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FORESTIMATOR : un plugin QGIS d'estimation de la hauteur dominante et du site index de peuplements résineux à partir de Lidar aérien / Laurent Dedry in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)
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Titre : FORESTIMATOR : un plugin QGIS d'estimation de la hauteur dominante et du site index de peuplements résineux à partir de Lidar aérien Type de document : Article/Communication Auteurs : Laurent Dedry, Auteur ; Olivier de Thier, Auteur ; Jérôme Perin, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 119 - 128 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt équienne
[Termes IGN] hauteur des arbres
[Termes IGN] indicateur biologique
[Termes IGN] lasergrammétrie
[Termes IGN] module d'extension
[Termes IGN] Picea abies
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] QGIS
[Termes IGN] sylviculture
[Termes IGN] système d'information géographique
[Termes IGN] Wallonie (Belgique)Résumé : (auteur) La hauteur dominante est une information souvent utilisée en gestion forestière. Il s'agit d'un bon indicateur du niveau de développement des peuplements, pouvant être employé pour estimer le niveau de productivité des peuplements purs équiennes. Cependant, son estimation à partir de mesures de terrain est relativement fastidieuse et coûteuse. Depuis plusieurs années, le LiDAR est reconnu pour sa capacité à estimer la hauteur des couverts forestiers de manière précise. En Wallonie, une couverture LiDAR basse densité (0,8 points/m2 au sol) est disponible sur l'intégralité du territoire. Cet article présente un outil d'aide à la gestion forestière s'appuyant sur un modèle de prédiction de la hauteur dominante à partir de données LiDAR aérien. Les estimations fournies par ce modèle sont ensuite couplées à des modèles de croissance en hauteur dominante qui permettent une mise à jour de la hauteur dominante au cours du temps et l'estimation du Site Index (indice de productivité). Cet outil a été validé pour les peuplements d'épicéa commun (Picea abies (L.) H. Karst.f) et de douglas (Pseudotsuga menziesii (Mirb.) Franco) sur une emprise géographique correspondant à la Wallonie (Belgique). Pour permettre une utilisation aisée, il a été intégré dans un plug-in du logiciel de Système d'Information Géographique (SIG) open source QGIS. Gratuit et facile d'utilisation, il est destiné aux gestionnaires forestiers et aux scientifiques. Numéro de notice : A2015-909 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.52638/rfpt.2015.550 En ligne : https://doi.org/10.52638/rfpt.2015.550 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79569
in Revue Française de Photogrammétrie et de Télédétection > n° 211 - 212 (juillet - décembre 2015) . - pp 119 - 128[article]Genetic differentiation of European larch along an altitudinal gradient in the French Alps / Maxime Nardin in Annals of Forest Science, vol 72 n° 5 (July 2015)
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Titre : Genetic differentiation of European larch along an altitudinal gradient in the French Alps Type de document : Article/Communication Auteurs : Maxime Nardin, Auteur ; Brigitte Musch, Auteur ; Yves Rousselle, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 517-527 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] Alpes (France)
[Termes IGN] altitude
[Termes IGN] cambium
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] diversité génétique
[Termes IGN] génétique
[Termes IGN] gradient
[Termes IGN] Larix decidua
[Termes IGN] montagne
[Termes IGN] placette d'échantillonnage
[Termes IGN] variabilité génétiqueRésumé : (Auteur) Key message : Despite variable dynamics of genetic diversification at the different altitudinal levels, strong gene flow tends to standardize larch genetic diversity: the larch forest distributed along the altitudinal gradient can be regarded as a single population.
Context : While in forest tree species many studies focus on the structure of the genetic diversity at the natural range and at the forest stand levels, few studies have worked at intermediate levels like the landscape level.
Aims : We tried to determine to what degree altitude variation can affect the genetic diversity and the local structure of the genetic diversity of European larch (Larix decidua Miller) at the landscape level.
Methods : Using microsatellite markers, we determined the between- and within-plot genetic structure and the spatial genetic structure (SGS) of four altitudinal plots distributed between 1,350 and 2,300 m a.s.l. in a European larch forest located in the French Alps.
Results : A homogenous neutral genetic structure was detected along this gradient. The intensity of the SGS was found to be stronger at 2,300 m and decreased at the 2,000-m plot. It was low or non-existent at the 1,700- and 1,350-m altitudinal levels.
