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Wood decay detection in Norway spruce forests based on airborne hyperspectral and ALS data / Michele Dalponte in Remote sensing, vol 14 n° 8 (April-2 2022)
[article]
Titre : Wood decay detection in Norway spruce forests based on airborne hyperspectral and ALS data Type de document : Article/Communication Auteurs : Michele Dalponte, Auteur ; Alvar J. I. Kallio, Auteur ; Hans Ole Ørka, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bois sur pied
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] dépérissement
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données lidar
[Termes IGN] image hyperspectrale
[Termes IGN] image infrarouge
[Termes IGN] Norvège
[Termes IGN] Perceptron multicouche
[Termes IGN] Picea abies
[Termes IGN] régression linéaire
[Termes IGN] régression logistique
[Termes IGN] santé des forêts
[Termes IGN] semis de pointsRésumé : (auteur) Wood decay caused by pathogenic fungi in Norway spruce forests causes severe economic losses in the forestry sector, and currently no efficient methods exist to detect infected trees. The detection of wood decay could potentially lead to improvements in forest management and could help in reducing economic losses. In this study, airborne hyperspectral data were used to detect the presence of wood decay in the trees in two forest areas located in Etnedal (dataset I) and Gran (dataset II) municipalities, in southern Norway. The hyperspectral data used consisted of images acquired by two sensors operating in the VNIR and SWIR parts of the spectrum. Corresponding ground reference data were collected in Etnedal using a cut-to-length harvester while in Gran, field measurements were collected manually. Airborne laser scanning (ALS) data were used to detect the individual tree crowns (ITCs) in both sites. Different approaches to deal with pixels inside each ITC were considered: in particular, pixels were either aggregated to a unique value per ITC (i.e., mean, weighted mean, median, centermost pixel) or analyzed in an unaggregated way. Multiple classification methods were explored to predict rot presence: logistic regression, feed forward neural networks, and convolutional neural networks. The results showed that wood decay could be detected, even if with accuracy varying among the two datasets. The best results on the Etnedal dataset were obtained using a convolution neural network with the first five components of a principal component analysis as input (OA = 65.5%), while on the Gran dataset, the best result was obtained using LASSO with logistic regression and data aggregated using the weighted mean (OA = 61.4%). In general, the differences among aggregated and unaggregated data were small. Numéro de notice : A2022-352 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.3390/rs14081892 Date de publication en ligne : 14/04/2022 En ligne : https://doi.org/10.3390/rs14081892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100541
in Remote sensing > vol 14 n° 8 (April-2 2022) . - n° 1892[article]Assessment of RTK quadcopter and structure-from-motion photogrammetry for fine-scale monitoring of coastal topographic complexity / Stéphane Bertin in Remote sensing, vol 14 n° 7 (April-1 2022)
[article]
Titre : Assessment of RTK quadcopter and structure-from-motion photogrammetry for fine-scale monitoring of coastal topographic complexity Type de document : Article/Communication Auteurs : Stéphane Bertin, Auteur ; Pierre Stéphan, Auteur ; Jérôme Ammann, Auteur Année de publication : 2022 Article en page(s) : n° 1679 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Bretagne
[Termes IGN] centrale inertielle
[Termes IGN] données GNSS
[Termes IGN] géomorphologie locale
[Termes IGN] géoréférencement
[Termes IGN] image captée par drone
[Termes IGN] point d'appui
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] sédiment
[Termes IGN] structure-from-motion
[Termes IGN] surveillance du littoralRésumé : (auteur) Advances in image-based remote sensing using unmanned aerial vehicles (UAV) and structure-from-motion (SfM) photogrammetry continue to improve our ability to monitor complex landforms over representative spatial and temporal scales. As with other water-worked environments, coastal sediments respond to shaping processes through the formation of multi-scale topographic roughness. Although this topographic complexity can be an important marker of hydrodynamic forces and sediment transport, it is seldom characterized in typical beach surveys due to environmental and technical constraints. In this study, we explore the feasibility of using SfM photogrammetry augmented with an RTK quadcopter for monitoring the coastal topographic complexity at the beach-scale in a macrotidal environment. The method had to respond to resolution and time constraints for a realistic representation of the topo-morphological features from submeter dimensions and survey completion in two hours around low tide to fully cover the intertidal zone. Different tests were performed at two coastal field sites with varied dimensions and morphologies to assess the photogrammetric performance and eventual means for optimization. Our results show that, with precise image positioning, the addition of a single ground control point (GCP) enabled a global precision (RMSE) equivalent to that of traditional GCP-based photogrammetry using numerous and well-distributed GCPs. The optimal model quality that minimized vertical bias and random errors was achieved from 5 GCPs, with a two-fold reduction in RMSE. The image resolution for tie point detection was found to be an important control on the measurement quality, with the best results obtained using images at their original scale. Using these findings enabled designing an efficient and effective workflow for monitoring coastal topographic complexity at a large scale. Numéro de notice : A2022-287 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14071679 Date de publication en ligne : 31/03/2022 En ligne : https://doi.org/10.3390/rs14071679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100321
