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Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey / L. Wang in Geoinformatica, vol 17 n° 1 (January 2013)  

Public [article]  inGeoinformatica > vol 17 n° 1 (January 2013) . - pp 35 - 61 Titre : Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey Type de document : Article/Communication Auteurs : L. Wang, Auteur ; A. Birt, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 35 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle géométrique [Termes IGN] Pinophyta [Termes IGN] Pinus taeda [Termes IGN] segmentation Résumé : (Auteur) Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical models and computer algorithms that infer or estimate specific forest metrics. For these outputs to be useful, algorithms must be validated and/or calibrated using a sub-sample of ‘known’ metrics measured using more detailed, reliable methods such as field sampling. In this paper, we describe a novel method for delineating and deriving metrics of individual trees from LiDAR data based on watershed segmentation. Because of the costs involved with collecting both LiDAR data and field samples for validation, we use synthetic LiDAR data to validate and assess the accuracy of our algorithm. This synthetic LiDAR data is generated using a simple geometric model of Loblolly pine (Pinus taeda) trees and a simulation of LiDAR sampling. Our results suggest that point densities greater than 2 and preferably greater than 4 points per m2 are necessary to obtain accurate forest inventory data from Loblolly pine stands. However the results also demonstrate that the detection errors (i.e. the accuracy and biases of the algorithm) are intrinsically related to the structural characteristics of the forest being measured. We argue that experiments with synthetic data are directly useful to forest managers to guide the design of operational forest inventory studies. In addition, we argue that the development of LiDAR simulation models and experiments with the data they generate represents a fundamental and useful approach to designing, improving and exploring the accuracy and efficiency of LiDAR algorithms. Numéro de notice : A2013-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s10707-011-0148-1 Date de publication en ligne : 29/11/2011 En ligne : https://doi.org/10.1007/s10707-011-0148-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32184 [article]

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