Centre dedocumentation
scientifique

Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data / Joris Ravaglia in Forests, vol 10 n° 7 (July 2019)  

Public [article]  inForests > vol 10 n° 7 (July 2019) . - 19 p. Titre : Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data Type de document : Article/Communication Auteurs : Joris Ravaglia, Auteur ; Richard A. Fournier, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur ; Jean-François Côté, Auteur ; Alexandre Piboule, Auteur ; Ulysse Rémillard, Auteur Année de publication : 2019 Projets : ARBRE / Article en page(s) : 19 p. Note générale : bibliographie Cédric Vega is supported by a public grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Canada [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] France (administrative) [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] transformation de Hough [Termes descripteurs IGN] volume en bois Résumé : (auteur) Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during forest inventories. Various specialized algorithms have been developed to provide automatic and objective estimates of forest attributes from point clouds. The STEP (Snakes for Tuboid Extraction from Point cloud) algorithm was developed to estimate both stem diameter at breast height and stem diameters along the bole length. Here, we evaluate the accuracy of this algorithm and compare its performance with two other state-of-the-art algorithms that were designed for the same purpose (i.e., the CompuTree and SimpleTree algorithms). We tested each algorithm against point clouds that incorporated various degrees of noise and occlusion. We applied these algorithms to three contrasting test sites: (1) simulated scenes of coniferous stands in Newfoundland (Canada), (2) test sites of deciduous stands in Phalsbourg (France), and (3) coniferous plantations in Quebec, Canada. In most cases, the STEP algorithm predicted diameter at breast height with higher R2 and lower RMSE than the other two algorithms. The STEP algorithm also achieved greater accuracy when estimating stem diameter in occluded and noisy point clouds, with mean errors in the range of 1.1 cm to 2.28 cm. The CompuTree and SimpleTree algorithms respectively produced errors in the range of 2.62 cm to 6.1 cm and 1.03 cm to 3.34 cm, respectively. Unlike CompuTree or SimpleTree, the STEP algorithm was not able to estimate trunk diameter in the uppermost portions of the trees. Our results show that the STEP algorithm is more adapted to extract DBH and stem diameter automatically from occluded and noisy point clouds. Our study also highlights that SimpleTree and CompuTree require data filtering and results corrections. Conversely, none of these procedures were applied for the implementation of the STEP algorithm. Numéro de notice : A2019-337 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f10070599 date de publication en ligne : 18/07/2019 En ligne : https://doi.org/10.3390/f10070599 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93367 [article]

Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF / Jules Morel in Computers and graphics, vol 74 (August 2018)  

Public [article]  inComputers and graphics > vol 74 (August 2018) . - pp 44 - 55 Titre : Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF Type de document : Article/Communication Auteurs : Jules Morel, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur Année de publication : 2018 Projets : DIABOLO / Packalen, Tuula Article en page(s) : pp 44 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] approximation [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] équation de Poisson [Termes descripteurs IGN] fonction de base radiale [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] reconstruction d'objet Résumé : (auteur) This paper introduces a novel surface reconstruction method based on unorganized point clouds, which focuses on offering complete and closed mesh models of partially sampled object surfaces. To accomplish this task, our approach builds upon a known a priori model that coarsely describes the scanned object to guide the modeling of the shape based on heavily occluded point clouds. In the region of space visible to the scanner, we retrieve the surface by following the resolution of a Poisson problem: the surface is modeled as the zero level-set of an implicit function whose gradient is the closest to the vector field induced by the 3D sample normals. In the occluded region of space, we consider the a priori model as a sufficiently accurate descriptor of the shape. Both models, which are expressed in the same basis of compactly supported radial functions to ensure computation and memory efficiency, are then blended to obtain a closed model of the scanned object. Our method is finally tested on traditional testing datasets to assess its accuracy and on simulated terrestrial LiDAR scanning (TLS) point clouds of trees to assess its ability to handle complex shapes with occlusions. Numéro de notice : A2018-530 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cag.2018.05.004 date de publication en ligne : 17/05/2018 En ligne : https://doi.org/10.1016/j.cag.2018.05.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91400 [article]

Terrain model reconstruction from terrestrial LiDAR data using radial basis functions / Jules Morel in IEEE Computer graphics and applications, vol 37 n° 5 ([01/09/2017])  

Public [article]  inIEEE Computer graphics and applications > vol 37 n° 5 [01/09/2017] . - pp 72 - 84 Titre : Terrain model reconstruction from terrestrial LiDAR data using radial basis functions Type de document : Article/Communication Auteurs : Jules Morel, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur Année de publication : 2017 Article en page(s) : pp 72 - 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] fonction de base radiale [Termes descripteurs IGN] modèle numérique de terrain Résumé : (auteur) The presence of vegetation and the terrain topography itself generate strong occlusions causing large gaps in terrestrial laser scanning (TLS) data at the ground level as well as a risk of integrating above-ground objects. This article introduces a surface-approximation algorithm dedicated to extracting digital terrain models (DTMs) from terrestrial TLS data acquired in forest areas. The proposed method is based on the combination of a quadtree subdivision of space guided by the local density and distribution of data together with a surface modeling via radial basis functions, which are used as partitions of unity for merging local quadratic approximating patches. Numéro de notice : A2017-881 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/MCG.2017.3621225 date de publication en ligne : 20/09/2017 En ligne : https://doi.org/10.1109/MCG.2017.3621225 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91402 [article]

Computation of tree volume from terrestrial LiDAR data / Jules Morel (2015) 

Public contenu dans Proceedings of SilviLaser 2015, 14th conference on Lidar Applications for Assessing and Managing Forest Ecosystems, September 28-30, 2015 - La Grande Motte, France / Sylvie Durrieu (2015)     Titre : Computation of tree volume from terrestrial LiDAR data Type de document : Article/Communication Auteurs : Jules Morel, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur Congrès : Silvilaser 2015, 14th conference on Lidar Applications for Assessing and Managing Forest Ecosystems (28 - 30 septembre 2015; La Grande Motte, France) , Auteur Editeur : Antony : Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture IRSTEA Année de publication : 2015 Importance : pp 308 - 310 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] distribution de Poisson [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] fonction de base radiale [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs IGN] reconstruction d'objet [Termes descripteurs IGN] volume en bois Résumé : (auteur) This paper introduces a new method for the detailed estimation of volumes of individual trees from terrestrial laser scanner data. This method is based on adapted compactly supported radial basis function models together with a deformable models approach. Numéro de notice : C2015-043 Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83731

Documents numériques

en open access Computation of tree volume Adobe Acrobat PDF

Forest carbon assessment from LiDAR 3D point cloud analysis / Alexandra Bac (2015)

Public Titre : Forest carbon assessment from LiDAR 3D point cloud analysis Type de document : Article/Communication Auteurs : Alexandra Bac, Auteur ; Jules Morel, Auteur ; Cédric Vega , Auteur Congrès : RFCC 2015, Regional Forum on Climate Change (1 - 3 juillet 2015; Bangkok, Thaïlande), Commanditaire Editeur : [s.l.] : [s.n.] Année de publication : 2015 Langues : Anglais (eng) Numéro de notice : C2015-044 Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93468

Reconstruction of trees with cylindrical quadrics and radial basis functions / Jules Morel (2015)

Permalink