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Improving the Fagacées growth model with an expanded common beech (Fagus sylvatica L.) data series from France and Germany / Gilles Le Moguédec in Annals of Forest Science [en ligne], vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 4 (December 2021) . - n° 84 Titre : Improving the Fagacées growth model with an expanded common beech (Fagus sylvatica L.) data series from France and Germany Type de document : Article/Communication Auteurs : Gilles Le Moguédec, Auteur ; Sidonie Artru, Auteur ; Axel Albrecht, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allométrie [Termes IGN] Fagus sylvatica [Termes IGN] forêt équienne [Termes IGN] France (administrative) [Termes IGN] hauteur des arbres [Termes IGN] jeu de données [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] Quercus (genre) [Termes IGN] République fédérale d'Allemagne [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message: The Fagacées growth model was originally designed for application in the Northern half of France. It is a robust model with potential applicability to a larger area, though this potential has not yet been verified. We added new data to the original parameterization data set and our results show that the Fagacées formalism can be generalized. Context: The Fagacées growth and yield model was designed for the management of pure even-aged stands of European beech and served as a prototype to build models for other tree species. Aims: The objective of this study was to improve the growth components of the Fagacées model with additional data from North-Western France to South-Western Germany. Material and methods: Our model was calibrated on several forest inventory data sets. The first one (F) is the original data set that was used to elaborate the equations in the Fagacées model. The second one (F+) is the original data set extended with additional measurements on the same sites and on new sites in Northern France. The third (G) adds complementary data from a forest network in Southwestern Germany. The last one (A) is the aggregate of all these data sets. Results: Fitting the original model equations on the extended F+ dataset led us to modify the equation for stand basal area increment. This new equation also fit the German dataset well. The other equations could be applied to all datasets, some with the same parameter values and some after recalibrating according to the dataset. Conclusion: We conclude that the general form of the model’s equations is appropriate for application to other regions, but that a recalibration of the equations is preferable in order to reflect local conditions. The advantage of our approach is that fewer data are required to recalibrate an existing equation than to establish an entirely new one. Numéro de notice : A2021-695 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01086-9 Date de publication en ligne : 20/09/2021 En ligne : https://doi.org/10.1007/s13595-021-01086-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98525 [article]

Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps / Batistin Bour in Forest ecology and management, vol 502 (15 december 2021)  

Public [article]  inForest ecology and management > vol 502 (15 december 2021) . - n° 119697 Titre : Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps Type de document : Article/Communication Auteurs : Batistin Bour, Auteur ; Victor Danneyrolles, Auteur ; Yan Boucher, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] carte forestière [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt boréale [Termes IGN] forêt de production [Termes IGN] gestion forestière [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] Picea mariana [Termes IGN] productivité [Termes IGN] Québec (Canada) [Termes IGN] récolte de bois [Termes IGN] semis de points Résumé : (auteur) Increase in forest disturbance due to land use as well as climate change has led to an expansion of young forests worldwide, which drives global carbon dynamics and timber allocation. This study presents a method that combines a single airborne LiDAR acquisition and time since harvest maps to model height growth of post-logged black spruce-dominated forests in a 1700 km2 eastern Canadian boreal landscape. We developed a random forest model in which forest height at a 20 m × 20 m pixel resolution is a function of stand age, combined with environmental variables (e.g., slope, site moisture, surface deposit). Our results highlight the model's strong predictive power: least-square regression between predicted and observed height of our validation dataset was very close to the 1:1 relation and strongly supported by validation metrics (R2 = 0.74; relative RMSE = 19%). Environmental variables thus allowed to accurately predict forest productivity with a high spatial resolution (20 m × 20 m pixels) and predicted forest height growth in the first 50 years after logging ranged between 16 and 27 cm·year−1 across the whole study area, with a mean of 20.5 cm·year−1. The spatial patterns of potential height growth were strongly linked to the effect of topographical variables, with better growth rates on mesic slopes compared to poorly drained soils. Such models could have key implications in forest management, for example to maintain forest ecosystem services by adjusting the harvesting rates depending on forest productivity across the landscapes. Numéro de notice : A2021-708 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2021.119697 Date de publication en ligne : 25/09/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98819 [article]

The efficiency of retention measures in continuous-cover forestry for conserving epiphytic cryptogams: A case study on Abies alba / Stefan Kaufmann in Forest ecology and management, vol 502 (15 december 2021)  

