{"id":"https://openalex.org/W4214678451","doi":"https://doi.org/10.3390/rs14051102","title":"Automatic Generation of Urban Road 3D Models for Pedestrian Studies from LiDAR Data","display_name":"Automatic Generation of Urban Road 3D Models for Pedestrian Studies from LiDAR Data","publication_year":2022,"publication_date":"2022-02-24","ids":{"openalex":"https://openalex.org/W4214678451","doi":"https://doi.org/10.3390/rs14051102"},"language":"en","primary_location":{"id":"doi:10.3390/rs14051102","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14051102","pdf_url":"https://www.mdpi.com/2072-4292/14/5/1102/pdf?version=1645682338","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/5/1102/pdf?version=1645682338","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026071095","display_name":"David Fern\u00e1ndez-Arango","orcid":"https://orcid.org/0000-0001-7831-6118"},"institutions":[{"id":"https://openalex.org/I11019714","display_name":"Universidade da Coru\u00f1a","ror":"https://ror.org/01qckj285","country_code":"ES","type":"education","lineage":["https://openalex.org/I11019714"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"David Fern\u00e1ndez-Arango","raw_affiliation_strings":["CartoLAB, Civil Engineering Department, University of Coru\u00f1a, Campus de Elvi\u00f1a, 15071 A Coru\u00f1a, Spain"],"affiliations":[{"raw_affiliation_string":"CartoLAB, Civil Engineering Department, University of Coru\u00f1a, Campus de Elvi\u00f1a, 15071 A Coru\u00f1a, Spain","institution_ids":["https://openalex.org/I11019714"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051074152","display_name":"Francisco\u2010Alberto Varela\u2010Garc\u00eda","orcid":"https://orcid.org/0000-0001-9705-2154"},"institutions":[{"id":"https://openalex.org/I11019714","display_name":"Universidade da Coru\u00f1a","ror":"https://ror.org/01qckj285","country_code":"ES","type":"education","lineage":["https://openalex.org/I11019714"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Francisco-Alberto Varela-Garc\u00eda","raw_affiliation_strings":["CartoLAB, Civil Engineering Department, University of Coru\u00f1a, Campus de Elvi\u00f1a, 15071 A Coru\u00f1a, Spain"],"affiliations":[{"raw_affiliation_string":"CartoLAB, Civil Engineering Department, University of Coru\u00f1a, Campus de Elvi\u00f1a, 15071 A Coru\u00f1a, Spain","institution_ids":["https://openalex.org/I11019714"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086407273","display_name":"Diego Gonz\u00e1lez\u2010Aguilera","orcid":"https://orcid.org/0000-0002-8949-4216"},"institutions":[{"id":"https://openalex.org/I184999862","display_name":"Universidad de Salamanca","ror":"https://ror.org/02f40zc51","country_code":"ES","type":"education","lineage":["https://openalex.org/I184999862"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Diego Gonz\u00e1lez-Aguilera","raw_affiliation_strings":["TIDOP Research Group, Polytechnic School of Avila, University of Salamanca, Hornos Caleros, 50, 05003 Avila, Spain"],"affiliations":[{"raw_affiliation_string":"TIDOP Research Group, Polytechnic School of Avila, University of Salamanca, Hornos Caleros, 50, 05003 Avila, Spain","institution_ids":["https://openalex.org/I184999862"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091178677","display_name":"S. Lag\u00fcela","orcid":"https://orcid.org/0000-0002-9427-3864"},"institutions":[{"id":"https://openalex.org/I184999862","display_name":"Universidad de Salamanca","ror":"https://ror.org/02f40zc51","country_code":"ES","type":"education","lineage":["https://openalex.org/I184999862"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Susana Lag\u00fcela-L\u00f3pez","raw_affiliation_strings":["TIDOP Research Group, Polytechnic School of Avila, University of Salamanca, Hornos Caleros, 50, 05003 Avila, Spain"],"affiliations":[{"raw_affiliation_string":"TIDOP Research Group, Polytechnic School of Avila, University of Salamanca, Hornos Caleros, 50, 05003 Avila, Spain","institution_ids":["https://openalex.org/I184999862"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5051074152"],"corresponding_institution_ids":["https://openalex.org/I11019714"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.8143,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.82685732,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"14","issue":"5","first_page":"1102","last_page":"1102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9986000061035156,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9901000261306763,"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/lidar","display_name":"Lidar","score":0.8248151540756226},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8021559715270996},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.8008929491043091},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6720101833343506},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5914156436920166},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.46712714433670044},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.457898885011673},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42910879850387573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3554879426956177},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.25257447361946106},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08411175012588501}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8248151540756226},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8021559715270996},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8008929491043091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6720101833343506},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5914156436920166},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.46712714433670044},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.457898885011673},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42910879850387573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3554879426956177},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.25257447361946106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08411175012588501},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/rs14051102","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14051102","pdf_url":"https://www.mdpi.com/2072-4292/14/5/1102/pdf?version=1645682338","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:27fe37c6ac2f4164a7519487559f57a9","is_oa":true,"landing_page_url":"https://doaj.org/article/27fe37c6ac2f4164a7519487559f57a9","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 