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Termes IGN > mathématiques > statistique mathématique
statistique mathématique
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biométrie,
échantillonnage (statistique), probabilité, statistique. >>Terme(s) spécifique(s) : analyse de régression, analyse de variance, analyse des données, analyse multivariée, analyse séquentielle, calcul d'erreur, carré latin, corrélation (statistique), efficacité asymptotique (statistique), fonction pseudo-aléatoire, loi des grands nombres, modèle linéaire (statistique), modèle non linéaire (statistique), moindre carré, physique statistique, plan d'expérience, rang et sélection (statistique), rupture (statistique), SAS (logiciel), série chronologique, statistique non paramétrique, statistique robuste, tableau de contingence, test d'hypothèses (statistique), statistique stellaire. Equiv. LCSH : Mathematical statistics. Domaine(s) : 510. |
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CAVIAR: an R package for checking, displaying and processing wood-formation-monitoring data / Cyrille B.K. Rathgeber in Tree Physiology, vol 38 n° 8 (August 2018)
[article]
Titre : CAVIAR: an R package for checking, displaying and processing wood-formation-monitoring data Type de document : Article/Communication Auteurs : Cyrille B.K. Rathgeber, Auteur ; Philippe Santenoise, Auteur ; Henri E. Cuny , Auteur Année de publication : 2018 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : pp 1246 - 1260 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne
[Termes IGN] données allométriques
[Termes IGN] dynamique de la végétation
[Termes IGN] forêt boréale
[Termes IGN] forêt tempérée
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Loi de Gompertz
[Termes IGN] phénologie
[Termes IGN] Pinophyta
[Termes IGN] R (langage)
[Termes IGN] régression logistique
[Termes IGN] visualisation de données
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) In the last decade, the pervasive question of climate change impacts on forests has revived investigations on intra-annual dynamics of wood formation, involving disciplines such as plant ecology, tree physiology and dendrochronology. This resulted in the creation of many research groups working on this topic worldwide and a rapid increase in the number of studies and publications. Wood-formation-monitoring studies are generally based on a common conceptual model describing xylem cell formation as the succession of four differentiation phases (cell division, cell enlargement, cell wall thickening and mature cells). They generally use the same sampling techniques, sample preparation methods and anatomical criteria to separate between differentiation zones and discriminate and count forming xylem cells, resulting in very similar raw data. However, the way these raw data are then processed, producing the elaborated data on which statistical analyses are performed, still remains quite specific to each individual study. Thereby, despite very similar raw data, wood-formation-monitoring studies yield results that are still quite difficult to compare. CAVIAR—an R package specifically dedicated to the verification, visualization and manipulation of wood-formation-monitoring data—can help to improve this situation. Initially, CAVIAR was built to provide efficient algorithms to compute critical dates of wood formation phenology for conifers growing in temperate and cold environments. Recently, we developed it further to check, display and process wood-formation-monitoring data. Thanks to new and upgraded functions, raw data can now be consistently verified, standardized and modelled (using logistic regressions and Gompertz functions), in order to describe wood phenology and intra-annual dynamics of tree-ring formation. We believe that CAVIAR will help strengthening the science of wood formation dynamics by effectively contributing to the standardization of its concepts and methods, making thereby possible the comparison between data and results from different studies. Numéro de notice : A2018-657 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/treephys/tpy054 Date de publication en ligne : 19/05/2018 En ligne : https://doi.org/10.1093/treephys/tpy054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93813
in Tree Physiology > vol 38 n° 8 (August 2018) . - pp 1246 - 1260[article]A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 8 (August 2018)
[article]
Titre : A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification Type de document : Article/Communication Auteurs : Zhen Wang, Auteur ; Liqiang Zhang, Auteur ; Liang Zhang, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 4594 - 4604 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] arbre aléatoire
[Termes IGN] classification par réseau neuronal
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] méthode robuste
[Termes IGN] Perceptron multicouche
[Termes IGN] pondération
[Termes IGN] précision de la classification
