{"id":"https://openalex.org/W3118436882","doi":"https://doi.org/10.1109/tgrs.2020.3046624","title":"Tunnel Reconstruction With Block Level Precision by Combining Data-Driven Segmentation and Model-Driven Assembly","display_name":"Tunnel Reconstruction With Block Level Precision by Combining Data-Driven Segmentation and Model-Driven Assembly","publication_year":2021,"publication_date":"2021-01-12","ids":{"openalex":"https://openalex.org/W3118436882","doi":"https://doi.org/10.1109/tgrs.2020.3046624","mag":"3118436882"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3046624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3046624","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103031182","display_name":"Zhen Cao","orcid":"https://orcid.org/0000-0002-3870-1342"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Cao","raw_affiliation_strings":["College of Civil Engineering, Nanjing Forestry University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Civil Engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013116360","display_name":"Dong Chen","orcid":"https://orcid.org/0000-0001-8118-3889"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Chen","raw_affiliation_strings":["College of Civil Engineering, Nanjing Forestry University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8118-3889","affiliations":[{"raw_affiliation_string":"College of Civil Engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027174277","display_name":"Jiju Peethambaran","orcid":"https://orcid.org/0000-0003-0245-5933"},"institutions":[{"id":"https://openalex.org/I66890659","display_name":"Saint Mary's University","ror":"https://ror.org/010zh7098","country_code":"CA","type":"education","lineage":["https://openalex.org/I66890659"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiju Peethambaran","raw_affiliation_strings":["Saint Mary\u2019s University, Halifax, NS, Canada","Saint Mary's University, Halifax, NS, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0245-5933","affiliations":[{"raw_affiliation_string":"Saint Mary\u2019s University, Halifax, NS, Canada","institution_ids":["https://openalex.org/I66890659"]},{"raw_affiliation_string":"Saint Mary's University, Halifax, NS, Canada","institution_ids":["https://openalex.org/I66890659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101584424","display_name":"Zhenxin Zhang","orcid":"https://orcid.org/0000-0002-4070-9415"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenxin Zhang","raw_affiliation_strings":["College of Resource Environment and Tourism, Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Resource Environment and Tourism, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060714617","display_name":"Shaobo Xia","orcid":"https://orcid.org/0000-0003-2890-838X"},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaobo Xia","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2890-838X","affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou, China","institution_ids":["https://openalex.org/I1284762954"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100459445","display_name":"Liqiang Zhang","orcid":"https://orcid.org/0000-0002-4175-7590"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liqiang Zhang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4175-7590","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":3.4227,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91868727,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"59","issue":"10","first_page":"8853","last_page":"8872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6757445335388184},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6170933246612549},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6036993265151978},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5806683301925659},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5331665277481079},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4938872456550598},{"id":"https://openalex.org/keywords/geometric-modeling","display_name":"Geometric modeling","score":0.4888107478618622},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.48580336570739746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3810771703720093},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3734455108642578},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.256718248128891},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17528396844863892}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6757445335388184},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6170933246612549},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6036993265151978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5806683301925659},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5331665277481079},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4938872456550598},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.4888107478618622},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.48580336570739746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3810771703720093},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3734455108642578},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.256718248128891},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17528396844863892},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.3046624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3046624","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G184730824","display_name":null,"funder_award_id":"BK20201387","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G2765049426","display_name":null,"funder_award_id":"41925006","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G4813990130","display_name":null,"funder_award_id":"41971415","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4858439871","display_name":null,"funder_award_id":"OFSLRSS202010","funder_id":"https://openalex.org/F4320335627","funder_display_name":"State