Interurban visibility diagnosis from point clouds

UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.endPage690es_ES
UDC.grupoInvInformation Retrieval Lab (IRlab)es_ES
UDC.issue1es_ES
UDC.journalTitleEuropean Journal of Remote Sensinges_ES
UDC.startPage673es_ES
UDC.volume49es_ES
dc.contributor.authorIglesias Valiño, Óscar
dc.contributor.authorDíaz-Vilariño, Lucía
dc.contributor.authorGonzález-Jorge, Higinio
dc.contributor.authorLorenzo, Henrique
dc.date.accessioned2025-01-24T19:26:22Z
dc.date.available2025-01-24T19:26:22Z
dc.date.issued2016
dc.description.abstract[Abstract]: We present an approach for automatic visibility analysis in interurban roads from point clouds. The methodology is based on a ray-tracing algorithm followed by an occlusion detection to identify potential obstacles between the driver and the theoretical position of pedestrians and cyclists. As a result, the area of visibility from each driver position is obtained. The method compares the performance and suitability of point clouds acquired from both Airborne and Mobile Laser Scanning. The methodology is tested in six real case studies. In most cases, results obtained from MLS are more accurate since the point clouds are acquired from a perspective similar to driver and they have higher resolution.es_ES
dc.description.sponsorshipAuthors would like to thank to the Dirección General de Tráfico (Ministerio del Interior), Ministerio de Economía y Competitividad (Gobierno de España), and Xunta de Galicia, for the financial support given through the grants (SPIP20141500, CN2012/269, ENE2013- 48015-C3-1-R,TIN2013-46801-C4-4-R).es_ES
dc.description.sponsorshipDirección General de Tráfico (DGT); SPIP20141500es_ES
dc.description.sponsorshipXunta de Galicia; CN2012/269es_ES
dc.identifier.citationIglesias, Ó., Díaz-Vilariño, L., González-Jorge, H., & Lorenzo, H. (2016). Interurban visibility diagnosis from point clouds. European Journal of Remote Sensing, 49(1), 673–690. https://doi.org/10.5721/EuJRS20164935es_ES
dc.identifier.doi10.5721/EuJRS20164935
dc.identifier.issn2279-7254
dc.identifier.urihttp://hdl.handle.net/2183/40900
dc.language.isoenges_ES
dc.publisherTaylor and Francises_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ENE2013-48015-C3-1-R/ES/SISTEMA INTEGRADO PARA LA OPTIMIZACION ENERGETICA Y REDUCCION DE LA HUELLA DE CO2 EN EDIFICIOS: TECNOLOGIAS BIM, INDOOR MAPPING, UAV Y HERRAMIENTAS DE SIMULACION ENERGETICAes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2013-46801-C4-4-R/ES/HEALTHY AND EFFICIENT ROUTES IN MASSIVE OPEN-DATA BASED SMART CITIES: SMART 3D MODELLINGes_ES
dc.relation.urihttps://doi.org/10.5721/EuJRS20164935es_ES
dc.rights© 2016 The Author(s)es_ES
dc.rightsAtribución 4.0 Internacional (CC-BY 4.0)es_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectVisibilityes_ES
dc.subjectPoint cloudses_ES
dc.subjectMobile Laser Scanninges_ES
dc.subjectAirborne Laser Scanninges_ES
dc.subjectRoad safetyes_ES
dc.titleInterurban visibility diagnosis from point cloudses_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication2525180e-687a-436c-9032-f46f72c38858
relation.isAuthorOfPublication.latestForDiscovery2525180e-687a-436c-9032-f46f72c38858

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