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Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)
[article]
Titre : Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory Type de document : Article/Communication Auteurs : Alex Appiah Mensah, Auteur ; Hans Petersson, Auteur ; Jonas Dahlgren, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120605 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] azote
[Termes IGN] changement climatique
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] forêt boréale
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Suède
[Termes IGN] surface terrière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Changes over time in annual basal area growth and mean height for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) over the period, 1983–2020 were studied using sample tree data from temporary plots recorded in the Swedish National Forest Inventory. The annual basal area growth was derived from the last measured full ring on increment cores. Using 20 to 60-year-old dominant trees, the mean height and annual basal area growth were examined as functions of tree, stand and site conditions, and trends were assessed mainly using residual analyses over time. A significant increase in mean height at a given age was found for both species, but the annual basal area growth level remained stable over the 38-year period. Currently, at a given age of 50 annual rings at breast height, the mean heights of pines and spruces increased on average by 10.1% (i.e. ∼2 m), compared to 50 year-old pines and spruces in the 1980s, and the increase was similar in the different regions. The results suggest that trees have become taller and slenderer in Swedish forests. Increasing tree height over time at a given age in Northern Europe has been documented in several reports and many causes have been suggested, such as changed forest management, increasing temperatures and nitrogen deposition. We suggest that elevated CO2 in the air and improved water-use efficiency for the trees might also be strong drivers. Numéro de notice : A2023-005 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120605 Date de publication en ligne : 05/11/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120605 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102008
in Forest ecology and management > vol 527 (January-1 2023) . - n° 120605[article]Tree diversity and identity modulate the growth response of thermophilous deciduous forests to climate warming / Giovanni Jacopetti in Oikos, vol 2023 n° inconnu (2023)
[article]
Titre : Tree diversity and identity modulate the growth response of thermophilous deciduous forests to climate warming Type de document : Article/Communication Auteurs : Giovanni Jacopetti, Auteur ; Federico Selvi, Auteur ; Filippo Bussotti, Auteur ; Martina Pollastrini, Auteur ; Tommaso Jucker, Auteur ; Olivier Bouriaud , Auteur Année de publication : 2023 Projets : FunDivEUROPE / Article en page(s) : n ° e08875 Note générale : bibliographie
The research leading to these results received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant 265171.Langues : Anglais (eng) Descripteur : [Termes IGN] cerne
[Termes IGN] croissance des arbres
[Termes IGN] forêt de feuillus
[Termes IGN] forêt thermophile
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Italie
[Termes IGN] richesse floristique
[Termes IGN] sécheresse
[Termes IGN] température au sol
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Tree diversity and species identity are known to play an important role in modulating forest productivity and its capacity to buffer the effects of climatic events. The FunDivEurope exploratory platform allowed us to analyse this modulating effect in a medium-term time span, after an abrupt rise to a new stable level of the average summer temperature of ca 2°C, in Mediterranean forests in central Italy. This paper aims to answer the following questions: 1) did increasing temperature and drought events affect the growth of thermophilous deciduous forests? 2) Was this effect buffered in mixed stands compared to monocultures? 3) Did co-occurring tree species with different ecological characteristics, from more mesophilous to more xerophilous, have different responses? In 2012 and 2017, wood cores were collected from 659 trees in 36 plots representative of thermophilous deciduous forests. The selected tree species were Castanea sativa, Ostrya carpinifolia, Quercus cerris, Quercus ilex and Quercus petraea. In the sampling plots, they were present in pure stands and mixtures from two to four species. After measuring annual rings on cores, chronologies of basal area increment were built, and inventory data were used to estimate tree growth. Results showed a strong reduction of growth, lasting at least 18 years, after the temperature rise. Tree diversity significantly reduced the growth drop after the sudden and stable rise in summer average temperature. Tree mixture effect on growth stability appeared to be dependent on the tree species present in the mixture. Temperature rise and associated drought events, even without changes in rainfall, are one of the main challenges that European forests will face in the current scenarios of climate change. Tree diversity can buffer the effects of climate change over periods of at least 15 years and should be considered in forest management plans. Numéro de notice : A2023-070 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : archives Univ Florence Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/oik.08875 Date de publication en ligne : 22/12/2022 En ligne : https://doi.org/10.1111/oik.08875 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102324
in Oikos > vol 2023 n° inconnu (2023) . - n ° e08875[article]Tree height-growth trajectory estimation using uni-temporal UAV laser scanning data and deep learning / Stefano Puliti in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)
[article]
Titre : Tree height-growth trajectory estimation using uni-temporal UAV laser scanning data and deep learning Type de document : Article/Communication Auteurs : Stefano Puliti, Auteur ; J. Paul McLean, Auteur ; Nicolas Cattaneo, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 37 - 48 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] Betula pendula
