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Modeling size-density trajectories of even-aged ash (Fraxinus excelsior L.) stands in France. A baseline to assess the impact of Chalara ash dieback / Noël Le Goff in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 1 (March 2021) . - n° 3 Titre : Modeling size-density trajectories of even-aged ash (Fraxinus excelsior L.) stands in France. A baseline to assess the impact of Chalara ash dieback Type de document : Article/Communication Auteurs : Noël Le Goff, Auteur ; François Ningre, Auteur ; Jean-Marc Ottorini, Auteur Année de publication : 2021 Article en page(s) : n° 3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] densité de la végétation [Termes descripteurs IGN] dépérissement [Termes descripteurs IGN] éclaircie (sylviculture) [Termes descripteurs IGN] foresterie [Termes descripteurs IGN] France (administrative) [Termes descripteurs IGN] Fraxinus excelsior [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] mortalité [Termes descripteurs IGN] mycota [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: A piecewise polynomial function already used to represent the size-density trajectories of pure even-aged stands of beech, oak, and Douglas-fir proved its ability to represent the size-density trajectories of a new species, ash. The widespread ash dieback caused departures from the expected size-density trajectories. These abnormalities can be used to detect an extra level of mortality due to infection by Hymenoscyphus fraxineus in pure even-aged ash stands. Context: The size-density trajectories allow quantifying more precisely the density of stands and can help the forest manager to decide of the opportunity of thinnings. This study helped to quantify extra mortality in pure even-aged stands by using the size-density trajectories established for stands evolving at maximum density. Aims: This study was conducted to establish size-density trajectories of pure even-aged ash stands and compare them with those recently established for beech and oak in France, in particular concerning the onset of density-dependent (regular) mortality. The additional effect of ash dieback on mortality was also an issue. Material and methods: We used permanent and semi-permanent unthinned ash plots installed in the north of France and where inventories of trees were performed at more or less regular intervals: measurements included tree status (dead or alive) and diameter or girth at breast height for all trees and total height for a sample of living trees. The size-density trajectories of plots describing the course of the number of living trees in relation with the mean stand girth, in logarithmic scales, were modeled with a piecewise polynomial function fitted with a mixed-effects model. A permanent sample of trees was also selected for ash dieback and extra mortality monitoring. Results: The piecewise polynomial function already used proved its ability to represent the size-density trajectories of even-aged ash stands of various initial densities and fertility levels. As for beech and oak, the trajectories were modeled so that mortality onset occurred at a constant relative density. This level appeared to be much higher for ash (RDI = 0.58), revealing that ash survived with less growing space than beech and oak and appeared to be more efficient. Ash dieback caused an additional mortality in the experimental ash stands studied, and this excess of mortality appeared predictable on the basis of observed departures from the expected size-density trajectories. Conclusion: A single parameter function family could be used to predict the size-density trajectories of even-aged ash stands, on the basis of the results obtained previously on oak and beech. Mortality onset and space requirements of ash could be compared with those of beech and oak and show that ash can survive at higher densities and is a more efficient species. Predicted size-density trajectories proved also useful to detect and quantify the excess of mortality due to H. fraxineus on ash. This approach could be extended to other diseases and species with predictable size-density trajectories. Numéro de notice : A2021-164 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01005-4 date de publication en ligne : 07/01/2021 En ligne : https://doi.org/10.1007/s13595-020-01005-4 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97095 [article]

Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 27 - 40 Titre : Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis Type de document : Article/Communication Auteurs : T. Poblete, Auteur ; C. Camino, Auteur ; P.S.A. Beck, Auteur Année de publication : 2020 Article en page(s) : pp 27 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] chlorophylle [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] espèce végétale [Termes descripteurs IGN] fluorescence [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] Italie [Termes descripteurs IGN] maladie bactérienne [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] Olea europaea [Termes descripteurs IGN] stress hydrique [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] télédétection aérienne [Termes descripteurs IGN] traitement d'image Résumé : (auteur) Xylella fastidiosa (Xf) is a harmful plant pathogenic bacterium, able to infect over 500 plant species worldwide. Successful eradication and containment strategies for harmful pathogens require large-scale monitoring techniques for the detection of infected hosts, even when they do not display visual symptoms. Although a previous study using airborne hyperspectral and thermal imagery has shown promising results for the early detection of Xf-infected olive (Olea europaea) trees, further work is needed when adopting these techniques for large scale monitoring using multispectral cameras on board airborne platforms and satellites. We used hyperspectral and thermal imagery collected during a two-year airborne campaign in a Xf-infected area in southern Italy to assess the performance of spectrally constrained machine-learning algorithms for this task. The algorithms were used to assess multispectral bandsets, selected from the original hyperspectral imagery, that were compatible with large-scale monitoring from unmanned platforms and manned aircraft. In addition, the contribution of solar–induced chlorophyll fluorescence (SIF) and the temperature-based Crop Water Stress Index (CWSI) retrieved from hyperspectral and thermal imaging, respectively, were evaluated to quantify their relative importance in the algorithms used to detect Xf infection. The detection performance using support vector machine algorithms decreased from ∼80% (kappa, κ = 0.42) when using the original full hyperspectral dataset including SIF and CWSI to ∼74% (κ = 0.36) when the optimal set of six spectral bands most sensitive to Xf infection were used in addition to the CWSI thermal indicator. When neither SIF nor CWSI were used, the detection yielded less than 70% accuracy (decreasing κ to very low performance, 0.29), revealing that tree temperature was more important than chlorophyll fluorescence for the Xf detection. This work demonstrates that large-scale Xf monitoring can be supported using airborne platforms carrying multispectral and thermal cameras with a limited number of spectral bands (e.g., six to 12 bands with 10 nm bandwidths) as long as they are carefully selected by their sensitivity to the Xf symptoms. More precisely, the blue (bands between 400 and 450 nm to derive the NPQI index) and thermal (to derive CWSI from tree temperature) were the most critical spectral regions for their sensitivity to Xf symptoms in olive. Numéro de notice : A2020-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.010 date de publication en ligne : 18/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.010 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94745 [article]

Guide de gestion des crises sanitaires en forêt / Louise Brunier (2020)

Public Titre : Guide de gestion des crises sanitaires en forêt Type de document : Monographie Auteurs : Louise Brunier, Editeur scientifique ; Frédéric Delport, Editeur scientifique ; Xavier Gauquelin, Editeur scientifique Mention d'édition : 2eme édition Editeur : Paris [France] : Centre national professionnel de la propriété forestière Année de publication : 2020 Autre Editeur : Paris [France] : Institut pour le développement forestier IDF Importance : 184 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-2-916525-66-2 Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes descripteurs IGN] Abies alba [Termes descripteurs IGN] Abies grandis [Termes descripteurs IGN] aide à la décision [Termes descripteurs IGN] carpinus betulus [Termes descripteurs IGN] dépérissement [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] Fraxinus excelsior [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] Picea abies [Termes descripteurs IGN] Pinus nigra [Termes descripteurs IGN] Pinus pinea [Termes descripteurs IGN] Populus (genre) [Termes descripteurs IGN] pseudotsuga menziesii [Termes descripteurs IGN] Quercus pedunculata [Termes descripteurs IGN] Quercus sessiliflora [Termes descripteurs IGN] risque sanitaire [Termes descripteurs IGN] santé des forêts [Termes descripteurs IGN] surveillance sanitaire [Termes descripteurs IGN] tilia (genre) [Vedettes matières IGN] Sylviculture Index. décimale : 48.00 Végétation - généralités Résumé : (éditeur) Depuis 2010, de nouvelles crises sanitaires en forêt se sont multipliées au gré de conditions climatiques défavorables pour les forêts et de l’apparition et l’explosion localisée de bioagresseurs. Chacune d’elles est spécifique dans son ampleur, ses enjeux, sa dynamique et sa gestion. Mais toutes désorganisent la gestion forestière courante pendant plusieurs années. Cette nouvelle édition revient sur le retour d’expérience des crises passées et décrit de nouvelles crises. Elle met à disposition des acteurs forestiers les bonnes pratiques à mettre en œuvre et les outils pour affronter collectivement les évènements d’une crise sanitaire, sur les plans organisationnels et techniques. Numéro de notice : 10669 Affiliation des auteurs : non IGN Thématique : FORET Nature : Recueil / ouvrage collectif Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96946

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
10669-01	48.00	Livre	Centre de documentation	Végétation - Forêt	Disponible
IFN-001-001011	48.00 BRU	Livre	Nogent-sur-Vernisson	Bibliothèque Nogent IFN	Exclu du prêt

Individual tree detection and classification for mapping pine wilt disease using multispectral and visible color imagery acquired from unmanned aerial vehicle / Takeshi Hoshikawa in Journal of The Remote Sensing Society of Japan, vol 40 n° 1 (2020)  

