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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)  

Public [article]  inForest ecology and management > vol 497 (1 October 2021) . - n° 119493 Titre : Early detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery Type de document : Article/Communication Auteurs : Run Yu, Auteur ; Youqing Luo, Auteur ; Quan Zhou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119493 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] dépérissement [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] maladie phytosanitaire [Termes IGN] milieu tropical [Termes IGN] peuplement mélangé [Termes IGN] Pinus (genre) [Termes IGN] Pinus massoniana [Termes IGN] réflectance spectrale [Termes IGN] Ulmus (genre) Résumé : (auteur) Pine wilt disease (PWD) is a global devastating threat to forest ecosystems. Therefore, a feasible and effective approach to precisely monitor PWD infection is indispensable, especially at the early stages. However, a precise definition of “early stage” and a rapid and high-efficiency method to detect PWD infection have not been well established. In this study, we systematically divided the PWD infection into green, early, middle, and late stages based on the needle color, the resin secretion, and whether the pine wood nematode (PWN) was carried. Simultaneously, an unmanned aerial vehicle (UAV) equipped with multispectral cameras was used to obtain images. Two target detection algorithms (Faster R-CNN and YOLOv4) and two traditional machine learning algorithms based on feature extraction (random forest and support vector machine) were employed to realize the recognition of infected pine trees. Moreover, we took into consideration of the influence of green broad-leaved trees on the identification of pine trees at the early stage of PWD infection. We obtained the following results: (1) the accuracy of Faster R-CNN (60.98–66.7%) was higher than that of YOLOv4 (57.07–63.55%), but YOLOv4 outperformed in terms of model size, processing speed, training time, and testing time; (2) although the traditional machine learning models had higher accuracy (73.28–79.64%), they were not able to directly identify the object from the images; (3) the accuracy of early detection of PWD infection showed an increase of 3.72–4.29%, from 42.36–44.59% to 46.08–48.88%, when broad-leaved trees were considered. In this study, the combination of UAV-based multispectral images and target detection algorithms allowed us to monitor the occurrence of PWD and obtain the distribution of infected trees at an early stage, which can provide technical support for the prevention and control of PWD. Numéro de notice : A2021-658 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2021.119493 En ligne : https://doi.org/10.1016/j.foreco.2021.119493 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98395 [article]

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)  

Public [article]  inSilva fennica > vol 55 n° 4 (September 2021) . - n° 10515 Titre : Detection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds Type de document : Article/Communication Auteurs : Alwin A. Hardenbol, Auteur ; Anton Kuzmin, Auteur ; Lauri Korhonen, Auteur ; Pasi Korpelainen, Auteur ; Timo Kumpula, Auteur ; Matti Maltamo, Auteur ; Jari Kouki, Auteur Année de publication : 2021 Article en page(s) : n° 10515 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] aire protégée [Termes IGN] analyse discriminante [Termes IGN] Betula (genre) [Termes IGN] détection d'arbres [Termes IGN] forêt boréale [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] orthoimage couleur [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Populus tremula [Termes IGN] semis de points [Termes IGN] variation saisonnière Résumé : (auteur) Current remote sensing methods can provide detailed tree species classification in boreal forests. However, classification studies have so far focused on the dominant tree species, with few studies on less frequent but ecologically important species. We aimed to separate European aspen (Populus tremula L.), a biodiversity-supporting tree species, from the more common species in European boreal forests (Pinus sylvestris L., Picea abies [L.] Karst., Betula spp.). Using multispectral drone images collected on five dates throughout one thermal growing season (May–September), we tested the optimal season for the acquisition of mono-temporal data. These images were collected from a mature, unmanaged forest. After conversion into photogrammetric point clouds, we segmented crowns manually and automatically and classified the species by linear discriminant analysis. The highest overall classification accuracy (95%) for the four species as well as the highest classification accuracy for aspen specifically (user’s accuracy of 97% and a producer’s accuracy of 96%) were obtained at the beginning of the thermal growing season (13 May) by manual segmentation. On 13 May, aspen had no leaves yet, unlike birches. In contrast, the lowest classification accuracy was achieved on 27 September during the autumn senescence period. This is potentially caused by high intraspecific variation in aspen autumn coloration but may also be related to our date of acquisition. Our findings indicate that multispectral drone images collected in spring can be used to locate and classify less frequent tree species highly accurately. The temporal variation in leaf and canopy appearance can alter the detection accuracy considerably. Numéro de notice : A2021-735 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10515 Date de publication en ligne : 14/07/2021 En ligne : https://doi.org/10.14214/sf.10515 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98691 [article]

