{"id":"https://openalex.org/W2057116809","doi":"https://doi.org/10.1109/igarss.2014.6947444","title":"Large scale road network extraction in forested moutainous areas using airborne laser scanning data","display_name":"Large scale road network extraction in forested moutainous areas using airborne laser scanning data","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2057116809","doi":"https://doi.org/10.1109/igarss.2014.6947444","mag":"2057116809"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2014.6947444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070888429","display_name":"Ant\u00f3nio Ferraz","orcid":"https://orcid.org/0000-0002-5328-5471"},"institutions":[{"id":"https://openalex.org/I4210125590","display_name":"Institute for Systems Engineering and Computers","ror":"https://ror.org/033wn8m60","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Antonio Ferraz","raw_affiliation_strings":["IGN/SR, Universite Paris Est, Saint-Mande, France","R&D Unit INESC Coimbra, Coimbra, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IGN/SR, Universite Paris Est, Saint-Mande, France","institution_ids":[]},{"raw_affiliation_string":"R&D Unit INESC Coimbra, Coimbra, Portugal","institution_ids":["https://openalex.org/I4210125590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001898964","display_name":"Cl\u00e9ment Mallet","orcid":"https://orcid.org/0000-0002-2675-165X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Clement Mallet","raw_affiliation_strings":["IGN/SR, Universite Paris Est, Saint-Mande, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IGN/SR, Universite Paris Est, Saint-Mande, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079887945","display_name":"Nesrine Chehata","orcid":"https://orcid.org/0000-0002-0614-1678"},"institutions":[{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210134548","display_name":"Institut de Recherche pour le D\u00e9veloppement","ror":"https://ror.org/044vzpb64","country_code":"TN","type":"government","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1327553481","https://openalex.org/I154202486","https://openalex.org/I2799535048","https://openalex.org/I2802818602","https://openalex.org/I4210088668","https://openalex.org/I4210090127","https://openalex.org/I4210113730","https://openalex.org/I4210131494","https://openalex.org/I4210134548","https://openalex.org/I4210166358","https://openalex.org/I4210166444","https://openalex.org/I4405257220"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4387154061","display_name":"Laboratoire d'\u00e9tude des Interactions Sol - Agrosyst\u00e8me - Hydrosyst\u00e8me","ror":"https://ror.org/05deqk823","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1327553481","https://openalex.org/I154202486","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I2799535048","https://openalex.org/I2802818602","https://openalex.org/I4210088668","https://openalex.org/I4210088668","https://openalex.org/I4210090127","https://openalex.org/I4210113730","https://openalex.org/I4210117091","https://openalex.org/I4210131494","https://openalex.org/I4210166444","https://openalex.org/I4387154061","https://openalex.org/I4399657933","https://openalex.org/I4405257220"]}],"countries":["FR","TN"],"is_corresponding":false,"raw_author_name":"Nesrine Chehata","raw_affiliation_strings":["IRD/UMR LISAH, Tunis, Tunisia","Laboratoire GE (EA 4592), IPB Universite de Bordeaux, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRD/UMR LISAH, Tunis, Tunisia","institution_ids":["https://openalex.org/I4210134548","https://openalex.org/I4387154061"]},{"raw_affiliation_string":"Laboratoire GE (EA 4592), IPB Universite de Bordeaux, France","institution_ids":["https://openalex.org/I15057530","https://openalex.org/I4210160189"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7327,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81908714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4315","last_page":"4318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"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/T12644","display_name":"Wildlife-Road Interactions and Conservation","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.684078574180603},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6435949206352234},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6336535811424255},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5842239260673523},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5693032145500183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5144772529602051},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5022473335266113},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4401856064796448},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"Laser scanning","score":0.43512314558029175},{"id":"https://openalex.org/keywords/road-map","display_name":"Road map","score":0.4292711913585663},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.4179782271385193},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38920122385025024},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37661731243133545},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3532114028930664},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32252413034439087},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17784935235977173},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.16094806790351868},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11228528618812561},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10996666550636292},{"id":"https://openalex.org/keywords/laser","display_name":"Laser","score":0.10764822363853455}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.684078574180603},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6435949206352234},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6336535811424255},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5842239260673523},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5693032145500183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5144772529602051},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5022473335266113},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4401856064796448},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.43512314558029175},{"id":"https://openalex.org/C188048851","wikidata":"https://www.wikidata.org/wiki/Q2298569","display_name":"Road map","level":2,"score":0.4292711913585663},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.4179782271385193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38920122385025024},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37661731243133545},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3532114028930664},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32252413034439087},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17784935235977173},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.16094806790351868},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11228528618812561},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10996666550636292},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.10764822363853455},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2014.6947444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-02384474v1","is_oa":false,"landing_page_url":"https://inria.hal.science/hal-02384474","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium, Jul 2014, Quebec City, Canada. pp.4315-4318, &#x27E8;10.1109/IGARSS.2014.6947444&#x27E9;","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2029377763","https://openalex.org/W2096666883","https://openalex.org/W2102048636","https://openalex.org/W2102083336","https://openalex.org/W2115430125","https://openalex.org/W2120531866","https://openalex.org/W2625544450"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1924178503","https://openalex.org/W1974056099","https://openalex.org/W4245343541"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,32],"present":[4],"an":[5],"approach":[6],"that":[7,41,80],"is":[8,59],"able":[9],"to":[10,82],"deal":[11],"with":[12,90],"large-scale":[13],"road":[14,30,39,54],"network":[15],"mapping.":[16],"While":[17],"former":[18],"methods":[19,71],"focus":[20],"on":[21,53],"delineating":[22],"patches":[23],"of":[24,38,63],"roads":[25],"without":[26],"computing":[27],"a":[28,34,45,50],"coherent":[29],"network,":[31],"formulate":[33],"very":[35,84,91],"large":[36,85],"number":[37],"hypothesis":[40],"are":[42],"pruned":[43],"using":[44],"graph":[46],"reasoning":[47],"and":[48,67,76],"weak":[49],"priori":[51],"knowledge":[52],"behavior.":[55],"The":[56],"initial":[57],"solution":[58],"computed":[60],"by":[61],"means":[62],"two":[64],"machine":[65],"learning":[66],"pattern":[68],"recognition":[69],"state-of-the-art":[70],"(namely,":[72],"Random":[73],"Forest":[74],"classification":[75],"Marked":[77],"Point":[78],"Process)":[79],"allow":[81],"process":[83],"areas":[86],"in":[87],"little":[88],"time":[89],"satisfactory":[92],"results.":[93]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