Conclusion : Our results suggest that the genetic structure observed at the landscape level in this European larch forest was only slightly affected by climatic variation, human activities, or historical events. However, the variation of intensity of the SGS within the altitudinal plots indicates the existence of variable genetic dynamics, despite the globally uniform genetic structure along the altitudinal gradient.Numéro de notice : A2015-413 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-015-0483-8 Date de publication en ligne : 30/04/2015 En ligne : https://doi.org/10.1007/s13595-015-0483-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76903
in Annals of Forest Science > vol 72 n° 5 (July 2015) . - pp 517-527[article]A novel negative abundance‐oriented hyperspectral unmixing algorithm / Rubén Marrero in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
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Titre : A novel negative abundance‐oriented hyperspectral unmixing algorithm Type de document : Article/Communication Auteurs : Rubén Marrero, Auteur ; Sebastian Lopez, Auteur ; Gustavo Callicó, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 3772 - 3790 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image hyperspectrale
[Termes IGN] propagation d'erreur
[Termes IGN] variabilitéRésumé : (Auteur) Spectral unmixing is a popular technique for analyzing remotely sensed hyperspectral data sets with subpixel precision. Over the last few years, many algorithms have been developed for each of the main processing steps involved in spectral unmixing (SU) under the LMM assumption: 1) estimation of the number of endmembers; 2) identification of the spectral signatures of the endmembers; and 3) estimation of the abundance of endmembers in the scene. Although this general processing chain has proven to be effective for unmixing certain types of hyperspectral images, it also has some drawbacks. The first one comes from the fact that the output of each stage is the input of the following one, which favors the propagation of errors within the unmixing chain. A second problem is the huge variability of the results obtained when estimating the number of endmembers of a hyperspectral scene with different state-of-the-art algorithms, which influences the rest of the process. A third issue is the computational complexity of the whole process. To address the aforementioned issues, this paper develops a novel negative abundance-oriented SU algorithm that covers, for the first time in the literature, the main steps involved in traditional hyperspectral unmixing chains. The proposed algorithm can also be easily adapted to a scenario in which the number of endmembers is known in advance and two additional variations of the algorithm are provided to deal with high-noise scenarios and to significantly reduce its execution time, respectively. Our experimental results, conducted using both synthetic and real hyperspectral scenes, indicate that the presented method is highly competitive (in terms of both unmixing accuracy and computational performance) with regard to other SU techniques with similar requirements, while providing a fully self-contained unmixing chain without the need for any input parameters. Numéro de notice : A2015-317 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2383440 En ligne : https://doi.org/10.1109/TGRS.2014.2383440 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76567
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 7 (July 2015) . - pp 3772 - 3790[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015071 RAB Revue Centre de documentation En réserve L003 Disponible Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data / Laven Naidoo in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
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Titre : Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data Type de document : Article/Communication Auteurs : Laven Naidoo, Auteur ; Renaud Mathieu, Auteur ; Russell Main, Auteur ; Waldo Kleynhans, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 234 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Afrique du sud (état)
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] bande X
[Termes IGN] biomasse
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image TerraSAR-X
[Termes IGN] savaneRésumé : (auteur) Structural parameters of the woody component in African savannahs provide estimates of carbon stocks that are vital to the understanding of fuelwood reserves, which is the primary source of energy for 90% of households in South Africa (80% in Sub-Saharan Africa) and are at risk of over utilisation. The woody component can be characterised by various quantifiable woody structural parameters, such as tree cover, tree height, above ground biomass (AGB) or canopy volume, each been useful for different purposes. In contrast to the limited spatial coverage of ground-based approaches, remote sensing has the ability to sense the high spatio-temporal variability of e.g. woody canopy height, cover and biomass, as well as species diversity and phenological status – a defining but challenging set of characteristics typical of African savannahs. Active remote sensing systems (e.g. Light Detection and Ranging – LiDAR; Synthetic Aperture Radar – SAR), on the other hand, may be more effective in quantifying the savannah woody component because of their ability to sense within-canopy properties of the vegetation and its insensitivity to atmosphere and clouds and shadows. Additionally, the various components of a particular target’s structure can be sensed differently with SAR depending on the frequency or wavelength of the sensor being utilised. This study sought to test and compare the accuracy of modelling, in a Random Forest machine learning environment, woody above ground biomass (AGB), canopy cover (CC) and total canopy volume (TCV) in South African savannahs using a combination of