Descripteur
Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > botanique générale > arbre (flore) > houppier
houppier |
Documents disponibles dans cette catégorie (76)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) / Langning Huo in Remote sensing of environment, vol 270 (March 2022)
[article]
Titre : Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) Type de document : Article/Communication Auteurs : Langning Huo, Auteur ; Eva Lindberg, Auteur ; Johan Holmgren, Auteur Année de publication : 2022 Article en page(s) : n° 112857 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt boréale
[Termes IGN] hauteur à la base du houppier
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] sous-bois
[Termes IGN] sous-étage
[Termes IGN] strate végétale
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] SuèdeRésumé : (auteur) Obtaining low vegetation data is important in order to quantify the structural characteristics of a forest. Dense three-dimensional (3D) laser scanning data can provide information on the vertical profile of a forest. However, most studies have focused on the dominant and subdominant layers of the forest, while few studies have tried to delineate the low vegetation. To address this issue, we propose a framework for individual tree crown (ITC) segmentation from laser data that focuses on both overstory and understory trees. The framework includes 1) a new algorithm (SSD) for 3D ITC segmentation of dominant trees, by detecting the symmetrical structure of the trees, and 2) removing points of dominant trees and mean shift clustering of the low vegetation. The framework was tested on a boreal forest in Sweden and the performance was compared 1) between plots with different stem density levels, vertical complexities, and tree species composition, and 2) using airborne laser scanning (ALS) data, terrestrial laser scanning (TLS) data, and merged ALS and TLS data (ALS + TLS data). The proposed framework achieved detection rates of 0.87 (ALS + TLS), 0.86 (TLS), and 0.76 (ALS) when validated with field-inventory data (of trees with a diameter at breast height ≥ 4 cm). When validating the estimated number of understory trees by visual interpretation, the framework achieved 19%, 21%, and 39% root-mean-square error values with ALS + TLS, TLS, and ALS data, respectively. These results show that the SSD algorithm can successfully separate laser points of overstory and understory trees, ensuring the detection and segmentation of low vegetation in forest. The proposed framework can be used with both ALS and TLS data, and achieve ITC segmentation for forests with various structural attributes. The results also illustrate the potential of using ALS data to delineate low vegetation. Numéro de notice : A2022-127 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112857 Date de publication en ligne : 03/01/2022 En ligne : https://doi.org/10.1016/j.rse.2021.112857 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99707
in Remote sensing of environment > vol 270 (March 2022) . - n° 112857[article]A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway / Christian Kuehne in Silva fennica, vol 56 n° 1 (January 2022)
[article]
Titre : A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway Type de document : Article/Communication Auteurs : Christian Kuehne, Auteur ; J. Paul McLean, Auteur ; Kobra Maleki, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] branche (arbre)
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] forêt équienne
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] modèle de croissance végétale
[Termes IGN] Norvège
[Termes IGN] Pinus sylvestris
[Termes IGN] rendement
[Termes IGN] surface terrière
[Termes IGN] volume en bois
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment. Numéro de notice : A2022-171 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.10627 Date de publication en ligne : 26/01/2022 En ligne : https://doi.org/10.14214/sf.10627 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99806
in Silva fennica > vol 56 n° 1 (January 2022) . - n° 1[article]Tree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines / Maria Caballol in Forest ecology and management, vol 505 (February-1 2022)
[article]
Titre : Tree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines Type de document : Article/Communication Auteurs : Maria Caballol, Auteur ; Maia Ridley, Auteur ; Michele Colangelo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 119935 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] dendrochronologie
[Termes IGN] dépérissement
[Termes IGN] endophyte
[Termes IGN] épidémie
[Termes IGN] Espagne
[Termes IGN] grêle
[Termes IGN] houppier
[Termes IGN] maladie cryptogamique
[Termes IGN] mortalité
[Termes IGN] Pinus halepensis
[Termes IGN] Pinus nigra
[Termes IGN] Pinus pinea
[Termes IGN] Pinus sylvestris
[Termes IGN] santé des forêts
[Termes IGN] sécheresse
