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3D reconstruction of internal wood decay using photogrammetry and sonic tomography / Junjie Zhang in Photogrammetric record, vol 35 n° 171 (September 2020)  

Public [article]  inPhotogrammetric record > vol 35 n° 171 (September 2020) . - pp 357-374 Titre : 3D reconstruction of internal wood decay using photogrammetry and sonic tomography Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; Kourosh Khoshelham, Auteur Année de publication : 2020 Article en page(s) : pp 357-374 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] dépérissement [Termes IGN] hauteur des arbres [Termes IGN] interpolation spatiale [Termes IGN] onde acoustique [Termes IGN] qualité du bois [Termes IGN] reconstruction 3D [Termes IGN] temps de vol [Termes IGN] tomographie [Termes IGN] tronc [Termes IGN] visualisation 3D Résumé : (Auteur) Knowledge of deteriorations within tree trunks is critical for arborists to conduct individual tree health assessments. Sonic tree tomography, a non‐destructive technique using sound waves, has been widely used to estimate the size and shape of internal decay based on sound wave velocity variations. However, it has commonly been applied to 2D horizontal or vertical cross sections and its accuracy is questionable due to the poor approximation of the shape of the cross section. This paper proposes an integration of close‐range photogrammetry and sonic tomography to enable accurate reconstruction of the exterior and interior of the tree trunk in 3D. The internal wood quality is represented by the spatially interpolated sound wave velocities, using the time of flight of the sound waves and the coordinates of the acoustic sensors obtained from the photogrammetric model. Experimental results show that the proposed approach provides a realistic 3D visualisation of the size, shape and location of the internal deteriorations. Numéro de notice : A2020-436 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12328 Date de publication en ligne : 06/08/2020 En ligne : https://doi.org/10.1111/phor.12328 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95842 [article]

A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada / Junjie Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 98 (December 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 98 (December 2014) . - pp 44 - 57 Titre : A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; Gunho Sohn, Auteur ; Mathieu Brédif , Auteur Année de publication : 2014 Article en page(s) : pp 44 - 57 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] détection d'objet [Termes IGN] hauteur des arbres [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle stochastique [Termes IGN] Pinophyta [Termes IGN] traitement d'image Résumé : (Auteur) This study presents a hybrid framework for single tree detection from airborne laser scanning (ALS) data by integrating low-level image processing techniques into a high-level probabilistic framework. The proposed approach modeled tree crowns in a forest plot as a configuration of circular objects. We took advantage of low-level image processing techniques to generate candidate configurations from the canopy height model (CHM): the treetop positions were sampled within the over-extracted local maxima via local maxima filtering, and the crown sizes were derived from marker-controlled watershed segmentation using corresponding treetops as markers. The configuration containing the best possible set of detected tree objects was estimated by a global optimization solver. To achieve this, we introduced a Gibbs energy, which contains a data term that judges the fitness of the objects with respect to the data, and a prior term that prevents severe overlapping between tree crowns on the configuration space. The energy was then embedded into a Markov Chain Monte Carlo (MCMC) dynamics coupled with a simulated annealing to find its global minimum. In this research, we also proposed a Monte Carlo-based sampling method for parameter estimation. We tested the method on a temperate mature coniferous forest in Ontario, Canada and also on simulated coniferous forest plots with different degrees of crown overlap. The experimental results showed the effectiveness of our proposed method, which was capable of reducing the commission errors produced by local maxima filtering, thus increasing the overall detection accuracy by approximately 10% on all of the datasets. Numéro de notice : A2014-631 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.007 Date de publication en ligne : 20/10/2014 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75047 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2014121	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Single tree detection from airborne laser scanning data using a marked point process based method / Junjie Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W1 (May 2013)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W1 (May 2013) . - pp 41 - 46 Titre : Single tree detection from airborne laser scanning data using a marked point process based method Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; Gunho Sohn, Auteur ; Mathieu Brédif , Auteur Année de publication : 2013 Conférence : ISPRS VCM 2013, ISPRS Workshop on 3D Virtual City Modeling 28/05/2013 25/05/2013 Regina Saskatchewan - Canada OA ISPRS Annals Article en page(s) : pp 41 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme du gradient [Termes IGN] arbre (flore) [Termes IGN] détection d'objet [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] enthalpie libre [Termes IGN] forêt [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] placette d'échantillonnage [Termes IGN] programmation par contraintes [Termes IGN] reconstruction d'objet Mots-clés libres : Single tree detection  marked point process  segmentation Résumé : (auteur) Tree detection and reconstruction is of great interest in large-scale city modelling. In this paper, we present a marked point process model to detect single trees from airborne laser scanning (ALS) data. We consider single trees in ALS recovered canopy height model (CHM) as a realization of point process of circles. Unlike traditional marked point process, we sample the model in a constraint configuration space by making use of image process techniques. A Gibbs energy is defined on the model, containing a data term which judge the fitness of the model with respect to the data, and prior term which incorporate the prior knowledge of object layouts. We search the optimal configuration through a steepest gradient descent algorithm. The presented hybrid framework was test on three forest plots and experiments show the effectiveness of the proposed method. Numéro de notice : A2013-821 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W1-41-2013 Date de publication en ligne : 16/05/2013 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W1-41-2013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80995 [article]

Full waveform-based analysis for forest type information derivation from large footprint spaceborne lidar data / Junjie Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 3 (March 2011)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 3 (March 2011) . - pp 281 - 290 Titre : Full waveform-based analysis for forest type information derivation from large footprint spaceborne lidar data Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; A. De Gier, Auteur ; Y. Xing, Auteur ; Gunho Sohn, Auteur Année de publication : 2011 Conférence : SilviLaser 2010, 10th International Conference on LiDAR Applications for Assessing Forest Ecosystems 14/09/2010 17/09/2010 Fribourg Allemagne OA ISPRS Annals Article en page(s) : pp 281 - 290 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] capteur spatial [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] couvert forestier [Termes IGN] décomposition de Gauss [Termes IGN] données lidar [Termes IGN] feuillu [Termes IGN] lidar à retour d'onde complète [Termes IGN] Pinophyta [Termes IGN] signal laser Résumé : (Auteur) This study developed a new method to derive forest type information from large-footprint lidar data based on full waveform analysis. For this purpose, the raw waveform was decomposed into Gaussian components, and canopy return and ground return of the waveforms were separated. Two types of metrics hypothesized to have relationship with forest types were derived from the canopy return part of the waveform. The first type of metrics is quantile-based metrics reflecting the vertical distribution of canopy return energy, and the second type is statistical characteristics of the Gaussian components of canopy return part. Support Vector Machine classification was applied to different combinations of the metrics to find their relationship with different forest types. The results showed that the second type of metrics, indicating the canopy stratum characteristics, showed great promise in separating broad-leaved and needle-leaved forests with the accuracy ranging from 88.68 percent to 90.57 percent and Kappa statistic from 0.7406 to 0.7868. Numéro de notice : A2011-081 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.77.3.281 En ligne : https://doi.org/10.14358/PERS.77.3.281 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30862 [article]