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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 n° 1 (1 January 2023)  

Public [article]  inForest ecology and management > vol 527 n° 1 (1 January 2023) . - n° 120605 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 forestier Résumé : (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 [article]

Age-independent diameter increment models for mixed mountain forests / Albert Ciceu in European Journal of Forest Research, vol 141 n° 5 (October 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 5 (October 2022) . - pp 781 - 800 Titre : Age-independent diameter increment models for mixed mountain forests Type de document : Article/Communication Auteurs : Albert Ciceu, Auteur ; Karol Bronisz, Auteur ; Juan Garcia-Duro, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 781 - 800 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] échantillonnage [Termes IGN] Fagus sylvatica [Termes IGN] forêt alpestre [Termes IGN] forêt inéquienne [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] Roumanie [Vedettes matières IGN] Foresterie Résumé : (auteur) Mixed mountain forests with an uneven-aged structure are characterized by a high tree-growth variability making traditional age-dependent growth models inapplicable. Estimating site productivity is yet another impediment for modelling tree growth in such forests. Uneven-aged mixed-stand forests are known for their high resilience, resistance and productivity, and are being promoted as a suitable alternative to even-aged, pure plantations for climate change adaptation and mitigation. However, their growth must be accurately measured and predicted, but diameter at the breast height (dbh) increment models specifically designed for uneven-aged mixed mountain forests are still rare. Using permanent sampling network data and 465 increment cores, we built two age-independent dbh increment (id) models for the main species of the study area, namely Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.). Mixed effects models and the algebraic difference approach were employed to develop id models based on empirical and commonly used theoretical growth functions. A past growth index was further developed and introduced in the model in order to explain the id variability. Several mixed effects calibration strategies were assessed in order to obtain the most accurate localized curve for new plots. Tree size, competition and biogeoclimatic variables were found to explain the id through the empirical growth function, while the growth index significantly improved the theoretical growth function for Norway spruce. The optimization of the calibration strategy for the mixed effects modelling framework enables the growth index implementation in forest practice as an accurate method for estimating site productivity. The accuracy of the two id models was similar: the root mean squared error of the empirical growth function varied between 0.940 and 1.042 cm for spruce, beech and fir, while the root mean squared error obtained through the theoretical growth function for spruce only was 1.105 cm. The basal area increment prediction at the plot level based on the theoretical growth function reached a root mean squared error of 0.043 m2 while using the empirical growth function the root mean squared error is 0.047 m2. The high accuracy obtained using age-independent models underlines their suitability for predicting growth in mixed uneven-aged forests. The developed models can be easily integrated into forest practice to accurately obtain id estimates. Numéro de notice : A2022-758 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-022-01473-5 Date de publication en ligne : 13/08/2022 En ligne : https://doi.org/10.1007/s10342-022-01473-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101767 [article]

Benchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest / Daniel Kükenbrink in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 113 (September 2022) . - n° 102999 Titre : Benchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest Type de document : Article/Communication Auteurs : Daniel Kükenbrink, Auteur ; Mauro Marty, Auteur ; Ruedi Bösch, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102999 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] caméra à bas coût [Termes IGN] cartographie et localisation simultanées [Termes IGN] détection d'arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt tempérée [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lidar mobile [Termes IGN] lidar topographique [Termes IGN] photogrammétrie terrestre [Termes IGN] semis de points [Termes IGN] série temporelle [Termes IGN] structure-from-motion [Termes IGN] Zurich (Suisse) Résumé : (auteur) National forest inventories (NFI) are important for the assessment of the state and development of forests. Traditional NFIs often rely on statistical sampling approaches as well as expert assessment which may suffer from observer bias and may lack robustness for time series analysis. Over the course of the last decade, close-range remote sensing techniques such as terrestrial and mobile laser scanning became ever more established for the assessment of three-dimensional (3D) forest structure. With the ongoing trend to make the systems smaller, easier to use and more efficient, the pathway is being opened for an operational inclusion of such devices within the framework of an NFI to support the traditional field assessment. Close-range remote sensing could potentially speed up field inventory work as well as increase the area in which certain parameters are assessed. Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices. Among the many parameters evaluated in traditional NFIs, the focus of the performance evaluation of this study is set on the automatic tree detection and DBH extraction. The results showed that TLS delivers the highest tree detection rate (TDR) of up to 94.6% under leaf-off and up to 82% under leaf-on conditions and a relative RMSE (rRMSE) for the DBH extraction between 2.5 and 9%, depending on the undergrowth complexity. The tested PLS system (leaf-on) achieved a TDR of up to 80% with an rRMSE between 3.7 and 5.8%. The tested UAVLS systems showed lowest TDR of less than 77% under leaf-off and less than 37% under leaf-on conditions. The novel GoPro approach achieved a TDR of up to 53% under leaf-on conditions. The reduced TDR can be explained by the reduced area coverage due to the chosen circular acquisition path taken with the GoPro approach. The DBH extraction performance on the other hand is comparable to those of the LiDAR devices with an rRMSE between 2 and 9%. Further benchmarks are needed in order to fully assess the applicability of these systems in the framework of an NFI. Especially the robustness under varying forest conditions (seasonality) and over a broader range of forest types and canopy structure has to be evaluated. Numéro de notice : A2022-787 Affiliation des auteurs : IGN (1940-2011) Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102999 Date de publication en ligne : 05/09/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102999 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101893 [article]

Estimating carbon stocks and biomass expansion factors of urban greening trees using terrestrial laser scanning / Linlin Wu in Forests, vol 13 n° 9 (september 2022)  

Public [article]  inForests > vol 13 n° 9 (september 2022) . - n° 1389 Titre : Estimating carbon stocks and biomass expansion factors of urban greening trees using terrestrial laser scanning Type de document : Article/Communication Auteurs : Linlin Wu, Auteur ; Yongjun Shi, Auteur ; Fanyi Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1389 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] biomasse forestière [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt urbaine [Termes IGN] houppier [Termes IGN] puits de carbone [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre [Termes IGN] volume en bois Résumé : (auteur) Urban forest carbon sequestration represents an important component of the global forest carbon pool; however, accurate measurements are limited by the inability of existing field stand models to match the specificity of urban greening species. Herein, canopy volume, carbon stock, and the biomass expansion factor (BEF) of 30 Koelreuteria paniculate trees were measured based on terrestrial laser scanning (TLS) and compared to the results of existing wood volume and carbon stock model measurements. The findings revealed that (1) TLS point cloud data were highly reproducible and accurate (root mean square error of tree height and diameter at breast height were ±0.35 m and ±0.33 cm, respectively). (2) Owing to human interference and cluttered urban environments, the BEF of urban greening tree species fluctuated irregularly, considerably different from that of natural forest stands. (3) Leaf carbon stocks were influenced by the size of the voxel. (4) Different tree measurement factors maintained variable degrees of influence on BEF (height under branch, volume of thick branch, crown width, and projected areas of tree-crown produced correlation coefficients of −0.64, 0.54, 0.45, and 0.43, respectively). Accordingly, the carbon stock and BEF of urban greening tree species can be accurately calculated via TLS without damage. Numéro de notice : A2022-755 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13091389 Date de publication en ligne : 31/08/2022 En ligne : https://doi.org/10.3390/f13091389 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101758 [article]

Exploring tree growth allometry using two-date terrestrial laser scanning / Tuomas Yrttimaa in Forest ecology and management, vol 518 (15 August 2022)  