in Remote sensing > vol 14 n° 7 (April-1 2022) . - n° 1679[article]La bathymétrie ancienne au service de l’étude de tsunamis inexpliqués : le cas du pertuis d’Antioche (1785, 1875, 1882) / Helen Mair Rawsthorne in Norois, n° 263 (avril - juin 2022)
[article]
Titre : La bathymétrie ancienne au service de l’étude de tsunamis inexpliqués : le cas du pertuis d’Antioche (1785, 1875, 1882) Type de document : Article/Communication Auteurs : Helen Mair Rawsthorne , Auteur ; Frédéric Surville, Auteur ; Nathan Godet, Auteur ; et al., Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : pp 31 - 53 Note générale : Bibliographie
Le texte intégral en libre accès sera disponible sur le portail Cairn en janvier 2025Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bathymétrie
[Termes IGN] données localisées historiques
[Termes IGN] La Rochelle
[Termes IGN] relief sous-marin
[Termes IGN] risque naturel
[Termes IGN] submersion marine
[Termes IGN] système d'information géographique
[Termes IGN] vagueRésumé : (Auteur) Depuis la fin du xviiie siècle, des surcotes avec des vagues de type tsunami ont pu être observées à trois reprises dans le vieux port de La Rochelle : le 6 septembre 1785, le 9 juin 1875 et le 22 avril 1882. Au regard de leur caractère très localisé et n’étant corrélées ni à des anomalies météorologiques de type tempête, ni à un séisme majeur, une recherche pluridisciplinaire a été engagée pour en déterminer l’origine. Nous réalisons dans un premier temps une analyse des connaissances actuelles à propos de la géologie, la sédimentologie, la sismicité et l’hydrologie de la zone d’étude. Ensuite, nous recoupons trois sources historiques qui nous fournissent des informations complémentaires à propos des événements : des données sismiques et météorologiques anciennes, des témoignages à propos des événements, et des cartes bathymétriques anciennes du pertuis d’Antioche. Grâce à des études comparées des bathymétries ante et post aléas, et la réalisation d’un modèle numérique des différences en bathymétrie, nous montrons des variations importantes dans le chenal situé entre l’île de Ré et La Pallice, une zone interprétée comme une cicatrice d’un glissement sous-marin. Cette déstabilisation de la pente sous-marine pourrait être à l’origine de vagues mesurées à La Rochelle en 1785, en 1875 et en 1882. Numéro de notice : A2022-925 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : Cairn Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/norois.12324 Date de publication en ligne : 24/03/2022 En ligne : https://doi.org/10.4000/norois.12324 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102632
in Norois > n° 263 (avril - juin 2022) . - pp 31 - 53[article]Comparison of neural networks and k-nearest neighbors methods in forest stand variable estimation using airborne laser data / Andras Balazs in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 4 (April 2022)
[article]
Titre : Comparison of neural networks and k-nearest neighbors methods in forest stand variable estimation using airborne laser data Type de document : Article/Communication Auteurs : Andras Balazs, Auteur ; Eero Liski, Auteur ; Sakari Tuominen, Auteur Année de publication : 2022 Article en page(s) : n° 100012 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme génétique
[Termes IGN] bois sur pied
[Termes IGN] classification barycentrique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] covariance
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Finlande
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] réseau neuronal artificiel
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (auteur) In the remote sensing of forests, point cloud data from airborne laser scanning contains high-value information for predicting the volume of growing stock and the size of trees. At the same time, laser scanning data allows a very high number of potential features that can be extracted from the point cloud data for predicting the forest variables. In some methods, the features are first extracted by user-defined algorithms and the best features are selected based on supervised learning, whereas both tasks can be carried out automatically by deep learning methods typically based on deep neural networks. In this study we tested k-nearest neighbor method combined with genetic algorithm (k-NN), artificial neural network (ANN), 2-dimensional convolutional neural network (2D-CNN) and 3-dimensional CNN (3D-CNN) for estimating the following forest variables: volume of growing stock, stand mean height and mean diameter. The results indicate that there were no major differences in the accuracy of the tested methods, but the ANN and 3D-CNN generally resulted in the lowest RMSE values for the predicted forest variables and the highest R2 values between the predicted and observed forest variables. The lowest RMSE scores were 20.3% (3D-CNN), 6.4% (3D-CNN) and 11.2% (ANN) and the highest R2 results 0.90 (3D-CNN), 0.95 (3D-CNN) and 0.85 (ANN) for volume of growing stock, stand mean height and mean diameter, respectively. Covariances of all response variable combinations and all predictions methods were lower than corresponding covariances of the field observations. ANN predictions had the highest covariances for mean height vs. mean diameter and total growing stock vs. mean diameter combinations and 3D-CNN for mean height vs. total growing stock. CNNs have distinct theoretical advantage over the other methods in complex recognition or classification tasks, but the utilization of their full potential may possibly require higher point density clouds than applied here. Thus, the relatively low density of the point clouds data may have been a contributing factor to the somewhat inconclusive ranking of the methods in this study. The input data and computer codes are available at: https://github.com/balazsan/ALS_NNs. Numéro de notice : A2022-265 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.ophoto.2022.100012 Date de publication en ligne : 12/03/2022 En ligne : https://doi.org/10.1016/j.ophoto.2022.100012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100263