Public [article]  inForest ecology and management > vol 502 (15 december 2021) . - n° 119698 Titre : The efficiency of retention measures in continuous-cover forestry for conserving epiphytic cryptogams: A case study on Abies alba Type de document : Article/Communication Auteurs : Stefan Kaufmann, Auteur ; Sarah-Katharina Funck, Auteur ; Franziska Paintner, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119698 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] Allemagne [Termes IGN] Bryophyte [Termes IGN] coupe rase (sylviculture) [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] échantillonnage [Termes IGN] écosystème forestier [Termes IGN] Fagus sylvatica [Termes IGN] habitat (nature) [Termes IGN] lichen [Termes IGN] Picea abies [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Lacking structural diversity in production forests has been evidenced to decrease epiphytic bryophytes and lichens. One approach to create structurally more diverse forests is retention forestry. Only a small number of studies focused on the effectiveness of retention measures in continuous-cover forestry. Most studies have been conducted in even-aged, clear-cut based management systems and applied different approaches, but they all have in common that the retained trees have been examined for epiphytes only after harvest. Thus, it remains unclear whether these trees or even a certain tree species could take the life-boat function for epiphytes on logged sites. Thus, prior to logging, we assessed epiphytic bryophytes and lichens on potential large living retention trees, here referred to as habitat trees (HT), of Abies alba and compared the diversity pattern to nearby average trees (AT; A. alba, Fagus sylvatica or Picea abies) of smaller sizes in selectively harvested continuous-cover forests. Selection of AT was based on the average stem diameter of all trees within the stand. We found that species richness and Simpson diversity of lichens were significantly higher on HT. For bryophytes, F. sylvatica AT showed significantly higher Simpson diversity. Mixed models revealed positive effects of F. sylvatica on bryophytes, whereas large stem diameters and elevation were the driving forces for lichens. Additionally, ordinations revealed clear patterns in species composition separating between conifers and broadleaved trees, and along increasing altitude and stem diameter. Concerning HT selection, we suggest to focus rather on the tree species diversity than on stem diameter, when aiming to protect epiphytic bryophytes and lichens. Numéro de notice : A2021-769 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119698 Date de publication en ligne : 30/09/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119698 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98821 [article]

Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery / Camile Sothe in Geocarto international, Vol 36 n° 19 ([18/10/2021])  

Public [article]  inGeocarto international > Vol 36 n° 19 [18/10/2021] . - pp 2241 - 2259 Titre : Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery Type de document : Article/Communication Auteurs : Camile Sothe, Auteur ; Claudia Maria de Almeida, Auteur ; Marcos Benedito Schimalski, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2241 - 2259 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] Brésil [Termes IGN] délimitation [Termes IGN] forêt tropicale [Termes IGN] houppier [Termes IGN] identification de plantes [Termes IGN] image à très haute résolution [Termes IGN] image Worldview [Termes IGN] méthode heuristique [Termes IGN] orthoimage [Termes IGN] segmentation d'image Résumé : (auteur) In the case of tree species delineation with very high spatial resolution (VHR) images, is desirable that each segment corresponds to one individual tree crown (ITC). However, in order to have a segmentation algorithm that generates segments matching to ITCs, its parameters ought to be properly tuned. Aiming to avoid time-consuming trial-and-error procedures associated with this task, some initiatives for the automatic search of segmentation parameters have been developed, such as metaheuristic methods. The objective of this work was to test the automatic tuning of segmentation parameters of three segmentation algorithms for the delineation of ITCs belonging to a native endangered species in a subtropical forest area, comparing this method with the traditional trial-and-error approach. Two datasets (WorldView-2 and an orthoimage) and three segmentation algorithms (multiresolution, mean-shift and graph-based) were tested. For the automatic approach, a hybrid metaheuristic method was applied to accomplish the automatic search of parameters for the segmentation algorithms, while for the trial-and-error, a visual assessment was conducted for each set of parameters tested. Four supervised metrics were used to assess the quality of the segmentation results for the optimization approach and for the final set of parameters chosen in the trial-and-error approach. Results showed that none of the algorithms, datasets or approaches differ too much. The evaluation metrics values were lower, indicating that the reference ITCs polygons matched with the segmentation results. Despite the similar results, the automatic tuning of segmentation parameters proved to be a feasible alternative to reduce the subjectivity and the human effort in the choice of segmentation parameters as compared to the trial-and error approach. Numéro de notice : A2021-765 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1690056 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1690056 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98810 [article]

Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September - 2 2021)  

Public [article]  inRemote sensing > vol 13 n° 18 (September - 2 2021) . - n° 3777 Titre : Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches Type de document : Article/Communication Auteurs : He Zhang, Auteur ; Marijn Bauters, Auteur ; Pascal Boeckx, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 3777 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] apprentissage automatique [Termes IGN] biomasse aérienne [Termes IGN] Congo (bassin) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt tropicale [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] modèle numérique de terrain [Termes IGN] photogrammétrie aérienne [Termes IGN] point d'appui [Termes IGN] semis de points [Termes IGN] structure-from-motion [Termes IGN] surveillance forestière Résumé : (auteur) Tropical forests are a key component of the global carbon cycle and climate change mitigation. Field- or LiDAR-based approaches enable reliable measurements of the structure and above-ground biomass (AGB) of tropical forests. Data derived from digital aerial photogrammetry (DAP) on the unmanned aerial vehicle (UAV) platform offer several advantages over field- and LiDAR-based approaches in terms of scale and efficiency, and DAP has been presented as a viable and economical alternative in boreal or deciduous forests. However, detecting with DAP the ground in dense tropical forests, which is required for the estimation of canopy height, is currently considered highly challenging. To address this issue, we present a generally applicable method that is based on machine learning methods to identify the forest floor in DAP-derived point clouds of dense tropical forests. We capitalize on the DAP-derived high-resolution vertical forest structure to inform ground detection. We conducted UAV-DAP surveys combined with field inventories in the tropical forest of the Congo Basin. Using airborne LiDAR (ALS) for ground truthing, we present a canopy height model (CHM) generation workflow that constitutes the detection, classification and interpolation of ground points using a combination of local minima filters, supervised machine learning algorithms and TIN densification for classifying ground points using spectral and geometrical features from the UAV-based 3D data. We demonstrate that our DAP-based method provides estimates of tree heights that are identical to LiDAR-based approaches (conservatively estimated NSE = 0.88, RMSE = 1.6 m). An external validation shows that our method is capable of providing accurate and precise estimates of tree heights and AGB in dense tropical forests (DAP vs. field inventories of old forest: r2 = 0.913, RMSE = 31.93 Mg ha−1). Overall, this study demonstrates that the application of cheap and easily deployable UAV-DAP platforms can be deployed without expert knowledge to generate biophysical information and advance the study and monitoring of dense tropical forests. Numéro de notice : A2021-754 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13183777 Date de publication en ligne : 20/09/2021 En ligne : https://doi.org/10.3390/rs13183777 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98746 [article]

Extensification and afforestation of cultivated mineral soil for climate change mitigation in Finland / Boris Tupek in Forest ecology and management, vol 501 (1 December 2021)  

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Forest type matters: Global review about the structure of oak dominated old-growth temperate forests / Janos Bölöni in Forest ecology and management, vol 500 (15 November 2021)  

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National scale mapping of larch plantations for Wales using the Sentinel-2 data archive / Suvarna M. Punalekar in Forest ecology and management, vol 501 (1 December 2021)  

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Production potential, biodiversity and soil properties of forest reclamations: Opportunities or risk of introduced coniferous tree species under climate change? / Zdeněk Vacek in European Journal of Forest Research, vol 140 n° 5 (October 2021)  

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Variation in morphological and wood cell traits in coppice stems of Populus nigra L. and Salix alba L. / Seray Özden in Journal of forest science, vol 67 n° 8 (August 2021)  

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Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data / Anna Repo in Forest ecology and management, vol 498 (15 October 2021)  

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Early detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery / Run Yu in Forest ecology and management, vol 497 (1 October 2021)  

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Detection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds / Alwin A. Hardenbol in Silva fennica, vol 55 n° 4 (September 2021)  

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Large-area inventory of species composition using airborne laser scanning and hyperspectral data / Hans Ole Ørka in Silva fennica, vol 55 n° 4 (September 2021)  

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Modeling in forestry using mixture models fitted to grouped and ungrouped data / Eric K. Zenner in Forests, vol 12 n° 9 (September 2021)  

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