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Cross-correlation of diameter measures for the co-registration of forest inventory plots with airborne laser scanning data / Jean-Matthieu Monnet in Forests, vol 5 n° 9 (September 2014)  

Public [article]  inForests > vol 5 n° 9 (September 2014) . - pp 2307 - 2326 Titre : Cross-correlation of diameter measures for the co-registration of forest inventory plots with airborne laser scanning data Type de document : Article/Communication Auteurs : Jean-Matthieu Monnet, Auteur ; Eric Mermin, Auteur Année de publication : 2014 Article en page(s) : pp 2307 - 2326 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] dendrométrie [Termes IGN] forêt tempérée [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lasergrammétrie [Termes IGN] Pinophyta [Termes IGN] semis de points [Termes IGN] superposition d'images [Termes IGN] télémétrie laser aéroporté Mots-clés libres : forest inventory  airborne laser scanning  co-registration  Global Navigation Satellite System Résumé : (auteur) Continuous maps of forest parameters can be derived from airborne laser scanning (ALS) remote sensing data. A prediction model is calibrated between local point cloud statistics and forest parameters measured on field plots. Unfortunately, inaccurate positioning of field measures lead to a bad matching of forest measures with remote sensing data. The potential of using tree diameter and position measures in cross-correlation with ALS data to improve co-registration is evaluated. The influence of the correction on ALS models is assessed by comparing the accuracy of basal area prediction models calibrated or validated with or without the corrected positions. In a coniferous, uneven-aged forest with high density ALS data and low positioning precision, the algorithm co-registers 91% of plots within two meters from the operator location when at least the five largest trees are used in the analysis. The new coordinates slightly improve the prediction models and allow a better estimation of their accuracy. In a forest with various stand structures and species, lower ALS density and differential Global Navigation Satellite System measurements, position correction turns out to have only a limited impact on prediction models. Numéro de notice : A2014-620 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f5092307 En ligne : https://doi.org/10.3390/f5092307 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74968 [article]