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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]

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 de 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)  

Public [article]  inForest ecology and management > vol 437 (1 April 2019) . - pp 27-40 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 descripteurs IGN] agrégation temporelle [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données dendrométriques [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] insecte nuisible [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] jeu de données [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] politique forestière [Termes descripteurs IGN] quercus (genre) [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] tempête [Termes descripteurs IGN] Texas (Etats-Unis) [Vedettes matières IGN] Inventaire forestier Résumé : (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 [article]

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)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 1 (March 2019) Titre : Negative correlation between ash dieback susceptibility and reproductive success: good news for European ash forests Type de document : Article/Communication Auteurs : Devrim Semizer-Cuming, Auteur ; Reiner Finkeldey, Auteur ; Lene Rostgaard Nielsen, Auteur ; Erik Dahl Kjær, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] clonage [Termes descripteurs IGN] dépérissement [Termes descripteurs IGN] fraxinus excelsior [Termes descripteurs IGN] génétique forestière [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] mycota [Termes descripteurs IGN] régression linéaire [Vedettes matières IGN] Sylviculture Résumé : (auteur) Context : The introduced invasive pathogen Hymenoscyphus fraxineus (T. Kowalski) Baral, Queloz, and Hosoya cause extensive damage on European ash (Fraxinus excelsior L.). Heritable variation in susceptibility to ash dieback has been observed among ash trees in natural and planted populations, but it is not clear how variation in susceptibility influences reproductive fitness. Aims : We hypothesize that healthier male and female trees contribute more gametes to the following generation compared to unhealthy ones. Methods : We tested the hypothesis by studying gender, seed production, and paternal success in a clonal field trial with 39 replicated clones. In the trial, the susceptibility level of each clone has been recorded in terms of percent crown damage since 2007. We used a linear regression model to explore the relationship between susceptibility and reproductive success (female and male). Results : The clones revealed a clear gender dimorphism with an approximate 2:2:1 male/female/hermaphrodite ratio. Females with low levels of crown damage produced substantially more seeds compared to highly damaged females. The male clone with the lowest level of susceptibility was the most effective pollen donor, but highly susceptible males also sired some offspring. Conclusion : The results overall represent good news for the potential recovery of ash forests: selection against most susceptible genotypes at generation turnover is expected to facilitate building up disease resistance in ash populations. Numéro de notice : A2019-040 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0799-x date de publication en ligne : 13/02/2019 En ligne : https://doi.org/10.1007/s13595-019-0799-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92038 [article]

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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Des ormes résistants à la graphiose sont disponibles / Jean Pinon in Le Bois International : l'officiel du bois [édition verte], vol 2010 n° 14 (10 avril 2010)

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Phenotypic variation in the phenology of ascospore production between European populations of oak powdery mildew / Benoît Marçais ; Miloslava Kavkova ; Marie-Laure Desprez-Loustau in Annals of Forest Science, Vol 66 n° 8 (December 2009)  

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Peupleraie française : rouilles et puceron lanigère, l'inquiétude demeure / Olivier Baubet in Forêt entreprise, n° 189 (2009/6)

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Les pathogènes des fruitiers forestiers / Cl.-M. Favre in Forêt entreprise, n° 184 (2009/1)

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