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Modelling bark volume for six commercially important tree species in France: assessment of models and application at regional scale / Rodolphe Bauer in Annals of Forest Science, vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science > vol 78 n° 4 (December 2021) . - n° 104 Titre : Modelling bark volume for six commercially important tree species in France: assessment of models and application at regional scale Type de document : Article/Communication Auteurs : Rodolphe Bauer, Auteur ; Antoine Billard, Auteur ; Frédéric Mothe, Auteur ; Fleur Longuetaud, Auteur ; Mojtaba Houballah, Auteur ; Alain Bouvet, Auteur ; Henri E. Cuny , Auteur ; Antoine Colin , Auteur ; Francis Colin, Auteur Année de publication : 2021 Projets : ARBRE / AgroParisTech, EMERGE / Deleuze, Christine Article en page(s) : n° 104 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] biomasse forestière [Termes IGN] Bourgogne Franche-Comté (région 2016) [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] écorce [Termes IGN] Fagus sylvatica [Termes IGN] Grand Est (région 2016) [Termes IGN] inventaire forestier national (données France) [Termes IGN] modèle statistique [Termes IGN] Picea abies [Termes IGN] Pseudotsuga menziesii [Termes IGN] Quercus pedunculata [Termes IGN] Quercus sessiliflora [Termes IGN] volume (grandeur) [Vedettes matières IGN] Economie forestière Résumé : (auteur) Key message : A set of models of bark thickness at breast height and bark volume are now available for six species in France. A common model suitable for predicting bark volume was proposed for all species. A small but significant altitude effect on bark thickness at breast height was detected for three species. Context : The growing demand for wood energy and bio-molecules requires a thorough evaluation of forest biomass, particularly bark. Aims : The objective of this study is to have statistical models of bark volumes for the six main forest species present in North-Eastern France and to be able to estimate regional bark biomasses and quantities of chemical extractives at regional scale. Methods : A large databank gathering bark thickness measured at different heights in France was used for selecting literature or new alternative models of tree bark volume. These models were applied to the available forest inventory data from North-Eastern France to estimate the regional bark volume. Secondly, by multiplying these volumes by basic density data and extractive content recently obtained, bark biomasses and extractives quantities were deduced. Results : The first results consist in a set of species-specific models of bark thickness at breast height with R2 around 0.70 and a relative RMSE around 30% which is an improvement of 0.1 for R2 and of 1–2% for relative RMSE depending on the species compared to the best models from the literature. The second results consist in a set of species-specific models of tree bark volumes with R2 of 0.90 and a relative RMSE which varies between 22% when bark thickness at breast height is included and 40% when it is predicted. A significant relationship between bark thickness at breast height and altitude was also observed. The bark resources of Grand Est and Bourgogne-Franche-Comté regions were estimated at 558 000 m3/year and 611 000 m3/year respectively representing between 5.5% and 15% of the stem volume depending on the species. The propagation of the measurement error of bark gauge was estimated at 5% for model of bark thickness at breast height and 24% for bark volume model. Conclusion : These results constitute an important contribution for a better knowledge of the bark resource at a regional scale and may help to optimise bark valuation by the forest-wood sector. Numéro de notice : A2021-909 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01096-7 Date de publication en ligne : 02/01/2022 En ligne : https://doi.org/10.1007/s13595-021-01096-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99458 [article]

An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data / Van-Tho Nguyen in Annals of Forest Science, vol 78 n° 2 (June 2021)  

Public [article]  inAnnals of Forest Science > vol 78 n° 2 (June 2021) . - Article 32 Titre : An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data Type de document : Article/Communication Auteurs : Van-Tho Nguyen, Auteur ; Thiéry Constant, Auteur ; Francis Colin, Auteur Année de publication : 2021 Article en page(s) : Article 32 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] détection d'anomalie [Termes IGN] données de terrain [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écorce [Termes IGN] Fagus sylvatica [Termes IGN] qualité du bois [Termes IGN] Quercus sessiliflora [Termes IGN] segmentation d'image [Termes IGN] télémétrie laser terrestre [Termes IGN] tronc Résumé : (Auteur) We designed a novel method allowing to automatically detect and measure defects on the surface of trunks including branches, branch scars, and epicormics from terrestrial LiDAR data by using only high-density 3D information. We could automatically detect and measure the defects with a diameter as small as 0.5 cm on either oak (Quercus petraea (Matt.) Liebl.) or beech (Fagus sylvatica L.) trees that display either rough or smooth bark. Context : Ground-based light detection and ranging (LiDAR) technology describes standing trees with a high level of detail. This provides an opportunity to assess standing tree quality and to use this information in forest inventory. Assuming the availability of a very high level of detail, we could extract information about the surface defects, mainly inherited from past ramification and having a strong impact on wood quality. Aims : Within the general framework of the development of a computing method able to detect, identify, and quantify the defects on the trunk surface described from 3D data produced by a terrestrial LiDAR, this study focuses on the relevance of the whole process for two tree species with contrasted bark roughness (Quercus petraea (Matt.) Liebl. and Fagus sylvatica L.) in terms of detection, identification of the defects, and comparison with measurements performed manually on the bark surface. Methods : First, a segmentation algorithm detected singularities on the trunk surface. Next, a Random Forests machine learning algorithm identified the most probable defect type and allowed the elimination of false detections. Finally, we estimated the position, horizontal, and vertical dimensions of each defect from 3D data, and we compared them to those observed directly on the trunk by an operator. Results : The defects were detected and classified with a high accuracy with an average F1 score (harmonic mean of precision and recall) of 0.74. There were differences in computed and observed defect areas, but a much closer agreement for the number of defects. Conclusion : The information about the defects present on the trunk surface measured from terrestrial LiDAR data can be used in an automated procedure for grading standing trees or roundwoods. Numéro de notice : A2021-326 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01022-3 Date de publication en ligne : 01/04/2021 En ligne : https://doi.org/10.1007/s13595-020-01022-3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97484 [article]

