Descripteur
Documents disponibles dans cette catégorie (6430)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model / Arne Nothdurft in Forest ecology and management, vol 478 ([15/12/2020])
[article]
Titre : Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model Type de document : Article/Communication Auteurs : Arne Nothdurft, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] approche hiérarchique
[Termes IGN] Autriche
[Termes IGN] bioclimatologie
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] données météorologiques
[Termes IGN] estimation bayesienne
[Termes IGN] Fagus sylvatica
[Termes IGN] intégrale de Laplace
[Termes IGN] Larix decidua
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de régression
[Termes IGN] peuplement mélangé
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Quercus sessiliflora
[Termes IGN] série temporelle
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) A novel methodological framework is presented for climate-sensitive modeling of annual radial stem increments using tree-ring width time series. The approach is based on a hierarchical Bayes model together with a distributed time lag model that take into account the effects of a series of monthly temperature and precipitation values, as well as their interactions. By using a set of random walk priors, the hierarchical Bayes model allows both the detrending of the individual time series and the regression modeling to be performed simultaneously in a single model step. The approach was applied to comprehensive tree-ring width data from Austria collected on sample plots arranged in triplets representing different mixture types. Bayesian predictions revealed that European larch (Larix decidua Mill.), Norway spruce (Picea abies (L.) H. Karst.), and Scots pine (Pinus sylvestris L.) show positive climate-related growth trends throughout higher elevation sites in Tyrol, and these trends remain unchanged under a mixed-stand scenario. At the lower Austrian sites, Norway spruce was found to show a severely negative growth trend under both the pure- and mixed-stand scenario. The increment rates of European beech (Fagus sylvatica L.) were found to have a negative climate-related trend in pure stands, and the trend diminished through an admixture of spruce or larch. The trends of European larch and sessile oak (Quercus petraea (Matt.) Liebl.) showed stationary behavior, irrespective of the mixture scenario. Scots pine data showed a positive trend at the lower elevation sites under both the pure- and mixed-stand scenario. These findings indicate that species mixing does not lower the climate-related increment fluctuations of beech, oak, pine, and spruce at lower elevation sites. Numéro de notice : A2020-625 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118497 Date de publication en ligne : 07/09/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118497 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96025
in Forest ecology and management > vol 478 [15/12/2020] . - 14 p.[article]Application of various strategies and methodologies for landslide susceptibility maps on a basin scale: the case study of Val Tartano, Italy / Vasil Yordanov in Applied geomatics, vol 12 n° 4 (December 2020)
[article]
Titre : Application of various strategies and methodologies for landslide susceptibility maps on a basin scale: the case study of Val Tartano, Italy Type de document : Article/Communication Auteurs : Vasil Yordanov, Auteur ; Maria Antonia Brovelli, Auteur Année de publication : 2020 Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de sensibilité
[Termes IGN] cartographie des risques
[Termes IGN] cartographie géomorphologique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] effondrement de terrain
[Termes IGN] figuré linéaire
[Termes IGN] indice de risque
[Termes IGN] inventaire
[Termes IGN] Lombardie
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] modèle statistique
[Termes IGN] régression logistiqueRésumé : (auteur) Landslide susceptibility mapping is a crucial initial step in risk mitigation strategies. Landslide hazards are widely spread all over the world and, as such, mapping the relevant susceptibility levels is in constant research and development. As a result, numerous modelling techniques and approaches have been adopted by scholars, implementing these models at different scales and with different terrains, in search of the best-performing strategy. Nevertheless, a direct comparison is not possible unless the strategies are implemented under the same environmental conditions and scenarios. The aim of this work is to implement three statistical-based models (Statistical Index, Logistic Regression, and Random Forest) at the basin scale, using various scenarios for the input datasets (terrain variables), training samples and ratios, and validation metrics. A reassessment of the original input data was carried out to improve the model performance. In total, 79 maps were obtained using different combinations with some highly satisfactory outcomes and others that are barely acceptable. Random Forest achieved the highest scores in most of the cases, proving to be a reliable modelling approach. While Statistical Index passes the evaluation tests, most of the resulting maps were considered unreliable. This research highlighted the importance of a complete and up-to-date landslide inventory, the knowledge of local conditions, as well as the pre- and post-analysis evaluation of the input and output combinations. Numéro de notice : A2020-695 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00344-1 Date de publication en ligne : 09/11/2020 En ligne : https://doi.org/10.1007/s12518-020-00344-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96244