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsMots-clés libres : deep neural network with spatial pooling (DNNSP) Résumé : (Auteur) The large number of object categories and many overlapping or closely neighboring objects in large-scale urban scenes pose great challenges in point cloud classification. Most works in deep learning have achieved a great success on regular input representations, but they are hard to be directly applied to classify point clouds due to the irregularity and inhomogeneity of the data. In this paper, a deep neural network with spatial pooling (DNNSP) is proposed to classify large-scale point clouds without rasterization. The DNNSP first obtains the point-based feature descriptors of all points in each point cluster. The distance minimum spanning tree-based pooling is then applied in the point feature representation to describe the spatial information among the points in the point clusters. The max pooling is next employed to aggregate the point-based features into the cluster-based features. To assure the DNNSP is invariant to the point permutation and sizes of the point clusters, the point-based feature representation is determined by the multilayer perception (MLP) and the weight sharing for each point is retained, which means that the weight of each point in the same layer is the same. In this way, the DNNSP can learn the features of points scaled from the entire regions to the centers of the point clusters, which makes the point cluster-based feature representations robust and discriminative. Finally, the cluster-based features are input to another MLP for point cloud classification. We have evaluated qualitatively and quantitatively the proposed method using several airborne laser scanning and terrestrial laser scanning point cloud data sets. The experimental results have demonstrated the effectiveness of our method in improving classification accuracy. Numéro de notice : A2018-471 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2829625 Date de publication en ligne : 22/05/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2829625 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91253
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 8 (August 2018) . - pp 4594 - 4604[article]Detecting newly grown tree leaves from unmanned-aerial-vehicle images using hyperspectral target detection techniques / Chinsu Lin in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
[article]
Titre : Detecting newly grown tree leaves from unmanned-aerial-vehicle images using hyperspectral target detection techniques Type de document : Article/Communication Auteurs : Chinsu Lin, Auteur ; Shih-Yu Chen, Auteur ; Chia-Chun Chen, Auteur ; Chia-Huei Tai, Auteur Année de publication : 2018 Article en page(s) : pp 174 - 189 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse d'image orientée objet
[Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] drone
[Termes IGN] feuille (végétation)
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image RVB
[Termes IGN] indice de végétation
[Termes IGN] Kappa de Cohen
[Termes IGN] Taïwan
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Phenological events of tree leaves from initiation to senescence is generally influenced by temperature and water availability. Detection of newly grown leaves (NGL) is useful in the diagnosis of growth of trees, tree stress and even climatic change. Utilizing very high resolution UAV images, this paper examines the feasibility of NGL detection using hyperspectral detection algorithms and anomaly detectors. The issues of pixel resolution and hard decision thresholding in deriving accurate NGL maps are also explored. Results showed that the blind-detection algorithms RXDs are not suitable for NGL detection due to the spectra similarity between NGL and both mature leaves and grass, while brighter pixels, such as those produced by soil and concrete materials, are more easily recognized as anomaly in contrast to forest. Matching filter (MF) based detectors are, however, able to accurately detect NGL over forest stands and are even more effective in the sense of achieving satisfactory true positives and true negatives while providing minimal false alarms. Of the tested partial knowledge MF algorithms, the covariance matched filter based distance (KMFD) detector performed very well with overall accuracy (OA) 0.97 and kappa coefficient () 0.60 on a natural resolution of 6.75 cm image. When a variety of mature-leaf nonobjective targets are included in the detection, the orthogonal subspace projector (OSP) tends to suppress NGL pixels as an unwanted signature and this leads to poor detection. Conversely, the target constrained interference minimized filter (TCIMF) detector is still able to effectively detect NGL with a satisfactory OA and through effective matching filter of the target signature as the hard-decision threshold is subject to a level of 5% or 1% probability of false alarms. From decimeter resolution satellite images, the KMFD and TCIMF detectors are capable of achieving an accuracy of OA = 0.94 and = 0.56 or OA = 0.87 and = 0.48 for images with a resolution of 33.75 cm or 67.50 cm respectively. This indicates that hyperspectral target detection techniques have great potential in NGL detection via high spatial resolution satellite multispectral images. Numéro de notice : A2018-294 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.022 Date de publication en ligne : 15/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90412
