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dc.contributor.authorSoilán, Mario-
dc.contributor.authorTruong-Hong, Linh-
dc.contributor.authorRiveiro, Belén-
dc.contributor.authorLaefer, Debra F.-
dc.identifier.citationSoilán, M., Truong-Hong, L., Riveiro, B., Laefer, D.F. (2017). Automatic extraction of road features in urban environments using dense ALS data. International Journal of Applied Earth Observation and Geoinformation, 64, 226–236, doi:10.1016/j.jag.2017.09.010en
dc.description.abstractThis paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection.en
dc.description.sponsorshipSpanish Ministry of Economy and Competitiveness through the project HERMES:S3D – Healthy and Efficient Routes in Massive Open-data based Smart Cities (Ref.: TIN201346801-C4-4-R); Human Resources program FPI(Grant BES-2014-067736); Fundación Barrié (Grant holder – Ayudas a la Movilidad Internacional de Jóvenes Investigadores de Programas de Doctorado Sistema Universitario de Galicia 2016).en
dc.rights© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
dc.subjectAirborne laser scanningen
dc.subjectPoint cloud segmentationen
dc.subjectUrban modellingen
dc.subjectPavements classificationen
dc.subjectRemote sensingen
dc.titleAutomatic extraction of road features in urban environments using dense ALS dataen
prism.publicationNameInternational Journal of Applied Earth Observation and Geoinformationen
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