Détail de l'autorité
SPIE 2012, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions Conference 24/09/2012 27/09/2012 Edimbourg Royaume-Uni Proceedings SPIE
nom du congrès :
SPIE 2012, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions Conference
début du congrès :
24/09/2012
fin du congrès :
27/09/2012
ville du congrès :
Edimbourg
pays du congrès :
Royaume-Uni
site des actes du congrès :
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Change detection of trees in urban areas using multi-temporal airborne lidar point clouds / Wen Xiao (2012)
Titre : Change detection of trees in urban areas using multi-temporal airborne lidar point clouds Type de document : Article/Communication Auteurs : Wen Xiao, Auteur ; Sudan Xu, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur Editeur : Washington : Society of Photo-Optical Instrumentation Engineers SPIE Année de publication : 2012 Conférence : SPIE 2012, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions Conference 24/09/2012 27/09/2012 Edimbourg Royaume-Uni Proceedings SPIE Importance : n° 853207 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection d'arbres
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) Light detection and ranging (lidar) provides a promising way of detecting changes of vegetation in three dimensions (3D) because the beam of laser may penetrate through the foliage of vegetation. This study aims at the detection of changes in trees in urban areas with a high level of automation using mutil-temporal airborne lidar point clouds. Three datasets covering a part of Rotterdam, the Netherlands, have been classified into several classes including trees. A connected components algorithm was applied first to group the points of trees together. The attributes of components were utilized to differentiate tree components from misclassified non-tree components. A point based local maxima algorithm was implemented to distinguish single tree from multiple tree components. After that, the parameters of trees were derived through two independent ways: a point based method using 3D alpha shapes and convex hulls; and a model based method which fits a Pollock tree model to the points. Then the changes were detected by comparing the parameters of corresponding tree components which were matched by a tree to tree matching algorithm using the overlapping of bounding boxes and point to point distances. The results were visualized and statistically analyzed. The difference of parameters and the difference of changes derived from point based and model based methods were both lower than 10%. The comparison of these two methods illustrates the consistency and stability of the parameters. The detected changes show the potential to monitor the growth and pruning of trees. Numéro de notice : C2012-028 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1117/12.974266 Date de publication en ligne : 19/10/2012 En ligne : https://doi.org/10.1117/12.974266 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101192