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Mapping dead forest cover using a deep convolutional neural network and digital aerial photography / Jean-Daniel Sylvain in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 14 - 26 Titre : Mapping dead forest cover using a deep convolutional neural network and digital aerial photography Type de document : Article/Communication Auteurs : Jean-Daniel Sylvain, Auteur ; Guillaume Drolet, Auteur ; Nicolas Brown, Auteur Année de publication : 2019 Article en page(s) : pp 14 - 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] base de données forestières [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] Québec (Canada) [Termes descripteurs IGN] santé des forêts Résumé : (Auteur) Tree mortality is an important forest ecosystem variable having uses in many applications such as forest health assessment, modelling stand dynamics and productivity, or planning wood harvesting operations. Because tree mortality is a spatially and temporally erratic process, rates and spatial patterns of tree mortality are difficult to estimate with traditional inventory methods. Remote sensing imagery has the potential to detect tree mortality at spatial scales required for accurately characterizing this process (e.g., landscape, region). Many efforts have been made in this sense, mostly using pixel- or object-based methods. In this study, we explored the potential of deep Convolutional Neural Networks (CNNs) to detect and map tree health status and functional type over entire regions. To do this, we built a database of around 290,000 photo-interpreted trees that served to extract and label image windows from 20 cm-resolution digital aerial images, for use in CNN training and evaluation. In this process, we also evaluated the effect of window size and spectral channel selection on classification accuracy, and we assessed if multiple realizations of a CNN, generated using different weight initializations, can be aggregated to provide more robust predictions. Finally, we extended our model with 5 additional classes to account for the diversity of landcovers found in our study area. When predicting tree health status only (live or dead), we obtained test accuracies of up to 94%, and up to 86% when predicting functional type only (broadleaf or needleleaf). Channel selection had a limited impact on overall classification accuracy, while window size increased the ability of the CNNs to predict plant functional type. The aggregation of multiple realizations of a CNN allowed us to avoid the selection of suboptimal models and help to remove much of the speckle effect when predicting on new aerial images. Test accuracies of plant functional type and health status were not affected in the extended model and were all above 95% for the 5 extra classes. Our results demonstrate the robustness of the CNN for between-scene variations in aerial photography and also suggest that this approach can be applied at operational level to map tree mortality across extensive territories. Numéro de notice : A2019-316 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.07.010 date de publication en ligne : 02/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.07.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93353 [article]

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Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators / Dinesh Babu Irulappa Pillai Vijayakumar in Remote sensing, vol 11 n° 8 (August 2019)  

Public [article]  inRemote sensing > vol 11 n° 8 (August 2019) Titre : Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators Type de document : Article/Communication Auteurs : Dinesh Babu Irulappa Pillai Vijayakumar, Auteur ; Jean-Pierre Renaud, Auteur ; François Morneau, Auteur ; Ronald E. McRoberts, Auteur ; Cédric Vega , Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] arbre caducifolié [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] inférence statistique [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier national (données France) [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] Orléans, forêt d' (Loiret) [Termes descripteurs IGN] photogrammétrie numérique [Termes descripteurs IGN] Pinus pinaster [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] quercus pedunculata [Termes descripteurs IGN] quercus sessiliflora [Termes descripteurs IGN] Sologne (France) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Multisource forest inventory methods were developed to improve the precision of national forest inventory estimates. These methods rely on the combination of inventory data and auxiliary information correlated with forest attributes of interest. As these methods have been predominantly tested over coniferous forests, the present study used this approach for heterogeneous and complex deciduous forests in the center of France. The auxiliary data considered included a forest type map, Landsat 8 spectral bands and derived vegetation indexes, and 3D variables derived from photogrammetric canopy height models. On a subset area, changes in canopy height estimated from two successive photogrammetric models were also used. A model-assisted inference framework, using a k nearest-neighbors approach, was used to predict 11 field inventory variables simultaneously. The results showed that among the auxiliary variables tested, 3D metrics improved the precision of dendrometric estimates more than other auxiliary variables. Relative efficiencies (RE) varying from 2.15 for volume to 1.04 for stand density were obtained using all auxiliary variables. Canopy height changes also increased RE from 3% to 26%. Our results confirmed the importance of 3D metrics as auxiliary variables and demonstrated the value of canopy change variables for increasing the precision of estimates of forest structural attributes such as density and quadratic mean diameter. Numéro de notice : A2019-382 Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11080991 date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.3390/rs11080991 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93456 [article]

Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data / Joris Ravaglia in Forests, vol 10 n° 7 (July 2019)  

