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Evaluation of 10-year temporal and spatial variability in structure and growth across contrasting commercial thinning treatments in spruce-fir forests of northern Maine, USA / Christian Kuehne in Annals of Forest Science, vol 75 n° 1 (March 2018)
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Titre : Evaluation of 10-year temporal and spatial variability in structure and growth across contrasting commercial thinning treatments in spruce-fir forests of northern Maine, USA Type de document : Article/Communication Auteurs : Christian Kuehne, Auteur ; Aaron R. Weiskittel, Auteur ; Arne Pommerening, Auteur ; Robert G. Wagner, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies balsamea
[Termes IGN] arbre aléatoire
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] Maine (Etats-Unis)
[Termes IGN] Picea rubens
[Termes IGN] Pinus strobus
[Termes IGN] station forestière
[Termes IGN] thuja (genre)
[Vedettes matières IGN] SylvicultureRésumé : (Auteur) Key message: Detailed measures of growth pattern and structural heterogeneity applied in this study helped to quantify the immediate effects of various thinning regimes on forest structure and the resulting alterations in tree size as well as observed longer term stand dynamics.
Context: Forest management, stand structure, and tree growth are highly inter-correlated. Prior analyses, however, have resulted in mixed outcomes with limited success in revealing ecological mechanisms.
Aims: The study aimed at evaluating the relationship between forest structure and stand dynamics by applying several sophisticated measures of growth pattern and structural heterogeneity.
Methods : Data from a controlled and fully stem-mapped commercial thinning experiment with seven contrasting treatments including a non-thinned control at six locations across the Acadian Forest of Maine, USA, was used. Stand-level attributes examined included tree size and growth heterogeneity, spatial tree distribution, and growth dominance.
Results: Thinning generally reduced stand structural heterogeneity compared to the non-thinned control. In addition, the spatial arrangement of trees changed from fully random (non-thinned control) to a more clustered (removal of dominant and co-dominant individuals) or regular distribution (removal of intermediate and suppressed individuals). Overall, stand growth exhibited increasing (non-thinned control, removal of intermediate and suppressed individuals) or decreasing growth dominance of large trees (removal of co-dominant competitors). Forwarder trails increased basal area growth of individual trees up to a distance from the trail of approximately 5 m.
Conclusion: Findings of this study validate an earlier insight according to which interactions between management practices, forest structure, and tree growth form a permanent feedback loop.
KeywordsNuméro de notice : A2018-315 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-018-0697-7 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1007/s13595-018-0697-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90439
in Annals of Forest Science > vol 75 n° 1 (March 2018)[article]Evaluation of close-range photogrammetry image collection methods for estimating tree diameters / Martin Mokroš in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)
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Titre : Evaluation of close-range photogrammetry image collection methods for estimating tree diameters Type de document : Article/Communication Auteurs : Martin Mokroš, Auteur ; Xinlian Liang, Auteur ; Peter Surový, Auteur ; Peter Valent, Auteur ; Juraj Čerňava, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes IGN] angle de visée
[Termes IGN] diamètre des arbres
[Termes IGN] Fagus sylvatica
[Termes IGN] photogrammétrie métrologique
[Termes IGN] placette d'échantillonnage
[Termes IGN] semis de pointsRésumé : (Auteur) The potential of close-range photogrammetry (CRP) to compete with terrestrial laser scanning (TLS) to produce dense and accurate point clouds has increased in recent years. The use of CRP for estimating tree diameter at breast height (DBH) has multiple advantages over TLS. For example, point clouds from CRP are similar to TLS, but hardware costs are significantly lower. However, a number of data collection issues need to be clarified before the use of CRP in forested areas is considered effective. In this paper we focused on different CRP data collection methods to estimate DBH. We present seven methods that differ in camera orientation, shooting mode, data collection path, and other important factors. The methods were tested on a research plot comprised of European beeches (Fagus sylvatica L.). The circle-fitting algorithm was used to estimate DBH. Four of the seven methods were capable of producing a dense point cloud. The tree detection rate varied from 49% to 81%. Estimates of DBH produced a root mean square error that varied from 4.41 cm to 5.98 cm. The most accurate method was achieved using a vertical camera orientation, stop-and-go shooting mode, and a path leading around the plot with two diagonal paths through the plot. This method also had the highest rate of tree detection (81%). Numéro de notice : A2018-099 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030093 En ligne : https://doi.org/10.3390/ijgi7030093 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89514
in ISPRS International journal of geo-information > vol 7 n° 3 (March 2018)[article]Harmonic regression of Landsat time series for modeling attributes from national forest inventory data / Barry T. Wilson in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
