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Towards an optimization of sample plot size and scanner position layout for terrestrial laser scanning in multi-scan mode / Tim Ritter in Forests, vol 11 n° 10 (October 2020)  

Public [article]  inForests > vol 11 n° 10 (October 2020) . - n° 1099 Titre : Towards an optimization of sample plot size and scanner position layout for terrestrial laser scanning in multi-scan mode Type de document : Article/Communication Auteurs : Tim Ritter, Auteur ; Christoph Gollob, Auteur ; Arne Northdurft, Auteur Année de publication : 2020 Article en page(s) : n° 1099 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Autriche [Termes IGN] balayage laser [Termes IGN] détection d'arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] échantillonnage [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] placette d'échantillonnage [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre Résumé : (auteur) A novel approach is presented to model the tree detection probability of terrestrial laser scanning (TLS) in forest inventory applications using a multi-scan mode. The traditional distance sampling framework is further extended to account for multiple scan positions at a single sample plot and to allow for an imperfect detection probability at distance r = 0. The novel methodology is tested with real world data, as well as in simulations. It is shown that the underlying detection model can be parameterized using only data from single scans. Hereby, it is possible to predict the detection probability also for different sample plot sizes and scanner position layouts in a multi-scan setting. Simulations showed that a minor discretization bias can occur if the sample size is small. The methodology enables a generalized optimization of the scanning layout in a multi-scan setting with respect to the detection probability and the sample plot area. This will increase the efficiency of multi-scan TLS-based forest inventories in the future. Numéro de notice : A2020-754 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f11101099 Date de publication en ligne : 16/10/2020 En ligne : https://doi.org/10.3390/f11101099 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96438 [article]