{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T18:03:10Z","timestamp":1770487390626,"version":"3.49.0"},"reference-count":36,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2016,9,7]],"date-time":"2016-09-07T00:00:00Z","timestamp":1473206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate road asphalt extent delineation is needed for road and street planning, road maintenance, and road safety assessment. In this article, a new approach for automatic roadside delineation is developed based on the line clouds concept. The method relies on line cloud grouping from point cloud laser data. Using geometric criteria, the initial 3D LiDAR point data is structured in lines covering the road surface. These lines are then grouped according to a set of quasi-planar restriction rules. Road asphalt edge limits are extracted from the end points of lines belonging to these groups. Finally a two-stage smoothing procedure is applied to correct for edge occlusions and other anomalies. The method was tested on a 2.1 km stretch of road, and the results were checked using a RTK-GNSS measured dataset as ground truth. Correctness and completeness were 99% and 97%, respectively.<\/jats:p>","DOI":"10.3390\/rs8090740","type":"journal-article","created":{"date-parts":[[2016,9,7]],"date-time":"2016-09-07T09:59:46Z","timestamp":1473242386000},"page":"740","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept"],"prefix":"10.3390","volume":"8","author":[{"given":"Carlos","family":"Cabo","sequence":"first","affiliation":[{"name":"Department of Mining Exploitation, University of Oviedo, 33004 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3841-6533","authenticated-orcid":false,"given":"Antero","family":"Kukko","sequence":"additional","affiliation":[{"name":"Finnish Geospatial Research Institute FGI, P.O. 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