t\t\t\t1767.","DOI":"10.1109\/TGRS.2009.2036163"},{"key":"2025120913514340300_i1083-1363-26-2-117-Sun1","doi-asserted-by":"crossref","unstructured":"Sun,\n              Y.\n            , and\n\t\t\t\t\t\tLi,J.,\n\t\t\t\t\t\n          2003,\n\t\t\t\t\tTime\u2013frequency analysis for plastic landmine detection via forward-looking ground penetrating radar:\n\t\t\t\t\tIEE Proceedings-Radar, Sonar and Navigation,\n\t\t\t\t\t150(4)253\u2013\n\t\t\t\t\t261.","DOI":"10.1049\/ip-rsn:20030681"},{"key":"2025120913514340300_i1083-1363-26-2-117-Esgandani1","doi-asserted-by":"crossref","unstructured":"Tavakoli Taba,\n              S.\n            ,\n\t\t\t\t\t\tRahnamayie Zekavat,P.,\n\t\t\t\t\t\tAlipour Esgandani,G.,\n\t\t\t\t\t\tWang,X., and\n\t\t\t\t\t\tBernold,L.,\n\t\t\t\t\t\n          2015,\n\t\t\t\t\tA multidimensional analytical approach for identifying and locating large utility pipes in underground infrastructure:\n\t\t\t\t\tInternational Journal of Distributed Sensor Networks,\n\t\t\t\t\t11(6)1\u2013\n\t\t\t\t\t10.","DOI":"10.1155\/2015\/601859"},{"key":"2025120913514340300_i1083-1363-26-2-117-Waite1","unstructured":"Waite,\n              J.W.\n            , and\n\t\t\t\t\t\tWelaratna,R.,\n\t\t\t\t\t\n          2010,\n\t\t\t\t\tSensor fusion for model-based detection in pipe and cable locator systems:\n\t\t\t\t\tU.S. Patent 7834801B2."},{"key":"2025120913514340300_i1083-1363-26-2-117-Warren1","doi-asserted-by":"crossref","unstructured":"Warren,\n              C.\n            ,\n\t\t\t\t\t\tGiannopoulos,A., and\n\t\t\t\t\t\tGiannakis,I.,\n\t\t\t\t\t\n          2016,\n\t\t\t\t\tgprMax: Open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar:\n\t\t\t\t\tComputer Physics Communications,\n\t\t\t\t\t209,\n\t\t\t\t\t163\u2013\n\t\t\t\t\t170.","DOI":"10.1016\/j.cpc.2016.08.020"},{"key":"2025120913514340300_i1083-1363-26-2-117-Xiao1","doi-asserted-by":"crossref","unstructured":"Xiao,\n              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