X-band (TerraSAR-X), C-band (RADARSAT-2) and L-band (ALOS PALSAR) radar datasets. Training and validation data were derived from airborne LiDAR data to evaluate the SAR modelling accuracies. It was concluded that the L-band SAR frequency was more effective in the modelling of the CC (coefficient of determination or R2 of 0.77), TCV (R2 of 0.79) and AGB (R2 of 0.78) metrics in Southern African savannahs than the shorter wavelengths (X- and C-band) both as individual and combined (X + C-band) datasets. The addition of the shortest wavelengths also did not assist in the overall reduction of prediction error across different vegetation conditions (e.g. dense forested conditions, the dense shrubby layer and sparsely vegetated conditions). Although the integration of all three frequencies (X + C + L-band) yielded the best overall results for all three metrics (R2 = 0.83 for CC and AGB and R2 = 0.85 for TCV), the improvements were noticeable but marginal in comparison to the L-band alone. The results, thus, do not warrant the acquisition of all three SAR frequency datasets for tree structure monitoring in this environment. Numéro de notice : A2015-713 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78353
in ISPRS Journal of photogrammetry and remote sensing > vol 105 (July 2015) . - pp 234 - 250[article]Semisupervised transfer component analysis for domain adaptation in remote sensing image classification / Giona Matasci in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
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Titre : Semisupervised transfer component analysis for domain adaptation in remote sensing image classification Type de document : Article/Communication Auteurs : Giona Matasci, Auteur ; Michele Volpi, Auteur ; Mikhail Kanevski, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 3550 - 3564 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] classification à base de connaissances
[Termes IGN] classification automatique
[Termes IGN] découverte de connaissances
[Termes IGN] extraction automatique
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] occupation du solRésumé : (Auteur) In this paper, we study the problem of feature extraction for knowledge transfer between multiple remotely sensed images in the context of land-cover classification. Several factors such as illumination, atmospheric, and ground conditions cause radiometric differences between images of similar scenes acquired on different geographical areas or over the same scene but at different time instants. Accordingly, a change in the probability distributions of the classes is observed. The purpose of this work is to statistically align in the feature space an image of interest that still has to be classified (the target image) to another image whose ground truth is already available (the source image). Following a specifically designed feature extraction step applied to both images, we show that classifiers trained on the source image can successfully predict the classes of the target image despite the shift that has occurred. In this context, we analyze a recently proposed domain adaptation method aiming at reducing the distance between domains, Transfer Component Analysis, and assess the potential of its unsupervised and semisupervised implementations. In particular, with a dedicated study of its key additional objectives, namely the alignment of the projection with the labels and the preservation of the local data structures, we demonstrate the advantages of Semisupervised Transfer Component Analysis. We compare this approach with other both linear and kernel-based feature extraction techniques. Experiments on multi- and hyperspectral acquisitions show remarkable cross- image classification performances for the considered strategy, thus confirming its suitability when applied to remotely sensed images. Numéro de notice : A2015-319 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2377785 En ligne : https://doi.org/10.1109/TGRS.2014.2377785 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76570
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 7 (July 2015) . - pp 3550 - 3564[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015071 RAB Revue Centre de documentation En réserve L003 Disponible Subsidence monitoring in coal area using time-series InSAR combining persistent scatterers and distributed scatterers / Zhengjia Zhang in International journal of applied Earth observation and geoinformation, vol 39 (July 2015)
PermalinkThe full-scale avalanche test-site at Lautaret Pass (French Alps) / Emmanuel Thibert in Cold regions science and technology, vol 115 (July 2015)
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PermalinkToward evaluating multiscale segmentations of high spatial resolution remote sensing images / Xueliang Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
PermalinkDetermination of the spatial structure of vegetation on the repository of the mine “Fryderyk” in Tarnowskie Góry, based on airborne laser scanning from the ISOK project and digital orthophotomaps / Marta Szostak in Geodesy and cartography, vol 64 n° 1 (June 2015)
PermalinkLandscape monitoring of post-industrial areas using LiDAR and GIS technology / Piotr Wezyk in Geodesy and cartography, vol 64 n° 1 (June 2015)
PermalinkAccuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo / Xinging Li in Journal of geodesy, vol 89 n° 6 (June 2015)
PermalinkPermalinkenviroCar: A citizen science platform for analyzing and mapping crowd-sourced car sensor data / Arne Bröring in Transactions in GIS, vol 19 n° 3 (June 2015)
PermalinkNeighborhood greenspace and health in a large urban center / Omid Kardan in Scientific reports, vol 5 (2015)
PermalinkPOI Pulse: A multi-granular, semantic signature–based information observatory for the interactive visualization of big geosocial data / Grant McKenzie in Cartographica, vol 50 n° 2 (Summer 2015)
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