Calibration of the process-based model 3-PG for major central European tree species / David I. Forrester in European Journal of Forest Research, vol 140 n° 4 (August 2021)  

Public [article]  inEuropean Journal of Forest Research > vol 140 n° 4 (August 2021) . - pp 847 - 868 Titre : Calibration of the process-based model 3-PG for major central European tree species Type de document : Article/Communication Auteurs : David I. Forrester, Auteur ; Martina Lena Hobi, Auteur ; Amanda S. Mathys, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 847 - 868 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière [Termes IGN] changement climatique [Termes IGN] estimation bayesienne [Termes IGN] étalonnage de modèle [Termes IGN] Europe centrale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] peuplement mélangé [Termes IGN] régression [Termes IGN] Suisse [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Process-based forest models are important tools for predicting forest growth and their vulnerability to factors such as climate change or responses to management. One of the most widely used stand-level process-based models is the 3-PG model (Physiological Processes Predicting Growth), which is used for applications including estimating wood production, carbon budgets, water balance and susceptibility to climate change. Few 3-PG parameter sets are available for central European species and even fewer are appropriate for mixed-species forests. Here we estimated 3-PG parameters for twelve major central European tree species using 1418 long-term permanent forest monitoring plots from managed forests, 297 from un-managed forest reserves and 784 Swiss National Forest Inventory plots. A literature review of tree physiological characteristics, as well as regression analyses and Bayesian inference, were used to calculate the 3-PG parameters. The Swiss-wide calibration, based on monospecific plots, showed a robust performance in predicting forest stocks such as stem, foliage and root biomass. The plots used to inform the Bayesian calibration resulted in posterior ranges of the calibrated parameters that were, on average, 69% of the prior range. The bias of stem, foliage and root biomass predictions was generally less than 20%, and less than 10% for several species. The parameter sets also provided reliable predictions of biomass and mean tree sizes in mixed-species forests. Given that the information sources used to develop the parameters included a wide range of climatic, edaphic and management conditions and long time spans (from 1930 to present), these species parameters for 3-PG are likely to be appropriate for most central European forests and conditions. Numéro de notice : A2021-717 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-021-01370-3 Date de publication en ligne : 18/03/2021 En ligne : https://doi.org/10.1007/s10342-021-01370-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98630 [article]

The presence of shade-intolerant conifers facilitates the regeneration of Quercus petraea in mixed stands / Jeremy Borderieux in Forest ecology and management, vol 491 (1st July 2021)  

Public [article]  inForest ecology and management > vol 491 (1st July 2021) . - n° 119189 Titre : The presence of shade-intolerant conifers facilitates the regeneration of Quercus petraea in mixed stands Type de document : Article/Communication Auteurs : Jeremy Borderieux, Auteur ; Yoan Paillet, Auteur ; Marine Dalmasso , Auteur ; Anders Mårell, Auteur ; Thomas Pérot, Auteur ; Patrick Vallet, Auteur Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 119189 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Cervidae [Termes IGN] évapotranspiration [Termes IGN] inventaire forestier national (données France) [Termes IGN] peuplement mélangé [Termes IGN] Pinophyta [Termes IGN] Quercus sessiliflora [Termes IGN] régénération (sylviculture) [Termes IGN] sol forestier [Termes IGN] température de surface [Vedettes matières IGN] Foresterie Résumé : (auteur) Positive productivity-diversity relationships, pest-effect mitigation and increased resilience and stability maintain an ongoing interest for mixed stands in forestry. However, how mixing species affects forest regeneration is yet to be further explored. We used data from the French National Forest Inventory (from 2006 to 2016) to model Quercus petraea (Matt.) Liebl regeneration cover in pure and mixed Quercus petraea stands; we included the effects of abiotic and biotic factors as well as mixture. We hypothesized that the characteristics of the companion species would prevent or facilitate the regeneration of oak. Quercus petraea regeneration cover in this study responded negatively to total canopy cover and herbivory pressure. Mean July potential evapotranspiration (PET), mean December maximal temperature and soil pH are variables whose spatial variations over a given territory structure regeneration cover; all three of these variables have optimum values. Quercus petraea regeneration cover is linked to the proportion of Quercus petraea in the canopy layer in all mixed stands, except when the oak is mixed with shade-intolerant conifers: in this case, Quercus petraea regeneration is enhanced. The shade tolerance of admixed broadleaved species did not affect the Quercus petraea regeneration. This suggests that oak regeneration was facilitated with a shade-intolerant coniferous companion species due to better light transmittance through the crown or the competitive advantage of Quercus petraea over coniferous shade-intolerant species. These results are of interest for oak mixtures since Quercus petraea regeneration cover benefits from mixtures with shade-intolerant conifers and is at least equal to that of pure stands. Numéro de notice : A2021-309 Affiliation des auteurs : IGN+Ext (2020- ) Autre URL associée : vers HAL ouvert Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2021.119189 Date de publication en ligne : 08/04/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119189 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97743 [article]