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Titre : Harmonic regression of Landsat time series for modeling attributes from national forest inventory data Type de document : Article/Communication Auteurs : Barry T. Wilson, Auteur ; Joseph F. Knight, Auteur ; Ronald E. McRoberts, Auteur Année de publication : 2018 Article en page(s) : pp 29 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attribut
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] régression harmonique
[Termes IGN] série temporelleRésumé : (Auteur) Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009–2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10–20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher. Numéro de notice : A2018-077 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89439
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 29 - 46[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt How much does climate change threaten European forest tree species distributions? / Marcin K. Dyderski in Global change biology, vol 24 n° 3 (March 2018)
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Titre : How much does climate change threaten European forest tree species distributions? Type de document : Article/Communication Auteurs : Marcin K. Dyderski, Auteur ; Sonia Paz, Auteur ; Lee E. Frelich, Auteur ; Andrzej M. Jagodzinski, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] Betula pendula
[Termes IGN] changement climatique
[Termes IGN] distribution spatiale
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt tempérée
[Termes IGN] Fraxinus excelsior
[Termes IGN] gestion forestière
[Termes IGN] habitat (nature)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Larix decidua
[Termes IGN] modèle de simulation
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus rubra
[Termes IGN] Quercus sessiliflora
[Termes IGN] Robinia pseudoacacia
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios – optimistic (RCP2.6), moderate (RCP4.5) and pessimistic (RPC8.5) – using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: “winners” – mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur and Q. petraea; “losers” – mostly pioneer species: Betula pendula, Larix decidua, Picea abies and Pinus sylvestris and alien species – Pseudotsuga menziesii, Q. rubra and Robinia pseudoacacia, which may be also considered as “winners”. Assuming limited migration, most of the species studied would face significant decrease of suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. Numéro de notice : A2018-379 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/gcb.13925 En ligne : http://doi.org/10.1111/gcb.13925 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87220
in Global change biology > vol 24 n° 3 (March 2018)[article]Important LiDAR metrics for discriminating forest tree species in Central Europe / Yifang Shi in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
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Titre : Important LiDAR metrics for discriminating forest tree species in Central Europe Type de document : Article/Communication Auteurs : Yifang Shi, Auteur ; Tiejun Wang, Auteur ; Andrew K. Skidmore, Auteur ; Marco Heurich, Auteur Année de publication : 2018 Article en page(s) : pp 163 - 174 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Allemagne
[Termes IGN] arbre (flore)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Europe centrale
[Termes IGN] forêt tempérée
[Termes IGN] morphologie mathématiqueRésumé : (Auteur) Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe. Numéro de notice : A2018-080 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.002 Date de publication en ligne : 07/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89442
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 163 - 174[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Mapping tree cover with Sentinel-2 data using the Support Vector Machine (SVM) / Anna Mirończuk in Geoinformation issues, Vol 9 n° 1 (2017)
PermalinkOptimal management of larch (Larix olgensis A. Henry) plantations in Northeast China when timber production and carbon stock are considered / Wei Peng in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkPredicting suitability of forest dynamics to future climatic conditions: the likely dominance of Holm oak [Quercus ilex subsp. ballota (Desf.) Samp.] and Aleppo pine (Pinus halepensis Mill.) / Javier López-Tirado in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkRemote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data / Xiaojun Xu in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkResponses of the structure and function of the understory plant communities to precipitation reduction across forest ecosystems in Germany / Katja Felsmann in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkSeasonal time-course of the above ground biomass production efficiency in beech trees (Fagus sylvatica L.) / Laura Heid in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkA spatio-temporal dataset of forest mensuration for the analysis of tree species structure and diversity in semi-natural mixed floodplain forests / Most Jannatul Fardusi in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkUnderstanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
Permalink3D visualization of trees based on a sphere-board model / Jiangfeng She in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)
PermalinkEstimating forest standing biomass in savanna woodlands as an indicator of forest productivity using the new generation WorldView-2 sensor / Timothy Dube in Geocarto international, vol 33 n° 2 (February 2018)
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