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 174 - 189[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Digital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level / Tristan R.H. Goodbody in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
[article]
Titre : Digital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level Type de document : Article/Communication Auteurs : Tristan R.H. Goodbody, Auteur ; Nicholas C. Coops, Auteur ; Txomin Hermosilla, Auteur ; Piotr Tompalski, Auteur ; Grant MacCartney, Auteur ; David A. MacLean, Auteur Année de publication : 2018 Article en page(s) : pp 1 - 11 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] défoliation
[Termes IGN] dégradation de la flore
[Termes IGN] échantillonnage d'image
[Termes IGN] insecte nuisible
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] méthode des moindres carrés
[Termes IGN] Ontario (Canada)
[Termes IGN] photogrammétrie aérienne
[Termes IGN] photogrammétrie numérique
[Termes IGN] Picea abies
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] surface terrière
[Termes IGN] surveillance forestière
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Spruce budworm (Choristoneura fumiferana [Clem.], Lepidoptera: Tortricidae) is a native defoliating insect with an important disturbance role in the eastern boreal forests of North America. With an extensive history of outbreaks and associated impacts on forest structural changes and timber supply, the mapping of spruce budworm defoliation has been of major management importance. In this study we assessed the ability of high spatial resolution digital aerial photogrammetric (DAP) data to predict cumulative defoliation as well as basal area and merchantable volume in spruce budworm host stands in the Gordon Cosens Forest south of Kapuskasing, Ontario, Canada. To do so, DAP derived structural and spectral metrics were incorporated to implement a stratified sampling design to improve the efficiency and cost-effectiveness of field surveying. Standard forest inventory measurements including diameter and height, as well as ocular and branch level defoliation assessments were undertaken on thirty 400 m2 radius plots. A partial least squares analysis was performed to determine whether structural metrics from a DAP point cloud could be influenced by spruce budworm defoliation, as well as determine the relative effectiveness of spectral (e.g. mean NDVI) vs. structural (e.g. 90th percentile of height) metrics, or their combination, for predicting cumulative defoliation. Results indicated that spectral metrics were the most effective for predicting cumulative defoliation (R2 = 0.79), while structural metrics were the least effective (R2 = 0.49). Metrics characterizing variance of the spectral values were found to be the most important predictors. Structural metrics and linear regression were also used to estimate landscape-level volume and basal area per hectare yielding R2 = 0.80 and R2 = 0.90, respectively. Outcomes of this analysis indicate that DAP-derived spectral metrics were more capable of modeling cumulative defoliation, while structural metrics were effective for landscape-level estimations of standard forest inventory attributes. This analysis indicated that the provision of both spectral and structural metrics from a single aerial imagery survey has potential to enhance defoliation monitoring and forest attribute modeling at a landscape-level. Numéro de notice : A2018-290 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.012 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90408
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 1 - 11[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators / Pekka Hyvönen in Silva fennica, vol 52 n° 3 ([01/08/2018])
[article]
Titre : Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators Type de document : Article/Communication Auteurs : Pekka Hyvönen, Auteur ; Jaakko Heinonen, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] dommage matériel
[Termes IGN] estimateur
[Termes IGN] Finlande
