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Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada / Wushuang Li in Forest ecology and management, Vol 466 (15 June 2020)
[article]
Titre : Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada Type de document : Article/Communication Auteurs : Wushuang Li, Auteur ; John A. Kershaw, Auteur ; Kara K. L. Costanza, Auteur ; Anthony R. Taylor, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] azote
[Termes IGN] Canada
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] Picea rubens
[Termes IGN] température de l'air
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Numéro de notice : A2020-407 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118139 Date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118139 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95464
in Forest ecology and management > Vol 466 (15 June 2020)[article]Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests / Jiaxin Chen in Forest ecology and management, Vol 466 (15 June 2020)
[article]
Titre : Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests Type de document : Article/Communication Auteurs : Jiaxin Chen, Auteur ; Hongqiang Yang, Auteur ; Rongzhou Man, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] Canada
[Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données environnementales
[Termes IGN] données spatiotemporelles
[Termes IGN] forêt boréale
[Termes IGN] gestion forestière durable
[Termes IGN] hauteur des arbres
[Termes IGN] modèle dynamique
[Termes IGN] réseau neuronal artificiel
[Termes IGN] surveillance forestièreRésumé : (auteur) Sustainable forest management requires the ability to accurately model forest dynamics under a changing environment, which is difficult using conventional statistical methods as many factors that interactively affect forest growth must be considered. As well, statistical model development is often limited by the lack of broad-scale repeated forest measurements needed to capture changes in 1 or more variables and the corresponding changes in forest dynamics (e.g., growth in diameter and height), while assuming other variables do not change, or their changes do not significantly affect the forest dynamics of interest. In many forested countries, comprehensive monitoring programs have amassed large amounts of diverse forest measurement data. Here we propose a new approach for using artificial neural network-based machine learning to synthesize spatiotemporal tree measurement data collected over a vast area of boreal forest in central Canada to model diameter at breast height (DBH)-height and DBH-height-age relationships for 6 dominant tree species. More than 30 potentially important stand structure, site, and climate variables were considered. We used an individual-based modelling approach by considering each individual tree measurement as an instance of the complex relationships modelled; together, broad-scale long-term monitoring data contain many such instances, representing considerable spatial and temporal scale variation in forest growth and growing conditions. Using this approach, we significantly improved DBH-height and DBH-height-age models. And the models developed allowed us to analyze the effects of environmental conditions or changes in these conditions on forest growth. This may be the first attempt at applying this type of approach, which can be used to more accurately model, for example, forest growth, mortality, and how they are affected by changing climate in a variety of forest types. Numéro de notice : A2020-406 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118104 Date de publication en ligne : 04/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118104 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95463
in Forest ecology and management > Vol 466 (15 June 2020)[article]Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
[article]
Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] balayage laser
[Termes IGN] canopée
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] densité du bois
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] erreur moyenne quadratique
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] hauteur à la base du houppier
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] inventaire forestier local
[Termes IGN] modèle de croissance végétale
[Termes IGN] semis de points
[Termes IGN] télédétection aérienne
[Termes IGN] télémètre laser terrestre
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] troncRésumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 Date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994
in ISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020063 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020062 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies / Helena M. Henttonen in European Journal of Forest Research, vol 139 n° 2 (April 2020)
[article]
Titre : Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies Type de document : Article/Communication Auteurs : Helena M. Henttonen, Auteur ; Pekka Nöjd, Auteur ; Susanne Suvanto, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 279 – 293 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] brûlis
[Termes IGN] densité de la végétation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] échantillonnage de données
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] paturage
[Termes IGN] peuplement forestier
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] politique forestière
[Termes IGN] sylviculture
[Termes IGN] utilisation du sol