Public [article]  inJournal of The Remote Sensing Society of Japan > vol 40 n° 1 (2020) . - pp 13 - 19 Titre : Individual tree detection and classification for mapping pine wilt disease using multispectral and visible color imagery acquired from unmanned aerial vehicle Type de document : Article/Communication Auteurs : Takeshi Hoshikawa, Auteur ; Kazukiyo Yamamoto, Auteur Année de publication : 2020 Article en page(s) : pp 13 - 19 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] protection des forêts [Termes descripteurs IGN] régression logistique Résumé : (auteur) Pine wilt disease is one of the most destructive disease of pine forests. It is important to detect and exterminate infected trees for preservation of the forest. We demonstrated a novel method combining individual tree detection (ITD) and classification by logistic regression using unmanned aerial vehicle (UAV) images for the mapping of infected trees. In the ITD phase, 50 % and 84 % of damaged trees were automatically detected from the 3D point cloud generated from the UAV images using the local maximum filter. These rates of detection were comparable to previous studies that used UAV imagery. Subsequently, five vegetation indices calculated from multispectral and visible color (RGB) images were used. Among the vegetation indices, normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and vegetation atmospherically resistant index (VARI) were preferable explanatory variable in the logistic regression to divide damaged and undamaged trees. The accuracy of these models ranged from 98 % to 100 % and the F-measure ranged from 94 % to 100 %. The best model, the logistic regression model using VARI as the explanatory variable, was then tested using five datasets to evaluate general performance. Each model showed explicitly high accuracy ranging from 95 % to 100 %. The best accuracy when considering the ITD and classification was 84 %. To map pine wilt disease, the proposed method is suitable for practical use due to its high-efficient and low-cost. Numéro de notice : A2020-405 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.11440/rssj.40.13 date de publication en ligne : 31/01/2020 En ligne : https://doi.org/10.11440/rssj.40.13 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96090 [article]

Spatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods / Wolfgang B. Hamer in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)  

Public [article]  inISPRS International journal of geo-information > Vol 9 n° 1 (January 2020) Titre : Spatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods Type de document : Article/Communication Auteurs : Wolfgang B. Hamer, Auteur ; Tim Birr, Auteur ; Joseph-Alexander Verreet, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] Allemagne [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] diffusion spatiale [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] géostatistique [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] rendement agricole [Termes descripteurs IGN] risque environnemental [Termes descripteurs IGN] temps réel Résumé : (auteur) Real-time identification of the occurrence of dangerous pathogens is of crucial importance for the rapid execution of countermeasures. For this purpose, spatial and temporal predictions of the spread of such pathogens are indispensable. The R package papros developed by the authors offers an environment in which both spatial and temporal predictions can be made, based on local data using various deterministic, geostatistical regionalisation, and machine learning methods. The approach is presented using the example of a crops infection by fungal pathogens, which can substantially reduce the yield if not treated in good time. The situation is made more difficult by the fact that it is particularly difficult to predict the behaviour of wind-dispersed pathogens, such as powdery mildew (Blumeria graminis f. sp. tritici). To forecast pathogen development and spatial dispersal, a modelling process scheme was developed using the aforementioned R package, which combines regionalisation and machine learning techniques. It enables the prediction of the probability of yield- relevant infestation events for an entire federal state in northern Germany at a daily time scale. To run the models, weather and climate information are required, as is knowledge of the pathogen biology. Once fitted to the pathogen, only weather and climate information are necessary to predict such events, with an overall accuracy of 68% in the case of powdery mildew at a regional scale. Thereby, 91% of the observed powdery mildew events are predicted Numéro de notice : A2020-116 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9010044 date de publication en ligne : 15/01/2020 En ligne : https://doi.org/10.3390/ijgi9010044 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94723 [article]

Interpreting 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)  

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Negative correlation between ash dieback susceptibility and reproductive success: good news for European ash forests / Devrim Semizer-Cuming in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

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Est-il possible de tirer des enseignements des introductions anciennes d'agents pathogènes ? L'exemple de la graphiose de l'orme / Dominique Piou in Revue forestière française [en ligne], vol 70 n° 6 (2018)  

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Le suivi de la santé des forêts [diaporama] / Frédéric Delport (2018)  

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Estimation of ash mortality induced by Hymenoscyphus fraxineus in France and Belgium / Benoît Marçais in Baltic forestry, vol 23 n° 1 (2017)  

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La vie secrète des arbres / Peter Wohlleben (2017)

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Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)  

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Visualisation of spread of Chalara ash dieback for raising public awareness and responsible woodland access / Chen Wang (2015) 

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Le puceron lanigère du peuplier : les avancées de la recherche / François Lieutier in Revue forestière française, vol 66 n° 1 (janvier - février 2014)  

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L'oïdium de chêne / H. Pauly in Forêts de France, n° 533 (mai 2010)

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