[Termes IGN] croissance des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fraxinus excelsior
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] Norvège
[Termes IGN] semis de pointsRésumé : (auteur) Information on tree height-growth dynamics is essential for optimizing forest management and wood procurement. Although methods to derive information on height-growth information from multi-temporal laser scanning data already exist, there is no method to derive such information from data acquired at a single point in time. Drone laser scanning data (unmanned aerial vehicles, UAV-LS) allows for the efficient collection of very dense point clouds, creating new opportunities to measure tree and branch architecture. In this study, we examine if it is possible to measure the vertical positions of branch whorls, which correspond to nodes, and thus can in turn be used to trace the height growth of individual trees. We propose a method to measure the vertical positions of whorls based on a single-acquisition of UAV-LS data coupled with deep-learning techniques. First, single-tree point clouds were converted into 2D image projections, and a YOLOv5 (you-only-look-once) convolutional neural network was trained to detect whorls based on a sample of manually annotated images. Second, the trained whorl detector was applied to a set of 39 trees that were destructively sampled after the UAV-LS data acquisition. The detected whorls were then used to estimate tree-, plot- and stand-level height-growth trajectories. The results indicated that 70 per cent (i.e. precision) of the measured whorls were correctly detected and that 63 per cent (i.e. recall) of the detected whorls were true whorls. These results translated into an overall root-mean-squared error and Bias of 8 and −5 cm for the estimated mean annual height increment. The method’s performance was consistent throughout the height of the trees and independent of tree size. As a use case, we demonstrate the possibility of developing a height-age curve, such as those that could be used for forecasting site productivity. Overall, this study provides proof of concept for new methods to analyse dense aerial point clouds based on image-based deep-learning techniques and demonstrates the potential for deriving useful analytics for forest management purposes at operationally-relevant spatial-scales. Numéro de notice : A2023-100 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1093/forestry/cpac026 Date de publication en ligne : 05/07/2022 En ligne : https://doi.org/10.1093/forestry/cpac026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102418
in Forestry, an international journal of forest research > vol 96 n° 1 (January 2023) . - pp 37 - 48[article]Tree position estimation from TLS data using hough transform and robust least-squares circle fitting / Maja Michałowska in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)
[article]
Titre : Tree position estimation from TLS data using hough transform and robust least-squares circle fitting Type de document : Article/Communication Auteurs : Maja Michałowska, Auteur ; Jacek Rapinski, Auteur ; Joanna Janicka, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 100863 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] branche (arbre)
[Termes IGN] compensation par moindres carrés
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage du bruit
[Termes IGN] géolocalisation
[Termes IGN] méthode robuste
[Termes IGN] modèle numérique de terrain
[Termes IGN] Pologne
[Termes IGN] semis de points
[Termes IGN] transformation de HoughRésumé : (auteur) Forest management and planning require information regarding the current state of the forest. Remote sensing techniques allow to obtain geospatial data, also for the forestry sector. As one of the remote-sensed technologies datasets, Terrestrial Laser Scanning data is widely used to derive detailed information about tree and forest stand parameters. This article presents the combination of circular Hough transform, denoising procedure, and robust least-square circle fitting method to extract stem positions from Terrestrial Laser Scanning data. In the proposed approach, initial tree stems position was detected with circular Hough transform. Then, obtained results were denoised to exclude most non-tree trunk points and analyze three-dimensional data from laser scanning to find exact circular tree stems with a robust least-square circle fitting method. The developed algorithm is effective in obtaining the trees’ geodetic positions from laser scanning data. The results generated in this study can be used as basics for further automatic determination of tree characteristics, such as tree species, height, or crown range. In this study, 94.8% tree stems delineation was generated with a mean accuracy of 87.2%, 1.64 cm of root mean square error for stem position, and 1.15 cm for tree radius measured at ground level. The process conducted in this research can be used to detect other circle-shaped objects, such as lamps or power towers, for which obtaining dense Terrestrial Laser Scanning data is available. The detected positions of these objects can power the geographic information systems or thematic industry systems, where it is necessary to determine the geodetic object position results from legal regulations. Numéro de notice : A2023-018 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rsase.2022.100863 Date de publication en ligne : 04/11/2022 En ligne : https://doi.org/10.1016/j.rsase.2022.100863 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102183
in Remote Sensing Applications: Society and Environment, RSASE > vol 29 (January 2023) . - n° 100863[article]Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data / Ying Quan in GIScience and remote sensing, vol 60 n° 1 (2023)
[article]
Titre : Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data Type de document : Article/Communication Auteurs : Ying Quan, Auteur ; Mingze Li, Auteur ; Yuanshuo Hao, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 2171706 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] espèce végétale
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] forêt secondaire
[Termes IGN] image captée par drone