in Applied geomatics > vol 12 n° 4 (December 2020) . - 23 p.[article]Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination / Frederik Hass in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)
[article]
Titre : Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination Type de document : Article/Communication Auteurs : Frederik Hass, Auteur ; Jamal Jokar Arsanjani, Auteur Année de publication : 2020 Article en page(s) : n° 758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] Groenland
[Termes IGN] hydrocarbure
[Termes IGN] iceberg
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] navire
[Termes IGN] océan
[Termes IGN] seuillage d'image
[Termes IGN] trafic maritimeRésumé : (auteur) Synthetic aperture radar (SAR) plays a remarkable role in ocean surveillance, with capabilities of detecting oil spills, icebergs, and marine traffic both at daytime and at night, regardless of clouds and extreme weather conditions. The detection of ocean objects using SAR relies on well-established methods, mostly adaptive thresholding algorithms. In most waters, the dominant ocean objects are ships, whereas in arctic waters the vast majority of objects are icebergs drifting in the ocean and can be mistaken for ships in terms of navigation and ocean surveillance. Since these objects can look very much alike in SAR images, the determination of what objects actually are still relies on manual detection and human interpretation. With the increasing interest in the arctic regions for marine transportation, it is crucial to develop novel approaches for automatic monitoring of the traffic in these waters with satellite data. Hence, this study aims at proposing a deep learning model based on YoloV3 for discriminating icebergs and ships, which could be used for mapping ocean objects ahead of a journey. Using dual-polarization Sentinel-1 data, we pilot-tested our approach on a case study in Greenland. Our findings reveal that our approach is capable of training a deep learning model with reliable detection accuracy. Our methodical approach along with the choice of data and classifiers can be of great importance to climate change researchers, shipping industries and biodiversity analysts. The main difficulties were faced in the creation of training data in the Arctic waters and we concluded that future work must focus on issues regarding training data. Numéro de notice : A2020-808 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9120758 Date de publication en ligne : 19/12/2020 En ligne : https://doi.org/10.3390/ijgi9120758 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96953
in ISPRS International journal of geo-information > vol 9 n° 12 (December 2020) . - n° 758[article]Does recent fire activity impact fire-related traits of Pinus halepensis Mill. and Pinus sylvestris L. in the French Mediterranean area? / Bastien Romero in Annals of Forest Science, vol 77 n° 4 (December 2020)
[article]
Titre : Does recent fire activity impact fire-related traits of Pinus halepensis Mill. and Pinus sylvestris L. in the French Mediterranean area? Type de document : Article/Communication Auteurs : Bastien Romero, Auteur ; Anne Ganteaume, Auteur Année de publication : 2020 Article en page(s) : n° 106 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie)
[Termes IGN] écosystème
[Termes IGN] forêt méditerranéenne
[Termes IGN] France (administrative)
[Termes IGN] fréquence
[Termes IGN] génétique forestière
[Termes IGN] incendie de forêt
[Termes IGN] ontogenèse
[Termes IGN] Pinus halepensis
[Termes IGN] Pinus sylvestris
[Termes IGN] résilience écologique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: Climate change will induce a change in fire frequency in Mediterranean region and that could impact fire-adapted plant species. We showed that fire-related traits of some pine species are strongly related to other factors than fire but the recent fire history has nonetheless an impact on the variation of key traits for different fire adaptive strategies.
Context: In fire-prone Mediterranean areas, climate change is expected to exacerbate the fire pressure on ecosystems, altering the current fire regime and threatening species if they cannot acclimate.
Aims: Studying intraspecific variations of some fire-related traits in relation to variation in recent fire activity is thus an important step to better understand if this acclimation is possible.