Public [article]  inForest ecology and management > vol 518 (15 August 2022) . - n° 120303 Titre : Exploring tree growth allometry using two-date terrestrial laser scanning Type de document : Article/Communication Auteurs : Tuomas Yrttimaa, Auteur ; Ville Luoma, Auteur ; Ninni Saarinen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120303 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] allométrie [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt boréale [Termes IGN] houppier [Termes IGN] semis de points [Termes IGN] série temporelle [Termes IGN] surface terrière [Termes IGN] volume en bois Résumé : (auteur) Tree growth is a physio-ecological phenomena of high interest among researchers across disciplines. Observing changes in tree characteristics has conventionally required either repeated measurements of the characteristics of living trees, retrospective measurements of destructively sampled trees, or modelling. The use of close-range sensing techniques such as terrestrial laser scanning (TLS) has enabled non-destructive approaches to reconstruct the three-dimensional (3D) structure of trees and tree communities in space and time. This study aims at improving the understanding of tree allometry in general and interactions between tree growth and its neighbourhood in particular by using two-date point clouds. We investigated how variation in the increments in basal area at the breast height (Δg1.3), basal area at height corresponding to 60% of tree height (Δg06h), and volume of the stem section below 50% of tree height (Δv05h) can be explained with TLS point cloud-based attributes characterizing the spatiotemporal structure of a tree crown and crown neighbourhood, entailing the competitive status of a tree. The analyses were based on 218 trees on 16 sample plots whose 3D characteristics were obtained at the beginning (2014, T1) and at the end of the monitoring period (2019, T2) from multi-scan TLS point clouds using automatic point cloud processing methods. The results of this study showed that, within certain tree communities, strong relationships (|r| > 0.8) were observed between increments in the stem dimensions and the attributes characterizing crown structure and competition. Most often, attributes characterizing the competitive status of a tree, and the crown structure at T1, were the most important attributes to explain variation in the increments of stem dimensions. Linear mixed-effect modelling showed that single attributes could explain up to 35–60% of the observed variation in Δg1.3, Δg06h and Δv05h, depending on the tree species. This tree-level evidence of the allometric relationship between stem growth and crown dynamics can further be used to justify landscape-level analyses based on airborne remote sensing technologies to monitor stem growth through the structure and development of crown structure. This study contributes to the existing knowledge by showing that laser-based close-range sensing is a feasible technology to provide 3D characterization of stem and crown structure, enabling one to quantify structural changes and the competitive status of trees for improved understanding of the underlying growth processes. Numéro de notice : A2022-484 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2022.120303 Date de publication en ligne : 22/05/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120303 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100899 [article]

An automatic approach for tree species detection and profile estimation of urban street trees using deep learning and Google street view images / Kwanghun Choi in ISPRS Journal of photogrammetry and remote sensing, vol 190 (August 2022)  

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Crown allometry and growing space requirements of four rare domestic tree species compared to oak and beech: implications for adaptive forest management / Julia Schmucker in European Journal of Forest Research, vol 141 n° 4 (August 2022)  

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Modeling merchantable wood volume using airborne LiDAR metrics and historical forest inventory plots at a provincial scale / Antoine Leboeuf in Forests, vol 13 n° 7 (July 2022)  

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Simulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading / Štefan Kohek in International journal of applied Earth observation and geoinformation, vol 111 (July 2022)  

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Analysis of structure from motion and airborne laser scanning features for the evaluation of forest structure / Alejandro Rodríguez-Vivancos in European Journal of Forest Research, vol 141 n° 3 (June 2022)  

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Direct and automatic measurements of stem curve and volume using a high-resolution airborne laser scanning system / Eric Hyyppä in Science of remote sensing, vol 5 (June 2022)  

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Uncertainty of biomass stocks in Spanish forests: a comprehensive comparison of allometric equations / Aitor Ameztegui in European Journal of Forest Research, vol 141 n° 3 (June 2022)  

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Effects of climate and drought on stem diameter growth of urban tree species / Vjosa Dervishi in Forests, vol 13 n° 5 (May 2022)  

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Individual tree detection and estimation of stem attributes with mobile laser scanning along boreal forest roads / Raul de Paula Pires in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)  

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Comparison of neural networks and k-nearest neighbors methods in forest stand variable estimation using airborne laser data / Andras Balazs in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 4 (April 2022)  

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