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Diplodia shoot blight is an emergent forest disease in Europe caused by Diplodia sapinea. The short-term impacts of the pathogen on tree physiology are well known, but its capacity to cause mortality has been poorly documented. We compared the survival of four pine species affected by Diplodia shoot blight following a hailstorm: Pinus sylvestris, P. nigra, P. pinea and P. halepensis. In the case of P. sylvestris, survival in the hail-affected sites was compared with survival in other sites affected by Diplodia shoot blight with no hailstorm records. Mortality and crown condition were recorded over two years. Dendrochronological analyses were conducted to assess growth responses to drought and to test the influence of radial growth before the outbreak of Diplodia shoot blight on survival. The endophytic community, as well as the abundance of D. sapinea, was quantified by metabarcoding and qPCR respectively, and were correlated with crown damage. Crown damage was the best predictor of mortality across species. Pinus sylvestris experienced a much higher rate of mortality than P. nigra, P. pinea and P. halepensis. Two years after the outbreak, P. halepensis was the only species that could recover crown condition. Mortality was found to be unrelated to radial growth prior the outbreak. Drought responses did not correlate with mortality differences across pine species or sites. In the case of P. sylvestris, mortality was initially higher amongst diseased trees in areas affected by hailstorms than in sites not affected by hailstorms, however it tended to equalise after two years. Amongst P. sylvestris trees, crown damage correlated with a higher abundance of the pathogen. Signs of competition amongst endophytes were observed between non-defoliated and defoliated Scots pine trees following hailstorms. Our study shows that D. sapinea can cause a significant mortality to P. sylvestris. The legacy effects of crown damage can last for at least two years after an outbreak. During this time, crown damage is a good predictor of survival, and can help managers decide which trees remove after an outbreak. Numéro de notice : A2022-042 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119935 Date de publication en ligne : 23/12/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119935 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99400
in Forest ecology and management > vol 505 (February-1 2022) . - n° 119935[article]Detection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks / Stefan Reder in Remote sensing, vol 14 n° 1 (January-1 2022)
[article]
Titre : Detection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks Type de document : Article/Communication Auteurs : Stefan Reder, Auteur ; J.P. Mund, Auteur ; Nicole Albert, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] branche (arbre)
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] dommage forestier causé par facteurs naturels
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] image captée par drone
[Termes IGN] orthophotoplan numérique
[Termes IGN] segmentation sémantique
[Termes IGN] tempête
[Termes IGN] troncRésumé : (auteur) The increasing number of severe storm events is threatening European forests. Besides the primary damages directly caused by storms, there are secondary damages such as bark beetle outbreaks and tertiary damages due to negative effects on the market. These subsequent damages can be minimized if a detailed overview of the affected area and the amount of damaged wood can be obtained quickly and included in the planning of clearance measures. The present work utilizes UAV-orthophotos and an adaptation of the U-Net architecture for the semantic segmentation and localization of windthrown stems. The network was pre-trained with generic datasets, randomly combining stems and background samples in a copy–paste augmentation, and afterwards trained with a specific dataset of a particular windthrow. The models pre-trained with generic datasets containing 10, 50 and 100 augmentations per annotated windthrown stems achieved F1-scores of 73.9% (S1Mod10), 74.3% (S1Mod50) and 75.6% (S1Mod100), outperforming the baseline model (F1-score 72.6%), which was not pre-trained. These results emphasize the applicability of the method to correctly identify windthrown trees and suggest the collection of training samples from other tree species and windthrow areas to improve the ability to generalize. Further enhancements of the network architecture are considered to improve the classification performance and to minimize the calculative costs. Numéro de notice : A2022-082 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14010075 En ligne : https://doi.org/10.3390/rs14010075 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99476
in Remote sensing > vol 14 n° 1 (January-1 2022) . - n° 75[article]Early detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany / Kathrin Einzmann in Remote sensing of environment, vol 266 (December 2021)
[article]
Titre : Early detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany Type de document : Article/Communication Auteurs : Kathrin Einzmann, Auteur ; Clement Atzberger, Auteur ; Nicole Pinnel, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112676 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bavière (Allemagne)