Public [article]  inForests > vol 10 n° 7 (July 2019) . - 19 p. Titre : Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data Type de document : Article/Communication Auteurs : Joris Ravaglia, Auteur ; Richard A. Fournier, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur ; Jean-François Côté, Auteur ; Alexandre Piboule, Auteur ; Ulysse Rémillard, Auteur Année de publication : 2019 Projets : ARBRE / Article en page(s) : 19 p. Note générale : bibliographie Cédric Vega is supported by a public grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Canada [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] France (administrative) [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] transformation de Hough [Termes descripteurs IGN] volume en bois Résumé : (auteur) Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during forest inventories. Various specialized algorithms have been developed to provide automatic and objective estimates of forest attributes from point clouds. The STEP (Snakes for Tuboid Extraction from Point cloud) algorithm was developed to estimate both stem diameter at breast height and stem diameters along the bole length. Here, we evaluate the accuracy of this algorithm and compare its performance with two other state-of-the-art algorithms that were designed for the same purpose (i.e., the CompuTree and SimpleTree algorithms). We tested each algorithm against point clouds that incorporated various degrees of noise and occlusion. We applied these algorithms to three contrasting test sites: (1) simulated scenes of coniferous stands in Newfoundland (Canada), (2) test sites of deciduous stands in Phalsbourg (France), and (3) coniferous plantations in Quebec, Canada. In most cases, the STEP algorithm predicted diameter at breast height with higher R2 and lower RMSE than the other two algorithms. The STEP algorithm also achieved greater accuracy when estimating stem diameter in occluded and noisy point clouds, with mean errors in the range of 1.1 cm to 2.28 cm. The CompuTree and SimpleTree algorithms respectively produced errors in the range of 2.62 cm to 6.1 cm and 1.03 cm to 3.34 cm, respectively. Unlike CompuTree or SimpleTree, the STEP algorithm was not able to estimate trunk diameter in the uppermost portions of the trees. Our results show that the STEP algorithm is more adapted to extract DBH and stem diameter automatically from occluded and noisy point clouds. Our study also highlights that SimpleTree and CompuTree require data filtering and results corrections. Conversely, none of these procedures were applied for the implementation of the STEP algorithm. Numéro de notice : A2019-337 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f10070599 date de publication en ligne : 18/07/2019 En ligne : https://doi.org/10.3390/f10070599 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93367 [article]

Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem / Aaron G. Kamoske in Forest ecology and management, vol 433 (15 February 2019)  

Public [article]  inForest ecology and management > vol 433 (15 February 2019) . - pp 364 - 375 Titre : Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem Type de document : Article/Communication Auteurs : Aaron G. Kamoske, Auteur ; Kyla M. Dahlin, Auteur ; Scott C. Stark, Auteur ; Shawn P. Serbin, Auteur Année de publication : 2019 Article en page(s) : pp 364 - 375 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] canopée [Termes descripteurs IGN] densité du feuillage [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] forêt tempérée [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] R (langage) [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] structure d'un peuplement forestier Résumé : (auteur) Forest processes that play an essential role in carbon sequestration, such as light use efficiency, photosynthetic capacity, and trace gas exchange, are closely tied to the three-dimensional structure of forest canopies. However, the vertical distribution of leaf traits is not uniform; leaves at varying vertical positions within the canopy are physiologically unique due to differing light and environmental conditions, which leads to higher carbon storage than if light conditions were constant throughout the canopy. Due to this within-canopy variation, three-dimensional structural traits are critical to improving our estimates of global carbon cycling and storage by Earth system models and to better understanding the effects of disturbances on carbon sequestration in forested ecosystems. In this study, we describe a reproducible and open-source methodology using the R programming language for estimating leaf area density (LAD; the total leaf area per unit of volume) from airborne LiDAR. Using this approach, we compare LAD estimates at the Smithsonian Environmental Research Center in Maryland, USA, from two airborne LiDAR systems, NEON AOP and NASA G-LiHT, which differ in survey and instrument specifications, collections goals, and laser pulse densities. Furthermore, we address the impacts of the spatial scale of analysis as well as differences in canopy penetration and pulse density on LAD and leaf area index (LAI) estimates, while offering potential solutions to enhance the accuracy of these estimates. LAD estimates from airborne LiDAR can be used to describe the three-dimensional structure of forests across entire landscapes. This information can help inform forest management and conservation decisions related to the estimation of aboveground biomass and productivity, the response of forests to large-scale disturbances, the impacts of drought on forest health, the conservation of bird habitat, as well as a host of other important forest processes and responses. Numéro de notice : A2019-008 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.11.017 date de publication en ligne : 21/11/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.11.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91601 [article]

