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Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing / Felipe Schwerz in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 77 n° 3 (September 2020) Titre : Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing Type de document : Article/Communication Auteurs : Felipe Schwerz, Auteur ; Durval D. Neto, Auteur ; Braulio O. Caron, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] essence d'arbre [Termes descripteurs IGN] Eucalyptus grandis [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] plantation forestière [Termes descripteurs IGN] puits de carbone [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Key message: The use of reduced planting spacings is an important strategy to increase the carbon storage in the above-belowground biomass and should be recommended for future exploitation of forest energy plantations when the purpose intended is the production of biomass for energy. Context: Recent concerns about global warming have resulted in more concerted studies on quantifying carbon storage in forest systems. Forest energy plantations play an essential role in the carbon storage. Aims: We proposed to evaluate the carbon storage and partitioning in short-rotation forest plantations and to characterize the elemental composition and energetic properties of the forest species Eucalyptus grandis W. Hill ex Maiden, Mimosa scabrella Benth, and Ateleia glazioviana Baill, grown under four planting spacings in Southern Brazil. Methods: A field study was conducted in order to evaluate forest carbon stock and wood composition using samples collected by direct method. The four spacings evaluated were 2.0 × 1.0, 2.0 × 1.5, 3.0 × 1.0, and 3.0 × 1.5 m. Results: The Eucalyptus grandis stored 327.1 Mg C ha−1 at 2.0 × 1.5-m spacing. When compared with the 3.0 × 1.5-m spacing, we observed a reduction of 29% in carbon stored. All forest species showed higher carbon storage in the following partitioning pattern: trunk>roots>branches>leaves>litter. Forest species energetic properties and elemental composition were not affected by planting spacing. On the other hand, variations according the tree portions were observed. For the carbon stocks in the soil, we observed an average accumulated carbon stock for the forest species studied of 77.4 Mg C ha−1 (0–40 cm). Conclusion: Forest managers can accelerate growth and increase the forest carbon storage and biomass yield by using reduced planting spacing that are smaller than the current pattern used by the majority of the forest producers, which is 3.0 × 1.5 m. For Eucalyptus grandis and Mimosa scabrella, the planting spacings recommended to produce biomass and improve carbon stocks were 2.0 × 1.5 and 2.0 × 1.0 m, respectively. Numéro de notice : A2020-402 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00974-w date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s13595-020-00974-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95450 [article]

Large-scale patterns in forest growth rates are mainly driven by climatic variables and stand characteristics / Hao Zhang in Forest ecology and management, vol 435 (1 March 2019)  

Public [article]  inForest ecology and management > vol 435 (1 March 2019) . - pp 120 - 127 Titre : Large-scale patterns in forest growth rates are mainly driven by climatic variables and stand characteristics Type de document : Article/Communication Auteurs : Hao Zhang, Auteur ; Kelin Wang, Auteur ; Zhaoxia Zeng, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 120 - 127 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] Chine [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] forêt [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] plantation forestière [Termes descripteurs IGN] puits de carbone [Vedettes matières IGN] Végétation et changement climatique Résumé : (Auteur) Comparing the growth rate of natural forest and plantation forest may be useful to better understand rates of carbon sequestration and carbon turnover. However, the large-scale patterns of biomass growth rates in China’s forests are still not well defined. We analyzed the growth rates of forest leaves, branches, stems, and roots across forest communities in China by using data collection, collation, and systematic analysis of published research and our unpublished data. The biomass growth rates in all forests exhibited negative latitudinal trends and negative altitudinal trends, with significant influence from climatic variables and stand characteristics. Stand characteristics explained more variation in growth rates of forest biomass than did climatic variables, and growth rates of forest leaves, branches, stems, and roots varied in relation to climate, stand characteristics, and forest origin. The cross-validated results of stepwise multiple regression (SMR) models and neural network models (NNM) indicated that the prediction accuracy of growth rate of forest biomass by NNM was better than that of the SMR models. Our results improve understanding of the environmental factors affecting Chinese forest growth and inform efforts to model dynamics of carbon accumulation in China’s forests. Numéro de notice : A2019-184 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.12.054 date de publication en ligne : 04/01/2019 En ligne : https://doi.org/10.1016/j.foreco.2018.12.054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92718 [article]

Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations / Kun Liu in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 465 - 482 Titre : Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations Type de document : Article/Communication Auteurs : Kun Liu, Auteur ; Xin Shen, Auteur ; Lin Cao, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 465 - 482 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse de sensibilité [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] canopée [Termes descripteurs IGN] Chine [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] drone [Termes descripteurs IGN] échelle des données [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] Ginkgo biloba [Termes descripteurs IGN] plantation forestière [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] structure de la végétation Résumé : (auteur) Estimating forest structural attributes in planted forests is crucial for sustainably management of forests and helps to understand the contributions of forests to global carbon storage. The Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) has become a promising technology and attempts to be used for forest management, due to its capacity to provide highly accurate estimations of three-dimensional (3D) forest structural information with a lower cost, higher flexibility and finer resolution than airborne LiDAR. In this study, the effectiveness of plot-level metrics (i.e., distributional, canopy volume and Weibull-fitted metrics) and individual-tree-summarized metrics (i.e., maximum, minimum and mean height of trees and the number of trees from the individual tree detection (ITD) results) derived from UAV-LiDAR point clouds were assessed, then these metrics were used to fit estimation models of six forest structural attributes by parametric (i.e., partial least squares (PLS)) and non-parametric (i.e., k-Nearest Neighbors (k-NN) and Random Forest (RF)) approaches, within a Ginkgo plantation in east China. In addition, we assessed the effects of UAV-LiDAR point cloud density on the derived metrics and individual tree segmentation results, and evaluated the correlations of these metrics with aboveground biomass (AGB) by a sensitivity analysis. The results showed that, in general, models based on both plot-level and individual-tree-summarized metrics (CV-R2 = 0.66–0.97, rRMSE = 2.83–23.35%) performed better than models based on the plot-level metrics only (CV-R2 = 0.62–0.97, rRMSE = 3.81–27.64%). PLS had a relatively high prediction accuracy for Lorey’s mean height (CV-R2 = 0.97, rRMSE = 2.83%), whereas k-NN performed well for predicting volume (CV-R2 = 0.94, rRMSE = 8.95%) and AGB (CV-R2 = 0.95, rRMSE = 8.81%). For the point cloud density sensitivity analysis, the canopy volume metrics showed a higher dependence on point cloud density than other metrics. ITD results showed a relatively high accuracy (F1-score > 74.93%) when the point cloud density was higher than 10% (16 pts·m−2). The correlations between AGB and the metrics of height percentiles, lower height level of canopy return densities and canopy cover appeared stable across different point cloud densities when the point cloud density was reduced from 50% (80 pts·m−2) to 5% (8 pts·m−2). Numéro de notice : A2018-544 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.001 date de publication en ligne : 08/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91570 [article]

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Estimating forest canopy cover in black locust (Robinia pseudoacacia L.) plantations on the loess plateau using random forest / Qingxia Zhao in Forests, vol 9 n° 10 (October 2018)  

Public [article]  inForests > vol 9 n° 10 (October 2018) Titre : Estimating forest canopy cover in black locust (Robinia pseudoacacia L.) plantations on the loess plateau using random forest Type de document : Article/Communication Auteurs : Qingxia Zhao, Auteur ; Non-répertorié, Auteur ; Jun Zhao, Auteur ; Jingjing Zhou, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] canopée [Termes descripteurs IGN] Chine [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] Enhanced vegetation index [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image panchromatique [Termes descripteurs IGN] loess [Termes descripteurs IGN] matrice de co-occurence [Termes descripteurs IGN] plantation forestière [Termes descripteurs IGN] régression [Termes descripteurs IGN] Robinia pseudoacacia [Termes descripteurs IGN] Soil Adjusted Vegetation Index Résumé : (Auteur) The forest canopy is the medium for energy and mass exchange between forest ecosystems and the atmosphere. Remote sensing techniques are more efficient and appropriate for estimating forest canopy cover (CC) than traditional methods, especially at large scales. In this study, we evaluated the CC of black locust plantations on the Loess Plateau using random forest (RF) regression models. The models were established using the relationships between digital hemispherical photograph (DHP) field data and variables that were calculated from satellite images. Three types of variables were calculated from the satellite data: spectral variables calculated from a multispectral image, textural variables calculated from a panchromatic image (Tpan) with a 15 × 15 window size, and textural variables calculated from spectral variables (TB+VIs) with a 9 × 9 window size. We compared different mtry and ntree values to find the most suitable parameters for the RF models. The results indicated that the RF model of spectral variables explained 57% (root mean square error (RMSE) = 0.06) of the variability in the field CC data. The soil-adjusted vegetation index (SAVI) and enhanced vegetation index (EVI) were more important than other spectral variables. The RF model of Tpan obtained higher accuracy (R2 = 0.69, RMSE = 0.05) than the spectral variables, and the grey level co-occurrence matrix-based texture measure—Correlation (COR) was the most important variable for Tpan. The most accurate model was obtained from the TB+VIs (R2 = 0.79, RMSE = 0.05), which combined spectral and textural information, thus providing a significant improvement in estimating CC. This model provided an effective approach for detecting the CC of black locust plantations on the Loess Plateau. Numéro de notice : A2018-477 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9100623 date de publication en ligne : 10/10/2018 En ligne : https://doi.org/10.3390/f9100623 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91178 [article]

Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 94 - 104 Titre : Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Jean-Claude Thill, Auteur ; Sutee Anantsuksomsri, Auteur ; Nij Tontisirin, Auteur ; Ran Tao, Auteur Année de publication : 2018 Article en page(s) : pp 94 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] Birmanie [Termes descripteurs IGN] Chine [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] dendrochronologie [Termes descripteurs IGN] Hevea brasiliensis [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] Laos [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] plantation forestière [Termes descripteurs IGN] série temporelle Résumé : (Auteur) Rubber (Hevea brasiliensis) plantations are a rapidly increasing source of land cover change in mainland Southeast Asia. Stand age of rubber plantations obtained at fine scales provides essential baseline data, informing the pace of industrial and smallholder agricultural activities in response to the changing global rubber markets, and local political and socioeconomic dynamics. In this study, we developed an integrated pixel- and object-based tree growth model using Landsat annual time series to estimate the age of rubber plantations in a 21,115 km2 tri-border region along the junction of China, Myanmar and Laos. We produced a rubber stand age map at 30 m resolution, with an accuracy of 87.00% for identifying rubber plantations and an average error of 1.53 years in age estimation. The integration of pixel- and object-based image analysis showed superior performance in building NDVI yearly time series that reduced spectral noises from background soil and vegetation in open-canopy, young rubber stands. The model parameters remained relatively stable during model sensitivity analysis, resulting in accurate age estimation robust to outliers. Compared to the typically weak statistical relationship between single-date spectral signatures and rubber tree age, Landsat image time series analysis coupled with tree growth modeling presents a viable alternative for fine-scale age estimation of rubber plantations. Numéro de notice : A2018-399 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.003 date de publication en ligne : 13/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90828 [article]

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Optimal 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 [en ligne], vol 75 n° 1 (March 2018)  

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Airborne laser scanning for tree diameter distribution modelling: a comparison of different modelling alternatives in a tropical single-species plantation / Matti Maltamo in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

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Predicting stem total and assortment volumes in an industrial pinus taeda L. forest plantation using airborne laser scanning data and random forest / Carlos Alberto Silva in Forests, vol 8 n° 7 (July 2017)  

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Gestion des peuplements en forêt publique : nouvelles pistes de recherche, développement et innovation / Christine Deleuze in Revue forestière française [en ligne], vol 68 n° 6 (décembre 2016)  

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An evolutionary ecology perspective to address forest pathology challenges of today and tomorrow / Marie-Laure Desprez-Loustau in Annals of Forest Science [en ligne], vol 73 n° 1 (March 2016)  

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Comparing individual-tree approaches for predicting height growth of underplanted seedlings / John M. Lhotka in Annals of Forest Science [en ligne], vol 72 n° 4 (June 2015)  

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Response of Swiss forests to management and climate change in the last 60 years / Meinrad Küchler in Annals of Forest Science [en ligne], vol 72 n° 3 (May 2015)  

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Variation in irradiance, soil features and regeneration patterns in experimental forest canopy gaps / Urša Vilhar in Annals of Forest Science [en ligne], vol 72 n° 2 (March - april 2015)  

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Assessing tree dendrometrics in young regenerating plantations using terrestrial laser scanning / Ying Li in Annals of Forest Science, vol 71 n° 4 (June 2014)  

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Green is the new grey / Mary Jo Wagner in GEO: Geoconnexion international, vol 13 n° 1 (january 2014)

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