[Termes IGN] changement climatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] dépérissement
[Termes IGN] détection de changement
[Termes IGN] houppier
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] insecte nuisible
[Termes IGN] phénomène climatique extrême
[Termes IGN] Picea abies
[Termes IGN] réflectance spectrale
[Termes IGN] série temporelle
[Termes IGN] stress hydriqueRésumé : (auteur) Vitality loss of trees caused by extreme weather conditions, drought stress or insect infestations, are expected to increase with ongoing climate change. The detection of vitality loss at an early stage is thus of vital importance for forestry and forest management to minimize ecological and economical damage. Remote sensing instruments are able to detect changes over large areas down to the level of individual trees. The scope of our study is to investigate whether it is possible to detect stress-related spectral changes at an early stage using hyperspectral sensors. For this purpose, two Norway spruce (Picea abies) forest stands, both different in age and maintenance, were monitored in the field over two vegetation periods. In parallel, time series of airborne hyperspectral remote sensing data were acquired. For each stand 70 trees were artificially stressed (ring-barked) and 70 trees were used as control trees. The data collected in south-eastern Germany consists of measurements at multiple times and at different scales: (1) crown conditions were visually assessed in the field (2) needle reflectance spectra were acquired in the laboratory using a FieldSpec spectrometer, and (3) hyperspectral airborne data (HySpex) were flown at 0.5 m spatial resolution. We aimed for a simultaneous data acquisition at the three levels. This unique data set was investigated whether any feature can be discriminated to detect vitality loss in trees at an early stage. Several spectral transformations were applied to the needle and tree crown spectra, such as spectral derivatives, vegetation indices and angle indices. All features were examined for their separability (ring-barked vs. control trees) with the Random Forest (RF) classification algorithm. As result, the younger, well maintained forest stand only showed minor changes over the 2-year period, whereas changes in the older forest stand were observable both in the needle and in the hyperspectral tree crown spectra, respectively. These changes could even be detected before changes were visible by field observations. The tree spectral reactions to ring-barking were first noticeable 11 months after ring-barking and 6 weeks before they were visible by field inspection. The most discriminative features for separating the two groups were the reflectance spectra and the spectral derivatives, over the VIs or angle indices. The tree crown spectra of the two groups could be separated by the RF classifier with a 79% overall accuracy at the beginning of the second vegetation period and 1 month later with 92% overall accuracy with high kappa index. The results clearly demonstrate the great potential of hyperspectral remote sensing in detecting early vitality changes of stressed trees. Numéro de notice : A2021-921 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112676 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112676 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99274
in Remote sensing of environment > vol 266 (December 2021) . - n° 112676[article]Radiative transfer modeling in structurally complex stands: towards a better understanding of parametrization / Frédéric André in Annals of Forest Science, vol 78 n° 4 (December 2021)PermalinkAutomatic tuning of segmentation parameters for tree crown delineation with VHR imagery / Camile Sothe in Geocarto international, vol 36 n° 19 ([01/11/2021])PermalinkAutomated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN) / Zhenbang Hao in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkDetecting structural changes induced by Heterobasidion root rot on Scots pines using terrestrial laser scanning / Timo P Pitkänen in Forest ecology and management, vol 492 (July-15 2021)PermalinkImproving tree biomass models through crown ratio patterns and incomplete data sources / Maria Menéndez-Miguélez in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkIndividual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)PermalinkPredicting tree species based on the geometry and density of aerial laser scanning point cloud of treetops / Nina Kranjec in Geodetski vestnik, vol 65 n° 2 (June - August 2021)PermalinkMixture effect on radial stem and shoot growth differs and varies with temperature / Maude Toïgo in Forest ecology and management, vol 488 (May-15 2021)PermalinkTowards silviculture guidelines to produce large-sized silver birch (betula pendula roth) logs in Western Europe / Héloïse Dubois in Forests, vol 12 n° 5 (May 2021)PermalinkAn iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects / Linyuan Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)Permalink