Forest conversion from Norway spruce to European beech increases species richness and functional structure of aboveground macrofungal communities / Peggy Heine in Forest ecology and management, vol 432 (15 January 2019)  

Public [article]  inForest ecology and management > vol 432 (15 January 2019) . - pp 522 - 533 Titre : Forest conversion from Norway spruce to European beech increases species richness and functional structure of aboveground macrofungal communities Type de document : Article/Communication Auteurs : Peggy Heine, Auteur ; Jonas Hausen, Auteur ; Richard Ottermanns, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 522 - 533 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Allemagne [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] conversion forestière [Termes descripteurs IGN] écosystème forestier [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] mycota [Termes descripteurs IGN] parc naturel national [Termes descripteurs IGN] Picea abies [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] protection de la biodiversité [Termes descripteurs IGN] protection des forêts [Termes descripteurs IGN] richesse floristique [Termes descripteurs IGN] tempête [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) This study investigated the response patterns of aboveground macrofungal communities to different management stages representing a forest conversion from Norway spruce (Picea abies) to European beech (Fagus sylvatica) in the Eifel National Park, Germany. We used a space-for-time substitution approach with three replicate study sites for each forest conversion stage: (I) even-aged single species Norway spruce, (II) unmanaged Norway spruce windthrow, (III) salvage-logged Norway spruce windthrow, (IV) single Norway spruce tree selection cutting (close-to-nature managed) with European beech underplanting and (V) old-growth, uneven-aged European beech (as reference). We assessed environmental variables and macrofungal sporocarps, while the latter were categorized into functional groups to link taxonomic information to potential ecosystem functions. Overall, we observed 235 macrofungal species. The highest species richness was found in the European beech reference stage, followed by the close-to-nature managed spruce/beech stage, while the Norway spruce stage showed approximately half the species richness, similar to the species level of both windthrow stages. Non-metric multidimensional scaling (NMDS) ordination separated each forest conversion stage into distinct fungal communities, while both windthrow stages could not be distinguished from each other. Beside tree species composition change and forest management, nutrient availability and microclimate were the main drivers of fungal community changes among the five differently-managed stages. Further, different functional groups responded in different patterns to forest management and to explanatory environmental variables. We reinforced the assumption, that old-growth, uneven-aged European beech forests (>120 years) can act as a refugium for unique forest type specific fungal communities with a higher functional structure, especially contrary to non-native, even-aged Norway spruce forests (∼70 years). Single Norway spruce tree selection cutting with further introduction of European beech trees can be an adequate strategy to allow a spruce forest conversion without necessarily reducing the macrofungal species richness and its functional structure. We displayed that ecological consequences of windthrow events can be a depression of fungal species richness and a collapse for the functional structure of fungi, especially after salvage logging. Our study underlines the need of including fungal conservation in forest conversion plans to optimize forest ecosystem integrity and resilience against biotic and abiotic agents, such as windstorm events. Numéro de notice : A2019-004 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.09.012 date de publication en ligne : 04/10/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.09.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91597 [article]

Réévaluation de la ressource et de la disponibilité en bois d’oeuvre des essences feuillues et conifères en France / Philippe Monchaux (2019)

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Detecting the competition between Moso bamboos and broad-leaved trees in mixed forests using a terrestrial laser scanner / Yingjie Yan in Forests, vol 9 n° 9 (September 2018)  

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Factors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012 : The role of topography and drought / Juan José Vidal-Macua in Forest ecology and management, vol 406 (15 December 2017)  

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Total canopy transmittance estimated from small-footprint, full-waveform airborne LiDAR / Milutin Milenković in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

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Assessing future suitability of tree species under climate change by multiple methods: a case study in southern Germany / Helge Walentowski in Annals of forest research, vol 60 n° 1 (January - June 2017)  

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Individual tree basal area increment models for broadleaved forests in Bhutan / Jigme Tenzin in Forestry, an international journal of forest research, vol 90 n° 3 (May 2017)  

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Utilisation d’un modèle numérique de hauteur en stratification des données de l’Inventaire Forestier National / Sophie Georges (2017) 

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Effective number of layers: A new measure for quantifying three-dimensional stand structure based on sampling with terrestrial LiDAR / Martin Ehbrecht in Forest ecology and management, vol 380 (15 november 2016)  

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Land ownership affects diversity and abundance of tree microhabitats in deciduous temperate forests / Franz Johann in Forest ecology and management, vol 380 (15 november 2016)  

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Direct measurement of evapotranspiration from a forest using a superconducting gravimeter / Michel Van Camp in Geophysical research letters, vol 43 n° 19 (15 October 2016)    

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