Methods: We measured structural (bark thickness, shoot bulk density, self-pruning, leaf surface to volume ratio) and functional (serotiny level for Pinus halepensis only) traits in two pines species (Pinus halepensis and Pinus sylvestris) commonly found in southeastern France and that present different fire-adaptive strategies (resilience vs resistance, respectively). Populations were sampled according to different fire frequency modalities (0 vs 1 to 2 fires) along a geographical gradient, measuring numerous environmental and plant characteristics to be used cofactors in the analyses.
Results: As expected, trait variation was strongly linked to environmental and tree characteristics as well as to ontogeny overriding the effect of fire modalities, even though using integrative models with random effect. However, fire modalities had an impact on the variance of some key fire-related traits of Pinus halepensis.
Conclusion: This study will help to anticipate the future response of these Mediterranean pine species and further underlines the importance of investigating chemical traits, flammability, and genetic variation of highly heritable traits, such as serotiny.Numéro de notice : A2020-722 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01016-1 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1007/s13595-020-01016-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96320
in Annals of Forest Science > vol 77 n° 4 (December 2020) . - n° 106[article]Du drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique / Maxime Lafleur in XYZ, n° 165 (décembre 2020)
[article]
Titre : Du drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique Type de document : Article/Communication Auteurs : Maxime Lafleur, Auteur ; Elliot Mugner, Auteur ; Rabine Keyetieu-Nlowe, Auteur ; Nicolas Seube, Auteur Année de publication : 2020 Article en page(s) : pp 25 -32 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] auscultation d'ouvrage
[Termes IGN] barrage
[Termes IGN] base de données localisées 3D
[Termes IGN] chaîne de traitement
[Termes IGN] données lidar
[Termes IGN] drone
[Termes IGN] exactitude des données
[Termes IGN] filtrage du bruit
[Termes IGN] géoréférencement
[Termes IGN] Haute-Loire (43)
[Termes IGN] précision des données
[Termes IGN] semis de points
[Termes IGN] sol nuRésumé : (Auteur) Le levé LiDAR présenté dans cet article a été effectué dans le cadre d’une mission d’évaluation de la chaîne de traitement mdInfinity, appliquée à des données acquises par un système drone LiDAR Microdrones. Les différents outils qui constituent cette chaîne de traitement ont été développés et intégrés sur la plateforme de traitement mdInfinity dans une version particulièrement adaptée au système de levé utilisé pour cette mission. Le site utilisé pour cette évaluation est le barrage de Labrioulette (Haute-Garonne), infrastructure située sur la Garonne et exploitée par EDF. Cette zone contient de nombreux éléments sur lesquels la précision et l’exactitude des données LiDAR est primordiale afin d’obtenir un nuage de point exploitable ; notamment la complexité structurelle du barrage (figure 1), les zones sous couvert végétal dense, l’aire de transformation électrique, etc. Pour cette raison, en plus de confirmer la bonne interopérabilité des systèmes LiDAR Microdrones avec les outils de traitement mdInfinity, nous avons tiré profit de cette acquisition pour évaluer les performances de nos algorithmes. Numéro de notice : A2020-770 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96662
in XYZ > n° 165 (décembre 2020) . - pp 25 -32[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 112-2020041 RAB Revue Centre de documentation En réserve L003 Disponible Exploring the heterogeneity of human urban movements using geo-tagged tweets / Ding Ma in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)PermalinkFlore et végétation d’une portion de côte en accrétion : sud du port de Taverna (côte orientale de la Corse) / Guilhan Paradis in Bulletin de la Société botanique du Centre-Ouest, n° 51 (2020)PermalinkForest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data / Selina Ganz in Forests, vol 11 n° 12 (December 2020)PermalinkGeomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) / Marcello Buccolini in Journal of maps, vol 16 n° 3 ([01/12/2020])PermalinkInfrastructure of the spatial information in the European Community (INSPIRE) based on examples of Italy and Poland / Marek Ogryzek in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)PermalinkLarge-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)PermalinkLearning from urban form to predict building heights / Nikola Milojevic-Dupont in Plos one, vol 15 n° 12 (December 2020)PermalinkLegal aspects of registration the time of cadastral data creation or modification / Joanna Reczyńska in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)PermalinkMapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)PermalinkMultistrategy ensemble regression for mapping of built-up density and height with Sentinel-2 data / Christian Geiss in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)Permalink