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dc.contributor.authorSoilán Rodríguez, Mario
dc.contributor.authorGonzález Aguilera, Diego 
dc.contributor.authorCampo Sánchez, Ana del 
dc.contributor.authorHernández López, David
dc.contributor.authorPozo Aguilera, Susana del 
dc.date.accessioned2024-09-10T11:00:04Z
dc.date.available2024-09-10T11:00:04Z
dc.date.issued2022
dc.identifier.citationSoilán, M., González-Aguilera, D., del-Campo-Sánchez, A., Hernández-López, D., & Del Pozo, S. (2022). Road marking degradation analysis using 3D point cloud data acquired with a low-cost Mobile Mapping System. Automation in Construction, 141, 104446. https://doi.org/10.1016/j.autcon.2022.104446es_ES
dc.identifier.issn0926-5805
dc.identifier.urihttp://hdl.handle.net/10366/159496
dc.description.abstract[EN] Road maintenance is an important task that ensures the availability and correct function of the road infrastructure. This work presents a methodology that, first, offers an empirical radiometric analysis of the Velodyne VLP-32C laser scanner. Second, it defines a road marking degradation model that estimates the coefficient of retroreflected luminance (night visibility, RL) using the intensity attribute of 3D point clouds acquired with this low-cost system. This model is validated and applied to a case study road section of about 6 km in length, where a continuous degradation map is defined together with data to assist decision-making for preventive and corrective maintenance. This validation shows that the proposed method is capable of offering good qualitative visualizations of the degradation status of the road markings, as well as detecting those areas with high degradation (RL< 100 mcd/m2 /lx) that require corrective maintenance.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMobile LiDAR systemes_ES
dc.subject3D point cloudes_ES
dc.subjectRoad markingses_ES
dc.subjectRoad maintenancees_ES
dc.subjectRetroreflectivity degradationes_ES
dc.titleRoad marking degradation analysis using 3D point cloud data acquired with a low-cost Mobile Mapping Systemes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.subject.unesco2511.03 Cartografía de Sueloses_ES
dc.identifier.doi10.1016/j.autcon.2022.104446
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleAutomation in Constructiones_ES
dc.volume.number141es_ES
dc.page.initial1es_ES
dc.page.final11es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.description.projectPublicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024


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Attribution-4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-4.0 Internacional