5, p 1102 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/5/1102/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14051102","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 5; Pages: 1102","raw_type":"Text"},{"id":"pmh:oai:ruc.udc.es:2183/30295","is_oa":true,"landing_page_url":"http://hdl.handle.net/2183/30295","pdf_url":null,"source":{"id":"https://openalex.org/S4306402204","display_name":"RUC (Universidade Da Coru\u00f1a)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3390/rs14051102","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14051102","pdf_url":"https://www.mdpi.com/2072-4292/14/5/1102/pdf?version=1645682338","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214678451.pdf","grobid_xml":"https://content.openalex.org/works/W4214678451.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1100793965","https://openalex.org/W1652321627","https://openalex.org/W1665692061","https://openalex.org/W1993610193","https://openalex.org/W1998970860","https://openalex.org/W2027251975","https://openalex.org/W2034546021","https://openalex.org/W2041330605","https://openalex.org/W2058155422","https://openalex.org/W2061408062","https://openalex.org/W2062520712","https://openalex.org/W2065171041","https://openalex.org/W2071347898","https://openalex.org/W2072723786","https://openalex.org/W2077506631","https://openalex.org/W2081780340","https://openalex.org/W2108897342","https://openalex.org/W2146798134","https://openalex.org/W2153977410","https://openalex.org/W2168308100","https://openalex.org/W2344796101","https://openalex.org/W2418781187","https://openalex.org/W2439667875","https://openalex.org/W2509596959","https://openalex.org/W2591025285","https://openalex.org/W2621322324","https://openalex.org/W2769699424","https://openalex.org/W2771339660","https://openalex.org/W2780653514","https://openalex.org/W2801833195","https://openalex.org/W2807603166","https://openalex.org/W2892061931","https://openalex.org/W2893333163","https://openalex.org/W2921345404","https://openalex.org/W2948640216","https://openalex.org/W2950401571","https://openalex.org/W2964203982","https://openalex.org/W2972999127","https://openalex.org/W2973304995","https://openalex.org/W2981224252","https://openalex.org/W2981937739","https://openalex.org/W2982279316","https://openalex.org/W2993330821","https://openalex.org/W2996385626","https://openalex.org/W3007185520","https://openalex.org/W3043821922","https://openalex.org/W3048185541","https://openalex.org/W3094398790","https://openalex.org/W3175921267","https://openalex.org/W3189999916","https://openalex.org/W3198402969","https://openalex.org/W4214748362","https://openalex.org/W6751762173","https://openalex.org/W7000594965"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4210818033","https://openalex.org/W4293094720","https://openalex.org/W2739701376"],"abstract_inverted_index":{"The":[0,134],"point":[1,55,83],"clouds":[2,56],"acquired":[3,59],"with":[4,60],"a":[5,43,88],"mobile":[6],"LiDAR":[7,82,116,193],"scanner":[8],"(MLS)":[9],"have":[10],"high":[11,143],"density":[12],"and":[13,62,110,169,176,191],"accuracy,":[14],"which":[15,158],"allows":[16],"one":[17],"to":[18,45,67,96,154,161],"identify":[19],"different":[20],"elements":[21],"of":[22,80,92,115,136,145,150,178],"the":[23,37,47,77,81,93,97,113,131,142,146,151,165,174,184,188,192],"road":[24],"in":[25,31,36,70,76,118,130,141,164,180,202],"them,":[26],"as":[27,126],"can":[28],"be":[29,68],"found":[30],"many":[32],"scientific":[33],"references,":[34],"especially":[35],"last":[38],"decade.":[39],"This":[40],"study":[41],"presents":[42],"methodology":[44],"characterize":[46],"urban":[48,181],"space":[49,153],"available":[50],"for":[51,122,167,199],"walking,":[52],"by":[53,103,107],"segmenting":[54],"from":[57],"data":[58,194],"MLS":[61],"automatically":[63],"generating":[64],"impedance":[65],"surfaces":[66],"used":[69,195],"pedestrian":[71,123,152,156,171],"accessibility":[72],"studies.":[73],"Common":[74],"problems":[75,101],"automatic":[78],"segmentation":[79,91],"cloud":[84],"were":[85,128],"corrected,":[86],"achieving":[87],"very":[89],"accurate":[90],"points":[94,117],"belonging":[95],"ground.":[98],"In":[99],"addition,":[100],"caused":[102,105],"occlusions":[104],"mainly":[106],"parked":[108],"vehicles":[109],"that":[111],"prevent":[112],"availability":[114],"spaces":[119],"normally":[120],"intended":[121],"circulation,":[124],"such":[125],"sidewalks,":[127],"solved":[129],"proposed":[132],"methodology.":[133],"innovation":[135],"this":[137],"method":[138],"lies,":[139],"therefore,":[140],"definition":[144],"generated":[147],"3D":[148],"model":[149,155],"mobility,":[157],"allowed":[159],"us":[160],"apply":[162],"it":[163],"search":[166],"shorter":[168],"safer":[170],"paths":[172],"between":[173],"homes":[175],"schools":[177],"students":[179],"areas":[182],"within":[183],"Big-Geomove":[185],"project.":[186],"Both":[187],"developed":[189],"algorithms":[190],"are":[196],"freely":[197],"licensed":[198],"their":[200],"use":[201],"further":[203],"research.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}