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Termes IGN] plan de volMots-clés libres : Théorème central limite Résumé : (Auteur) Climate change has been estimated to increase the risk of storm damage in forests in Finland. There is a growing need for methods to obtain information on the extent and severity of storm damage after a storm occurrence. The first objective of this study was to test whether digital photographs taken from aircrafts flying at low-altitude can be utilized in locating storm-damaged areas and estimating the need for harvesting of wind-thrown trees. The second objective was to test the performance of selected estimators. Depending on distances between flight lines, plots on lines and the used estimator, the relative standard errors of storm area estimates varied between 7.7 and 48.7%. For the area for harvesting and volume of wind-thrown trees, the relative standard errors of estimates varied between 16.8 and 167.3%. Using forest area information from Multisource National Forest Inventory data improved the accuracy of the estimates. However, performance of a simple random sampling estimator and ratio estimator were quite similar. Lindeberg’s method for variance estimation based on adjacent lines was sensitive to line directions in relation to possible trends in storm-damaged area locations. Our results showed that the tested method could be used in estimating storm-damaged area provided that the network of flight lines and photographs on lines are sufficiently dense. The developed model for simulations can be utilized also with forthcoming storms as model’s parameters can be freely adjusted to meet, e.g., the intensity and extent of the storm. Numéro de notice : A2018-508 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14214/sf.7710 Date de publication en ligne : 05/06/2018 En ligne : https://doi.org/10.14214/sf.7710 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91189
in Silva fennica > vol 52 n° 3 [01/08/2018][article]Incorporating tree- and stand-level information on crown base height into multivariate forest management inventories based on airborne laser scanning / Matti Maltamo in Silva fennica, vol 52 n° 3 ([01/08/2018])PermalinkIntra-annual phenology for detecting understory plant invasion in urban forests / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkMonitoring climate sensitivity shifts in tree-rings of Eastern Boreal North America using model-data comparison : Shifts in tree growth sensivity to climate / Clémentine Ols in Ecosystems, vol 21 n° 5 (August 2018)PermalinkA spatial analysis of non‐English Twitter activity in Houston, TX / Matthew Haffner in Transactions in GIS, vol 22 n° 4 (August 2018)PermalinkSpectral-spatial classification of hyperspectral images using wavelet transform and hidden Markov random fields / Elham Kordi Ghasrodashti in Geocarto international, vol 33 n° 8 (August 2018)PermalinkTask-oriented visualization approaches for landscape and urban change analysis / Jochen Schiewe in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)PermalinkThe problem of double longitudes on Glavač’s map / Marina Viličić in Cartographic journal (the), Vol 55 n° 3 (August 2018)PermalinkThree-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint / Fangning He in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkUnsupervised detection of ruptures in spatial relationships in video sequences based on log‑likelihood ratio / Abdalbassir Abou-Elailah in Pattern Analysis and Applications, vol 21 n° 3 (August 2018)PermalinkAdaptive stopping criterion for top-down segmentation of ALS point clouds in temperate coniferous forests / Nina Amiri in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)PermalinkAssociation rules-based multivariate analysis and visualization of spatiotemporal climate data / Feng Wang in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)PermalinkDifferential positioning based on the orthogonal transformation algorithm with GNSS multi-system / Xiao Liang in GPS solutions, vol 22 n° 3 (July 2018)PermalinkHierarchical cellular automata for visual saliency / Yao Qin in International journal of computer vision, vol 126 n° 7 (July 2018)PermalinkHuman mobility semantics analysis : a probabilistic and scalable approach / Xiaohui Guo in Geoinformatica, vol 22 n° 3 (July 2018)PermalinkParametric bootstrap estimators for hybrid inference in forest inventories / Mathieu Fortin in Forestry, an international journal of forest research, vol 91 n° 3 (July 2018)PermalinkA review of accuracy assesment for object-based image analysis: from per pixel to per-polygon approaches [review article] / Su Ye in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)PermalinkRevisit the calibration errors on experimental slant total electron content (TEC) determined with GPS / Wenfeng Nie in GPS solutions, vol 22 n° 3 (July 2018)PermalinkA sequential network approach for estimating GPS satellite phase biases at the PPP-AR producer-side / Omid Kamali in GPS solutions, vol 22 n° 3 (July 2018)PermalinkStochastic models in the DORIS position time series : estimates for IDS contribution to ITRF2014 / Anna Klos in Journal of geodesy, vol 92 n° 7 (July 2018)PermalinkThe impact of solid Earth-tide model error on tropospheric zenith delay estimates and GPS