Key Laboratory on Integrated Optoelectronics"},{"id":"https://openalex.org/G8836907405","display_name":"\u7ed3\u5408\u6ce8\u610f\u529b\u673a\u5236\u4e0e\u56fe\u5377\u79ef\u7f51\u7edc\u7684\u57ce\u5e02\u673a\u8f7d\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u591a\u5c42\u6b21\u5206\u7c7b\u6846\u67b6\u7814\u7a76","funder_award_id":"42071445","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335627","display_name":"State Key Laboratory on Integrated Optoelectronics","ror":"https://ror.org/00g102351"},{"id":"https://openalex.org/F4320336125","display_name":"National Science Fund for Distinguished Young Scholars","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W583811195","https://openalex.org/W1967649450","https://openalex.org/W1974895096","https://openalex.org/W1984183434","https://openalex.org/W2002905080","https://openalex.org/W2008229822","https://openalex.org/W2015360410","https://openalex.org/W2025071037","https://openalex.org/W2041239366","https://openalex.org/W2056600095","https://openalex.org/W2068707117","https://openalex.org/W2086867995","https://openalex.org/W2161406750","https://openalex.org/W2294798173","https://openalex.org/W2315859565","https://openalex.org/W2490585773","https://openalex.org/W2523639810","https://openalex.org/W2529270944","https://openalex.org/W2600960406","https://openalex.org/W2747499831","https://openalex.org/W2761306280","https://openalex.org/W2774823974","https://openalex.org/W2790820546","https://openalex.org/W2883774903","https://openalex.org/W2884374137","https://openalex.org/W2887055065","https://openalex.org/W2912354362","https://openalex.org/W2942820218","https://openalex.org/W2943613273","https://openalex.org/W2944991824","https://openalex.org/W2950458645","https://openalex.org/W2952242721","https://openalex.org/W2954901821","https://openalex.org/W3008534570","https://openalex.org/W3015072278","https://openalex.org/W3093009701","https://openalex.org/W4210521336","https://openalex.org/W6683746961"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W3016928466","https://openalex.org/W4389574804","https://openalex.org/W2357409937","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W2114282491","https://openalex.org/W2800228358"],"abstract_inverted_index":{"Metro":[0],"subway":[1,20,48],"systems":[2,21,54],"with":[3,145,234],"underground":[4],"tunnels":[5,38,216],"form":[6],"the":[7,43,93,114,136,165,173,219,249,254],"backbone":[8],"of":[9,18,30,32,37,46,79,148,197,226,238,241,253],"urban":[10],"transportations":[11],"and":[12,16,60,106,126,164,190,206,213,251],"therefore,":[13],"accurate":[14],"monitoring":[15,45,53],"maintenance":[17],"such":[19,47],"are":[22,39,143,169],"extremely":[23],"necessary":[24],"for":[25,42],"a":[26,71,101,107,124,146,153,157,235],"hassle-free":[27],"daily":[28],"commutation":[29],"billions":[31],"people.":[33],"Though":[34],"3-D":[35,115,137,141,150,167],"models":[36,59,78],"widely":[40],"used":[41],"deformation":[44],"tunnels,":[49],"existing":[50],"model-based":[51],"tunnel":[52,66,80,116,176,180,192,256],"rely":[55],"on":[56,187,211],"coarse":[57],"geometric":[58,77,207,220],"hence":[61],"fail":[62],"to":[63,74,171],"capture":[64],"complete":[65],"health":[67],"information.":[68],"We":[69],"present":[70],"two-stage":[72],"algorithm":[73,105],"create":[75,172],"high-fidelity":[76],"lining":[81,127],"from":[82,131,135,152],"Terrestrial":[83],"Laser":[84],"Scanning":[85],"(TLS)":[86],"point":[87,201],"clouds.":[88],"Tunnel":[89],"geometry,":[90],"defined":[91],"at":[92],"detailed":[94],"block":[95,103,117],"entity":[96],"level,":[97],"is":[98,231],"constructed":[99],"through":[100],"data-driven":[102],"segmentation":[104,118],"model-driven":[108],"assembly":[109],"technique.":[110],"In":[111],"our":[112],"approach,":[113],"problem":[119,130],"has":[120,183],"been":[121,184],"translated":[122],"into":[123],"bolt":[125],"joint":[128],"recognition":[129],"2-D":[132],"images":[133],"unfolded":[134],"scans.":[138],"The":[139,178,209],"segmented":[140],"blocks":[142],"matched":[144,166],"set":[147],"predefined":[149],"templates":[151,168],"primitive":[154],"library":[155],"via":[156],"constraint":[158],"total":[159],"least":[160],"squares":[161],"matching":[162],"method":[163,182],"assembled":[170],"final":[174],"watertight":[175],"model.":[177],"proposed":[179,255],"modeling":[181,257],"comprehensively":[185],"evaluated":[186],"Changzhou,":[188],"Nanjing,":[189],"Wuhan":[191],"data":[193,244],"sets":[194],"in":[195],"terms":[196],"outliers,":[198],"missing":[199],"data,":[200],"density,":[202],"topological":[203],"representation,":[204],"robustness,":[205],"accuracy.":[208],"experiments":[210],"Nanjing":[212],"Changzhou":[214],"metro":[215],"show":[217],"that":[218],"model":[221],"fitting":[222],"incurs":[223],"an":[224],"error":[225],"only":[227],"7":[228],"mm,":[229],"which":[230],"almost":[232],"consistent":[233],"mean":[236],"density":[237],"6":[239],"mm":[240],"these":[242],"two":[243],"sets.":[245],"Experimental":[246],"results":[247],"validate":[248],"advantages":[250],"potentials":[252],"method.":[258]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}