[Termes IGN] image hyperspectrale
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] semis de pointsRésumé : (auteur) Recent growth in unmanned aerial vehicle (UAV) technology have promoted the detailed mapping of individual tree species. However, the in-depth mining and comprehending of the significance of features derived from high-resolution UAV data for tree species discrimination remains a difficult task. In this study, a state-of-the-art approach combining UAV-borne light detection and ranging (LiDAR) and hyperspectral was used to classify 11 common tree species in a typical natural secondary forest in Northeast China. First, comprehensive relevant structural and spectral features were extracted. Then, the most valuable feature sets were selected by using a hybrid approach combining correlation-based feature selection with the optimized recursive feature elimination algorithm. The random forest algorithm was used to assess feature importance and perform the classification. Finally, the robustness of features derived from point clouds with different structures and hyperspectral images with different spatial resolutions was tested. Our results showed that the best classification accuracy was obtained by combining LiDAR and hyperspectral data (75.7%) compared to that based on LiDAR (60.0%) and hyperspectral (64.8%) data alone. The mean intensity of single returns and the visible atmospherically resistant index for red-edge band were the most influential LiDAR and hyperspectral derived features, respectively. The selected features were robust in point clouds with a density not lower than 5% (~5 pts/m2) and a resolution not lower than 0.3 m in hyperspectral data. Although canopy surface features were slightly different from original LiDAR features, canopy surface information was also important for tree species classification. This study proved the capabilities of UAV-borne LiDAR and hyperspectral data in natural secondary forest tree species discrimination and the potential for this approach to be transferable to other study areas. Numéro de notice : A2023-194 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1080/15481603.2023.2171706 Date de publication en ligne : 03/02/2023 En ligne : https://doi.org/10.1080/15481603.2023.2171706 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103075
in GIScience and remote sensing > vol 60 n° 1 (2023) . - n° 2171706[article]Using Google Earth Engine to classify unique forest and agroforest classes using a mix of Sentinel 2a spectral data and topographical features: a Sri Lanka case study / W.D.K.V. Nandasena in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkInteractive effects of abiotic factors and biotic agents on Scots pine dieback: A multivariate modeling approach in southeast France / Jean Lemaire in Forest ecology and management, vol 526 (December-15 2022)PermalinkAbove ground biomass estimation from UAV high resolution RGB images and LiDAR data in a pine forest in Southern Italy / Mauro Maesano in iForest, biogeosciences and forestry, vol 15 n° 6 (December 2022)PermalinkAssessment of camera focal length influence on canopy reconstruction quality / Martin Denter in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)PermalinkClimate and ungulate browsing impair regeneration dynamics in spruce-fir-beech forests in the French Alps / Mithila Unkule in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkClimate change-induced background tree mortality is exacerbated towards the warm limits of the species ranges / Adrien Taccoen in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkClimate envelope analyses suggests significant rearrangements in the distribution ranges of Central European tree species / Gàbor Illés in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkComparison of methods for the automatic classification of forest habitat types in the Southern Alps : Application to ecological data from the French national forest inventory / Charlotte Labit in Biodiversity & Conservation, vol 31 n° 13-14 (December 2022)PermalinkDendrometric data from the silvicultural scenarios developed by Office National des Forêts (ONF) in France: a tool for applied research and carbon storage estimates / Salomé Fournier in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkDesiccation does not increase frost resistance of pedunculate oak (Quercus robur L.) seeds / Paweł Chmielarz in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkDiscriminating pure Tamarix species and their putative hybrids using field spectrometer / Solomon G. Tesfamichael in Geocarto international, vol 37 n° 25 ([01/12/2022])PermalinkEffect of climate on cork-ring width and density of Quercus suber L. in Southern Portugal / Augusta Costa in Trees, vol 36 n° 6 (December 2022)PermalinkEstimating 10-m land surface albedo from Sentinel-2 satellite observations using a direct estimation approach with Google Earth Engine / Xingwen Lin in ISPRS Journal of photogrammetry and remote sensing, vol 194 (December 2022)PermalinkForêt amazonienne : de nouveau sous contrôle ? / Laurent Polidori in Géomètre, n° 2208 (décembre 2022)PermalinkHarvested area did not increase abruptly-how advancements in satellite-based mapping led to erroneous conclusions / Johannes Breidenbach in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkIdentification and spatial extent of understory plant species requiring vegetation control to ensure tree regeneration in French forests / Noé Dumas in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkInstance segmentation of standing dead trees in dense forest from aerial imagery using deep learning / Aboubakar Sani-Mohammed in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)PermalinkA novel entropy-based method to quantify forest canopy structural complexity from multiplatform lidar point clouds / Xiaoqiang Liu in Remote sensing of environment, vol 282 (December 2022)PermalinkOffering the appetite for the monitoring of European forests a diversified diet / Jean-Daniel Bontemps in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkPotentials and limitations of NFIs and remote sensing in the assessment of harvest rates: a reply to Breidenbach et al. / Guido Ceccherini in Annals of Forest Science, vol 79 n° 1 (2022)Permalink