coordinate time series / Fei Li in Survey review, vol 50 n° 361 (July 2018)PermalinkUsing interactions and dynamics for mining groups of moving objects from trajectory data / Corrado Loglisci in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)PermalinkApplication of deep learning for object detection / Ajeet Ram Pathak in Procedia Computer Science, vol 132 (2018)PermalinkAssessment of Sentinel-1A data for rice crop classification using random forests and support vector machines / Nguyen-Thanh Son in Geocarto international, vol 33 n° 6 (June 2018)PermalinkClassification à très large échelle d’images satellites à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkFusion tardive d’images SPOT 6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkGeometric reasoning with uncertain polygonal faces / Jochen Meidow in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)PermalinkGPS receiver phase biases estimable in PPP-RTK networks : dynamic characterization and impact analysis / Baocheng Zhang in Journal of geodesy, vol 92 n° 6 (June 2018)PermalinkInference on forest attributes and ecological diversity of trees outside forest by a two-phase inventory / Marco Marchetti in Annals of Forest Science, vol 75 n° 2 (June 2018)PermalinkInfluences of environmental loading corrections on the nonlinear variations and velocity uncertainties for the reprocessed global positioning system height time series of the crustal movement observation network of China / Peng Yuan in Remote sensing, vol 10 n° 6 (June 2018)PermalinkLive fuel moisture content (LFMC) time series for multiple sites and species in the French Mediterranean area since 1996 / N. Martin-St Paul in Annals of Forest Science, vol 75 n° 2 (June 2018)PermalinkMapping rubber trees based on phenological analysis of Landsat time series data-sets / Janatul Aziera binti Abd Razak in Geocarto international, vol 33 n° 6 (June 2018)PermalinkModeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data / Manuel Arias-Rodil in Annals of Forest Science, vol 75 n° 2 (June 2018)PermalinkOn the impact of GNSS ambiguity resolution: geometry, ionosphere, time and biases / Amir Khodabandeh in Journal of geodesy, vol 92 n° 6 (June 2018)PermalinkPost-1980 shifts in the sensitivity of boreal tree growth to North Atlantic Ocean dynamics and seasonal climate / Clémentine Ols in Global and Planetary Change, vol 165 (June 2018)PermalinkRange-image: Incorporating sensor topology for lidar point cloud processing / Pierre Biasutti in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)PermalinkA simple line clustering method for spatial analysis with origin-destination data and its application to bike-sharing movement data / Biao He in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)PermalinkSpatially sensitive statistical shape analysis for pedestrian recognition from LIDAR data / Michalis A. Savelonas in Computer Vision and image understanding, vol 171 (June 2018)PermalinkThe efficiency of different outlier detection approaches in geodetic networks: case study for Pobednik statue / Mehmed Batilović in Geodetski vestnik, vol 62 n° 2 (June 2018)PermalinkThe German Forest Strategy 2020: Target achievement control using national forest inventory results / Martin Lorenz in Annals of forest research, vol 61 n° 2 (July - December 2018)PermalinkA voxel- and graph-based strategy for segmenting man-made infrastructures using perceptual grouping laws: comparison and evaluation / Yusheng Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)PermalinkWithin- and between-tree variation of wood density components in Pinus nigra at six sites in Portugal / Alexandra Dias in Annals of Forest Science, vol 75 n° 2 (June 2018)PermalinkToward automatic georeferencing of archival aerial photogrammetric surveys / Sébastien Giordano in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2 (June 2018)PermalinkAn object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery / Luis Angel Ruiz in Geocarto international, vol 33 n° 5 (May 2018)PermalinkClassifying airborne LiDAR point clouds via deep features learned by a multi-scale convolutional neural network / Ruibin Zhao in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)PermalinkComparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY / Dunya Alraddawi in Atmospheric measurement techniques, vol 11 n° 5 (May 2018)PermalinkComplexity reduction in choropleth map animations by autocorrelation weighted generalization of time-series data / Christoph Traun in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)PermalinkConnecting infrared spectra with plant traits to identify species / Maria F. Buitrago in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkDeep convolutional neural network training enrichment using multi-view object-based analysis of Unmanned Aerial systems imagery for wetlands classification / Tao Liu in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkDo semantic parts emerge in convolutional neural