in ISPRS Open Journal of Photogrammetry and Remote Sensing > vol 4 (April 2022) . - n° 100012[article]Coupling fossil records and traditional discrimination metrics to test how genetic information improves species distribution models of the European beech Fagus sylvatica / Pedro Poli in European Journal of Forest Research, vol 141 n° 2 (April 2022)
[article]
Titre : Coupling fossil records and traditional discrimination metrics to test how genetic information improves species distribution models of the European beech Fagus sylvatica Type de document : Article/Communication Auteurs : Pedro Poli, Auteur ; Annie Guiller, Auteur ; Jonathan Lenoir, Auteur Année de publication : 2022 Article en page(s) : pp - 253–265 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie)
[Termes IGN] bioclimatologie
[Termes IGN] distribution spatiale
[Termes IGN] espèce végétale
[Termes IGN] Europe (géographie politique)
[Termes IGN] Fagus sylvatica
[Termes IGN] fossile
[Termes IGN] génétique forestière
[Termes IGN] Holocène
[Termes IGN] modèle de simulation
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Species distribution models (SDMs) are widely used to hindcast or forecast suitable habitat conditions during climate change. Although distant populations of a given species may show local adaptations to diverging environmental conditions, traditional SDMs disregard intraspecific variation. Yet, incorporating genetic information into SDMs could improve predictions. Here we aimed at investigating whether genetically informed SDMs would outperform traditional SDMs. Using published information on the spatial genetic structure of the European Beech Fagus sylvatica L. (1753), we built lineage-specific SDMs for each phylogenetic group of the species. We then combined all lineage-specific SDMs into a single genetically informed SDM that we compared against a traditional SDM approach. We finally compared SDMs’ predictions against independent datasets of present-day distribution as well as fossil distribution data from the Mid-Holocene, using six metrics of model performance. We found that aggregating lineage-specific SDMs into a single genetically informed SDM increased model performances to identify suitable areas currently occupied by F. sylvatica. In comparison to a traditional SDM, the genetically informed SDM we built for F. sylvatica assigned higher probabilities of occurrence during the Mid-Holocene at locations where fossil records were found. Aggregating lineage-specific SDMs into a single genetically informed SDM seems to outperform the traditional SDM approach, especially so when the aim is to identify potentially suitable areas of occupancy. This could be particularly useful for the identification of cryptic refugia that remain undetected by traditional SDMs. Genetically informed SDMs have the potential to improve our understanding of species redistribution under climate change. Numéro de notice : A2022-296 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-021-01437-1 Date de publication en ligne : 27/01/2022 En ligne : https://doi.org/10.1007/s10342-021-01437-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100353
in European Journal of Forest Research > vol 141 n° 2 (April 2022) . - pp - 253–265[article]Data assimilation of growing stock volume using a sequence of remote sensing data from different sensors / Niels Lindgren in Canadian journal of remote sensing, vol 48 n° 2 (April 2022)PermalinkDirect photogrammetry with multispectral imagery for UAV-based snow depth estimation / Kathrin Maier in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)PermalinkDrought impacts in forest canopy and deciduous tree saplings in Central European forests / Mirela Beloiu in Forest ecology and management, vol 509 (April-1 2022)PermalinkEffect of climate change on the growth of tree species: Dendroclimatological analysis / Archana Gauli in Forests, vol 13 n° 4 (April 2022)PermalinkEstimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models / Ana de Lera Garrido in Silva fennica, vol 56 n° 2 (April 2022)PermalinkFertilization modifies forest stand growth but not stand density: consequences for modelling stand dynamics in a changing climate / Hans Pretzsch in Forestry, an international journal of forest research, vol 95 n° 2 (April 2022)PermalinkIdentification and classification of routine locations using anonymized mobile communication data / Gonçalo Ferreira in ISPRS International journal of geo-information, vol 11 n° 4 (April 2022)PermalinkIdentifying locations for new bike-sharing stations in Glasgow: an analysis of spatial equity and demand factors / Jeneva Beairsto in Annals of GIS, vol 28 n° 2 (April 2022)PermalinkQuantifying discrepancies in the three-dimensional seasonal variations between IGS station positions and load models / Yujiao Niu in Journal of geodesy, vol 96 n° 4 (April 2022)PermalinkRecent changes in the climate-growth response of European larch (Larix decidua Mill.) in the Polish Sudetes / Malgorzata Danek in Trees, vol 36 n° 2 (April 2022)Permalink