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Auteur Thomas Pons |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesPathway detection and geometrical description from ALS data in forested mountaneous area / Nicolas David (2009)
contenu dans ISPRS Workshop Laserscanning'09, Paris, France, September 1-2, 2009 / Frédéric Bretar (2009)
Titre : Pathway detection and geometrical description from ALS data in forested mountaneous area Type de document : Article/Communication Auteurs : Nicolas David Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2009 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 38-3/W8 Conférence : ISPRS 2009, Workshop LaserScanning 01/09/2009 02/09/2009 Paris France OA Archives proceedings Importance : pp 242 - 247 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] extraction automatique
[Termes IGN] forêt
[Termes IGN] montagne
[Termes IGN] orthoimage
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) In the last decade, airborne laser scanning (ALS) systems have become an alternative source for the acquisition of altimeter data. Compared to high resolution orthoimages, one of the main advantages of ALS is the ability of the laser beam to penetrate vegetation and reach the ground underneath. Therefore, 3D point clouds are essential data for computing Digital Terrain Models (DTM) in natural and vegetated areas. DTMs are a key product for many applications such as tree detection, flood modelling, archeology or road detection. Indeed, in forested areas, traditional image-based algorithms for road and pathway detection would partially fail due to their occlusion by the canopy cover. Thus, crucial information for forest management and fire prevention such as road width and slope would be misevaluated.
This paper deals with road and pathway detection in a complex forested mountaneous area and with their geometrical parameter extraction using lidar data. Firstly, a three-step image-based methodology is proposed to detect road regions. Lidar feature orthoimages are first generated. Then, road seeds are both automatically and semi-automatically detected. And, a region growing algorithm is carried out to retrieve the full pathways from the seeds previously detected. Secondly, these pathways are vectorized using morphological tools, smoothed, and discretized. Finally, ID sections within the lidar point cloud are successively generated for each point of the pathways to estimate more accurately road widths in 3D. We also retrieve a precise location of the pathway borders and centers, exported as vector data.Numéro de notice : C2009-006 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVIII/3-W8/papers/242_laserscanning09.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65046