Improving aboveground biomass estimates by taking into account density variations between tree components / Antoine Billard in Annals of Forest Science, vol 77 n° 4 (December 2020)  

Public [article]  inAnnals of Forest Science > vol 77 n° 4 (December 2020) . - n° 103 Titre : Improving aboveground biomass estimates by taking into account density variations between tree components Type de document : Article/Communication Auteurs : Antoine Billard, Auteur ; Rodolphe Bauer, Auteur ; Frédéric Mothe, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allométrie [Termes IGN] base de données forestières [Termes IGN] biomasse aérienne [Termes IGN] bois de chauffage [Termes IGN] branche (arbre) [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] écorce [Termes IGN] hauteur des arbres [Termes IGN] résineux [Termes IGN] tomographie radar [Termes IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message: Strong density differences were observed between stem wood at 1.30 m and other tree components (stem wood, stem bark, knots, branch stumps and branches). The difference, up to 40% depending on the component, should be taken into account when estimating the biomass available for industrial uses, mainly fuelwood and wood for chemistry. Context: Basic density is a major variable in the calculation of tree biomass. However, it is usually measured on stem wood only and at breast height. Aims: The objectives of this study were to compare basic density of stem wood at 1.30 m with other tree components and assess the impact of differences on biomass. Methods: Three softwood species were studied: Abies alba Mill., Picea abies (L.) H. Karst., Pseudotsuga menziesii (Mirb.) Franco. X-Ray computed tomography was used to measure density. Results: Large differences were observed between components. Basic density of components was little influenced by tree size and stand density. Overall, bark, knot and branch biomasses were highly underestimated by using basic density measured at 1.30 m. Conclusion: Using available wood density databases mainly based on breast height measurements would lead to important biases (up to more than 40%) on biomass estimates for some tree components. Further work is necessary to complete available databases. Numéro de notice : A2020-714 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-020-00999-1 Date de publication en ligne : 26/10/2020 En ligne : https://doi.org/10.1007/s13595-020-00999-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96282 [article]

Entre l’écorce et l’arbre / Jean Hamann in Le Fil : Le journal de la communauté universitaire, vol 53 n° 25 ([19/04/2018])  

Public [article]  inLe Fil : Le journal de la communauté universitaire > vol 53 n° 25 [19/04/2018] Titre : Entre l’écorce et l’arbre Type de document : Article/Communication Auteurs : Jean Hamann, Auteur Année de publication : 2018 Langues : Français (fre) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] drone [Termes IGN] écorce [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] réseau neuronal convolutif [Vedettes matières IGN] Inventaire forestier Résumé : (éditeur) Des chercheurs (Mathieu Carpentier et Luca Gabriel Serban) développent un système intelligent pour identifier les espèces d'arbres à partir d'images de leur écorce. Numéro de notice : A2018-211 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : sans En ligne : https://www.lefil.ulaval.ca/entre-lecorce-larbre/ Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89973 [article]

The measurement of wood shrinkage and bark thickness on increment cores / Baptiste Kerfriden (2018)    

Public Titre : The measurement of wood shrinkage and bark thickness on increment cores Type de document : Article/Communication Auteurs : Baptiste Kerfriden , Auteur ; Lucile Savagner, Auteur ; Kévin Dupont-Marin, Auteur ; Jean-Michel Leban , Auteur Editeur : Paris [France] : Institut national de recherche pour l’agriculture, l’alimentation et l’environnement INRAE (2020-) Année de publication : 2018 Conférence : Hardwood 2018, 8th hardwood conference, New aspects of hardwood utilization - from science to technology 25/10/2018 26/10/2018 Sopron Hongrie Langues : Anglais (eng) Descripteur : [Termes IGN] anatomie du bois [Termes IGN] bois sur pied [Termes IGN] écorce [Termes IGN] épaisseur [Termes IGN] phytobiologie [Vedettes matières IGN] Botanique Numéro de notice : C2018-127 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Poster nature-HAL : Poster-avec-CL DOI : sans En ligne : https://hal.inrae.fr/hal-02786020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100049

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Angular reflectance of leaves with a dual-wavelength terrestrial lidar and its implications for leaf-bark separation and leaf moisture estimation / Steven Hancock in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)  

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La vie secrète des arbres / Peter Wohlleben (2017)

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A novel computer-aided tree species identification method based on burst wind segmentation of 3D bark textures / Alice Ahlem Othmani in Machine Vision and Applications, vol 27 n° 5 (July 2016)  

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