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Guide de gestion des crises sanitaires en forêt / Louise Brunier (2020)
Titre : Guide de gestion des crises sanitaires en forêt Type de document : Monographie Auteurs : Louise Brunier, Éditeur scientifique ; Frédéric Delport, Éditeur scientifique ; Xavier Gauquelin, Éditeur 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 IGN] Abies alba
[Termes IGN] Abies grandis
[Termes IGN] aide à la décision
[Termes IGN] Carpinus betulus
[Termes IGN] dépérissement
[Termes IGN] Fagus sylvatica
[Termes IGN] Fraxinus excelsior
[Termes IGN] maladie phytosanitaire
[Termes IGN] Picea abies
[Termes IGN] Pinus nigra
[Termes IGN] Pinus pinea
[Termes IGN] Populus (genre)
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus sessiliflora
[Termes IGN] risque sanitaire
[Termes IGN] santé des forêts
[Termes IGN] surveillance sanitaire
[Termes IGN] Tilia (genre)
[Vedettes matières IGN] SylvicultureIndex. 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 Réservation
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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 IFN-001-001012 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)
[article]
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 IGN] carte de la végétation
[Termes IGN] détection d'arbres
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] indice de végétation
[Termes IGN] maladie phytosanitaire
[Termes IGN] modèle de régression
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Pinus (genre)
[Termes IGN] protection des forêts
[Termes IGN] régression logistique
[Termes IGN] semis de pointsRésumé : (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
in Journal of The Remote Sensing Society of Japan > vol 40 n° 1 (2020) . - pp 13 - 19[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)
[article]
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 IGN] Allemagne
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] diffusion spatiale
[Termes IGN] données localisées
[Termes IGN] données météorologiques
[Termes IGN] géostatistique
[Termes IGN] maladie phytosanitaire
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] rendement agricole
[Termes IGN] risque environnemental
[Termes IGN] temps réelRésumé : (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
in ISPRS International journal of geo-information > Vol 9 n° 1 (January 2020)[article]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)
[article]
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 IGN] apprentissage profond
[Termes IGN] arbre mort
[Termes IGN] base de données forestières
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] couvert forestier
[Termes IGN] feuillu
[Termes IGN] forêt boréale
[Termes IGN] image aérienne
[Termes IGN] orthoimage
[Termes IGN] peuplement mélangé
[Termes IGN] Pinophyta
[Termes IGN] Québec (Canada)
[Termes IGN] santé des forêtsRésumé : (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 Affiliation des auteurs : non IGN 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
in ISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 14 - 26[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 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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Titre : Interpreting effects of multiple, large-scale disturbances using national forest inventory data: A case study of standing dead trees in east Texas, USA Type de document : Article/Communication Auteurs : Christopher B. Edgar, Auteur ; James A. Westfall, Auteur ; Paul A. Klockow, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 27-40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] agrégation temporelle
[Termes IGN] analyse diachronique
[Termes IGN] arbre mort
[Termes IGN] catastrophe naturelle
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données dendrométriques
[Termes IGN] échantillonnage
[Termes IGN] gestion forestière
[Termes IGN] insecte nuisible
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] jeu de données
[Termes IGN] maladie phytosanitaire
[Termes IGN] Pinus (genre)
[Termes IGN] politique forestière
[Termes IGN] Quercus (genre)
[Termes IGN] sécheresse
[Termes IGN] tempête
[Termes IGN] Texas (Etats-Unis)
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Understanding the impacts of large-scale disturbances on forest conditions is necessary to support forest management, planning, and policy decision making. National forest inventories (NFIs) are an important information source that provide consistent data encompassing large areas, covering all ownerships, and extending through time. Here we compare how temporal aggregation approaches with NFI data affects estimates of standing dead trees as these respond to extreme disturbance events. East Texas was selected for this study owing to the occurrence of three significant disturbance events in a short span: Hurricane Rita in 2005, Hurricane Ike in 2008, and a historic drought in 2011. Wide-spread tree damage and mortality were reported after each disturbance and estimates of standing dead trees were used as the inventory variable for assessment. In the NFI of the US, the plot network is systematically divided into panels and one panel is measured each year. A measurement cycle is completed when all panels have been measured, which varies between 5 and 10 years depending on the region. Using the standard estimation approach of the US NFI, we computed population estimates using data from the full set of panels (FSP), multiple sets of panels (MSP), and single set of panels (SSP). For estimation, a single plot observation is computed from the most recent measurement of the plot that does not exceed the estimate year. Because one panel is measured per year, FSP and MSP estimates will necessarily consist of plot observations whose measurements were collected over a number of years. The SSP estimate is computed from one panel and thus all the plot observations are based on measurements collected over one year. We found that interpretations of disturbance event impacts varied depending on which sets of estimates were considered. All sets of estimates suggested a large and significant drought impact. However, differences existed among the estimates in the timing and magnitude of the impacts. The FSP estimates showed clear lag bias and smoothing of trends relative to the SSP estimates. MSP estimates were intermediate between FSP and SSP estimates. Differences in Hurricane Rita impacts were also observed between sets of estimates. Evidence of a net impact on standing dead trees following Hurricane Ike was weak among all sets of estimates. Given the potential for lag bias and smoothing, we recommend that SSP and MSP estimates be considered along with FSP estimates in assessments of large-scale disturbance impacts on forest conditions. Numéro de notice : A2019-483 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2019.01.027 Date de publication en ligne : 28/01/2019 En ligne : https://doi.org/10.1016/j.foreco.2019.01.027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93659
in Forest ecology and management > vol 437 (1 April 2019) . - pp 27-40[article]Negative correlation between ash dieback susceptibility and reproductive success: good news for European ash forests / Devrim Semizer-Cuming in Annals of Forest Science, vol 76 n° 1 (March 2019)PermalinkAdaptation de la sylviculture du pin laricio en France dans le contexte de la maladie des bandes rouges : Quels sont les déterminants de la vulnérabilité du pin laricio à la maladie des bandes rouges ? / Sandrine Perret (2019)PermalinkPotentialités de l’imagerie couleur embarquée pour la détection et la cartographie des maladies fongiques de la vigne / Florent Abdelghafour (2019)PermalinkEst-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, vol 70 n° 6 (2018)PermalinkCartographie des défoliations du massif forestier du Pays des étangs en Lorraine : Apports potentiels de la télédétection / Thierry Bélouard in Revue forestière française, vol 70 n° 5 (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)PermalinkPermalinkPit-mound microrelief in forest soils: Review of implications for water retention and hydrologic modelling / Martin Valtera in Forest ecology and management, vol 393 (1 June 2017)PermalinkEstimation of ash mortality induced by Hymenoscyphus fraxineus in France and Belgium / Benoît Marçais in Baltic forestry, vol 23 n° 1 ([01/01/2017])PermalinkLa vie secrète des arbres / Peter Wohlleben (2017)Permalink