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Frequency distributions of tree diameters are a powerful tool for analyzing changes of tree populations in large areas. We analyzed the densities and mean volume estimates of trees in different size classes for the Finnish forests over the time-span of the National Forest Inventories (1921–2013). The results display a general increase in trees in all size classes, species group and geographical area, mainly after the 1970s. The densities of medium- and large-sized conifers showed large increases in the southern boreal subzone, spruces even more than pines. Small- to medium-sized pines have increased in the middle and northern boreal subzones. The shifts in growing stock are related to changing land use, resulting from the development of the society. The low quantities of both growing stock and large trees during the 1920s reflect a poor initial state of forests. Several land use forms of the former agriculture-based society were detrimental to forests, including slash and burn agriculture, cattle grazing and tar production. The pressure from alternative land use forms was stronger in southern Finland, where the population density (people per km2) is much higher. Between 1971 and 2013, the changes in size-class structure can be attributed mainly to intensified silviculture boosted by actions of the Finnish governments, including both legislation and financial support for management activities. Not only the development of growing stock has exceeded expectations, but the increase has also concentrated in the economically valuable trees in the large size classes. Numéro de notice : A2020-344 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-019-01241-y Date de publication en ligne : 27/11/2019 En ligne : https://doi.org/10.1007/s10342-019-01241-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95224
in European Journal of Forest Research > vol 139 n° 2 (April 2020) . - pp 279 – 293[article]Predicting carbon accumulation in temperate forests of Ontario, Canada using a LiDAR-initialized growth-and-yield model / Paulina T. Marczak in Remote sensing, vol 12 n° 1 (January 2020)
[article]
Titre : Predicting carbon accumulation in temperate forests of Ontario, Canada using a LiDAR-initialized growth-and-yield model Type de document : Article/Communication Auteurs : Paulina T. Marczak, Auteur ; Karin Y. Van Ewijk, Auteur ; Paul M. Treitz, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 29 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] changement climatique
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] diamètre des arbres
[Termes IGN] données lidar
[Termes IGN] forêt tempérée
[Termes IGN] modèle de croissance végétale
[Termes IGN] Ontario (Canada)
[Termes IGN] peuplement forestier
[Termes IGN] photo-interprétation
[Termes IGN] puits de carbone
[Termes IGN] rendement
[Termes IGN] semis de pointsRésumé : (auteur) Climate warming has led to an urgent need for improved estimates of carbon accumulation in uneven-aged, mixed temperate forests, where high uncertainty remains. We investigated the feasibility of using LiDAR-derived forest attributes to initialize a growth and yield (G&Y) model in complex stands at the Petawawa Research Forest (PRF) in eastern Ontario, Canada; i.e., can G&Y models based on LiDAR provide accurate predictions of aboveground carbon accumulation in complex forests compared to traditional inventory-based estimates? Applying a local G&Y model, we forecasted aboveground carbon stock (tons/ha) and accumulation (tons/ha/yr) using recurring plot measurements from 2012–2016, FVS1. We applied statistical predictors derived from LiDAR to predict stem density (SD), stem diameter distribution (SDD), and basal area distribution (BA_dist). These data, along with measured species abundance, were used to initialize a second model (FVS2). A third model was tested using LiDAR-initialized tree lists and photo-interpreted estimates of species abundance (i.e., FVS3). The carbon stock projections for 2016 from the inventory-based G&Y model) were equivalent to validation carbon stocks measured in 2016 at all size-class levels (p 0.05). At the plot level, LiDAR-based predictions of carbon accumulation over a nine-year period did not differ when using either inventory or photo-interpreted species (p Numéro de notice : A2020-222 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12010201 Date de publication en ligne : 06/01/2020 En ligne : https://doi.org/10.3390/rs12010201 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94934
in Remote sensing > vol 12 n° 1 (January 2020) . - 29 p.[article]Vulnerability of forest ecosystems to fire in the French Alps / Sylvain Dupire in European Journal of Forest Research, Vol 138 n° 5 (octobre 2019)PermalinkSize-density trajectories for even-aged sessile oak (Quercus petraea (Matt.) Liebl.) and common beech (Fagus sylvatica L.) stands revealing similarities and differences in the mortality process / François Ningre in Annals of Forest Science, Vol 76 n° 3 (September 2019)PermalinkThe utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests / Christopher Mulverhill in Annals of Forest Science, Vol 76 n° 3 (September 2019)PermalinkComparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data / Joris Ravaglia in Forests, vol 10 n° 7 (July 2019)PermalinkOcclusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)PermalinkEstimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching / Kasper Kansanen in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)PermalinkBayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory / Francesco Minunno in Forest ecology and management, vol 440 (15 May 2019)PermalinkInterpreting effects of multiple, large-scale disturbances using national forest inventory data: A case study of standing dead trees in east Texas, USA / Christopher B. Edgar in Forest ecology and management, vol 437 (1 April 2019)PermalinkEvidence of climate effects on the height-diameter relationships of tree species / Mathieu Fortin in Annals of Forest Science, vol 76 n° 1 (March 2019)PermalinkHarmonisation of stem volume estimates in European National Forest Inventories / Thomas Gschwantner in Annals of Forest Science, vol 76 n° 1 (March 2019)Permalink