Unmanned aerial vehicles (UAV)-based canopy height modeling under leaf-on and leaf-off conditions for determining tree height and crown diameter (Case study: Hyrcanian mixed forest) / Vahid Nasiri in Canadian Journal of Forest Research, Vol 51 n° 7 (July 2021)  

Public [article]  inCanadian Journal of Forest Research > Vol 51 n° 7 (July 2021) Titre : Unmanned aerial vehicles (UAV)-based canopy height modeling under leaf-on and leaf-off conditions for determining tree height and crown diameter (Case study: Hyrcanian mixed forest) Type de document : Article/Communication Auteurs : Vahid Nasiri, Auteur ; Ali Asghar Darvishsefat, Auteur ; Hossein Arefi, Auteur ; Marc Pierrot-Deseilligny , Auteur ; Manochehr Namiranian, Auteur ; Arnaud Le Bris , Auteur Année de publication : 2021 Projets : 2-Pas d'info accessible - article non ouvert / Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] diamètre des arbres [Termes IGN] filtre passe-bas [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] modèle numérique de terrain [Termes IGN] peuplement mélangé [Termes IGN] segmentation Résumé : (Auteur) Tree height and crown diameter are two common individual tree attributes that can be estimated from Unmanned Aerial Vehicles (UAVs) images thanks to photogrammetry and structure from motion. This research investigates the potential of low-cost UAV aerial images to estimate tree height and crown diameter. Two successful flights were carried out in two different seasons corresponding to leaf-off and leaf-on conditions to generate Digital Terrain Model (DTM) and Digital Surface Model (DSM), which were further employed in calculation of a Canopy Height Model (CHM). The CHM was used to estimate tree height using low pass and local maximum filters, and crown diameter was estimated based on an Invert Watershed Segmentation (IWS) algorithm. UAV-based tree height and crown diameter estimates were validated against field measurements and resulted in 3.22 m (10.1%) and 0.81 m (7.02%) RMSE, respectively. The results showed high agreement between our estimates and field measurements, with R2=0.808 for tree height and R2=0.923 for crown diameter. Generally, the accuracy of the results was considered acceptable and confirmed the usefulness of this approach for estimating tree heights and crown diameter. Numéro de notice : A2021-296 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1139/cjfr-2020-0125 Date de publication en ligne : 26/01/2021 En ligne : https://dx.doi.org/10.1139/cjfr-2020-0125 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97376 [article]

Characterization of mixed and monospecific stands of Scots pine and Maritime pine: soil profile, physiography, climate and vegetation cover data / Daphne Lopez-Marcos in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

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Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)  

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Mixture effect on radial stem and shoot growth differs and varies with temperature / Maude Toïgo in Forest ecology and management, vol 488 (15 May 2021)  

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Self-thinning tree mortality models that account for vertical stand structure, species mixing and climate / David I. Forrester in Forest ecology and management, Vol 487 ([01/05/2021])  

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Are pine-oak mixed stands in Mediterranean mountains more resilient to drought than their monospecific counterparts? / Francisco J. Muñoz-Gálvez in Forest ecology and management, vol 484 ([15/03/2021])  

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Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest / Seyedeh Kosar Hamidi in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)  

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Keeping mixtures of Norway spruce and birch in production forests: insights from survey data / Emma Hölmstrom in Scandinavian journal of forest research, vol 36 n° 2-3 ([01/03/2021])  

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The Salem simulator version 2.0: a tool for predicting the productivity of pure and mixed stands and simulating management operations / Raphaël Aussenac in Open Research Europe, vol 2021 ([01/03/2021])  

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Secondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices / Linda Rusalepp in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)  

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Sylviculture / Ana Cristina Goncalves (2021)    

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