networks? / Abel Gonzalez-Garcia in International journal of computer vision, vol 126 n° 5 (May 2018)PermalinkExploring the sensitivity of coastal inundation modelling to DEM vertical error / Harry West in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)PermalinkGen*: a generic toolkit to generate spatially explicit synthetic populations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)PermalinkGeodetic VLBI with an artificial radio source on the Moon : a simulation study / Grzegorz Klopotek in Journal of geodesy, vol 92 n° 5 (May 2018)PermalinkA geometric-based approach for road matching on multi-scale datasets using a genetic algorithm / Alireza Chehreghan in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)PermalinkLarge-scale supervised learning for 3D Point cloud labeling : Semantic3d.Net / Timo Hackel in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 5 (mai 2018)PermalinkA new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkSeed dispersal, microsites or competition : what drives gap regeneration in an old-growth forest? An application of spatial point process modelling / Georg Gratzer in Forests, vol 9 n° 5 (May 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)PermalinkBinary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification / Rama Rao Nidamanuri in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkCarrier phase bias estimation of geometry-free linear combination of GNSS signals for ionospheric TEC modeling / Anna Krypiak-Gregorczyk in GPS solutions, vol 22 n° 2 (April 2018)PermalinkCrowdsourcing the character of a place : Character‐level convolutional networks for multilingual geographic text classification / Benjamin Adams in Transactions in GIS, vol 22 n° 2 (April 2018)PermalinkEffects of terrain slope and aspect on the error of ALS-based predictions of forest attributes / Hans Ole Ørka in Forestry, an international journal of forest research, vol 91 n° 2 (April 2018)PermalinkJoint estimation of vertical total electron content (VTEC) and satellite differential code biases (SDCBs) using low-cost receivers / Baocheng Zhang in Journal of geodesy, vol 92 n° 4 (April 2018)PermalinkJournées de la recherche IGN 2018 / Anonyme in Géomatique expert, n° 121 (mars - avril 2018)PermalinkMapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records / Zhang Liu in Transactions in GIS, vol 22 n° 2 (April 2018)PermalinkMapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data / Abel Chemura in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkA methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model / R. Klees in Journal of geodesy, vol 92 n° 4 (April 2018)PermalinkReal-time accurate 3D head tracking and pose estimation with consumer RGB-D cameras / David Joseph Tan in International journal of computer vision, vol 126 n° 2-4 (April 2018)PermalinkRevue des descripteurs tridimensionnels (3D) pour la catégorisation des nuages de points acquis avec un système LiDAR de télémétrie mobile / Sylvie Daniel in Geomatica, vol 72 n° 1 (March 2018)PermalinkToward a global horizontal and vertical elastic load deformation model derived from GRACE and GNSS station position time series / Kristel Chanard in Journal of geophysical research : Solid Earth, vol 123 n° 4 (April 2018)PermalinkArpent : un prototype de haute exactitude pour les mesures de grande distance / Maylis Teyssendier de la Serve in XYZ, n° 154 (mars - mai 2018)PermalinkCombining land cover products using a minimum divergence and a Bayesian data fusion approach / Sarah Gengler in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)PermalinkComparing nearest neighbor configurations in the prediction of species-specific diameter distributions / Janne Raty in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkContextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)PermalinkEstimated location of the seafloor sources of marine natural oil seeps from sea surface outbreaks : A new "source path procedure" applied to the northern Gulf of Mexico / Zhour Najoui in Marine and Petroleum Geology, Vol 91 (March 2018)PermalinkEuropean Forest Types: toward an automated classification / Francesca Giannetti in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkEvaluation of 10-year temporal and spatial variability in structure and growth across contrasting commercial thinning treatments in spruce-fir forests of northern Maine, USA / Christian Kuehne in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkHarmonic regression of Landsat time series for modeling attributes from national forest inventory data / Barry T. Wilson in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkImage classification-based ground filtering of point clouds extracted from UAV-based aerial photos / Volkan Yilmaz in Geocarto international, vol 33 n° 3 (March 2018)PermalinkImportant LiDAR metrics for discriminating forest tree species in Central Europe / Yifang Shi in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkKriging and moving window kriging on a sphere in geometric (GNSS/levelling) geoid modelling / M. Ligas in Survey review, vol 50 n° 359 (March 2018)PermalinkLong-term prediction of polar motion using a combined SSA and ARMA model / Y. Shen in Journal of geodesy, vol 92 n° 3 (March 2018)PermalinkMapping tree cover with Sentinel-2 data using the Support Vector Machine (SVM) / Anna Mirończuk in Geoinformation issues, Vol 9 n° 1 (2017)PermalinkReduction of ZTD outliers through improved GNSS data processing and screening strategies [Interactive discussion] / Katarzyna Stępniak in Atmospheric measurement techniques, vol 11 n° 3 (March 2018)PermalinkRegional geoid computation by least squares modified Hotine’s formula with additive corrections / Silja Märdla in Journal of geodesy, vol 92 n° 3 (March 2018)PermalinkRemote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data / Xiaojun Xu in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkSensitivity analysis of pansharpening in hyperspectral change detection / Seyd Teymoor Seydi in Applied geomatics, vol 10 n° 1 (March 2018)PermalinkSystematic error reduction in geometric measurements based on altimetric enrichment of geographical features / Jean-François Girres in Cartographica, vol 53 n° 1 (Spring 2018)PermalinkAnalyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkComparing the performance of flat and hierarchical Habitat/Land-Cover classification models in a NATURA 2000 site / Yoni Gavish in ISPRS Journal of photogrammetry and remote sensing, vol 136 (February 2018)PermalinkEPLA : efficient personal location anonymity / Dapeng Zhao in Geoinformatica, vol 22 n° 1 (January 2018)PermalinkExtraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkImproving the upscaling of land cover maps by fusing uncertainty and spatial structure information / Peijun Sun in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 2 (February 2018)PermalinkInterpreting the fuzzy semantics of natural-language spatial relation terms with the fuzzy random forest algorithm / Xiaonan Wang in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkLarge-scale remote sensing image retrieval by deep hashing neural networks / Yansheng Li in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkLRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification / Yuebin Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkMultisource remote sensing data classification based on convolutional neural network / Xiaodong Xu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkNouvelle méthode en cascade pour la classification hiérarchique multi-temporelle ou multi-capteur d'images satellitaires haute résolution / Ihsen Hedhli in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkPredicting temperate forest stand types using only structural profiles from discrete return airborne lidar / Melissa Fedrigo in ISPRS Journal of photogrammetry and remote sensing, vol 136 (February 2018)PermalinkActive learning-based optimized training library generation for object-oriented image classification / Rajeswari Balasubramaniam in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkAdapting an existing semi-automatized image processing chain to enable Sentinel-2 data classification. / Hiyam Elbadri (2018)PermalinkAn accurate Kriging-based regional ionospheric model using combined GPS/BeiDou observations / Mohamed Abdelazeem in Journal of applied geodesy, vol 12 n° 1 (January 2018)PermalinkAn (almost) automated process to track the Martians dunes : ac.GetPreciseShifts / Arthur Coqué (2018)PermalinkBayesian statistics and Monte Carlo methods / Karl Rudolf Koch in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkBilan de l’Action COST ES1206 - GNSS4SWEC (Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate) / Olivier Bock (2018)PermalinkBruit de scintillation dans les séries temporelles de positions GNSS : origines et conséquences / Paul Rebischung (2018)PermalinkCartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)PermalinkPermalinkClassification à très haute résolution (THR) spatiale et fusion d'occupation des sols (OCS) / Tristan Postadjian (2018)PermalinkClassification à très large échelle d'images satellite à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian (2018)PermalinkComparative study of visual saliency maps in the problem of classification of architectural images with Deep CNNs / Abraham Montoya Obeso (2018)PermalinkConception d’une méthode radar de suivi bimensuel des déforestations et d’une méthode optique de classification d’occupation des sols / Luc Baudoux (2018)PermalinkCrop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping / Simon Bailly (2018)PermalinkCut-Pursuit algorithm for regularizing nonsmooth functionals with graph total variation / Hugo Raguet (2018)PermalinkDecision fusion of SPOT6 and multitemporal Sentinel2 images for urban area detection / Cyril Wendl (2018)PermalinkDeep learning based vehicular mobility models for intelligent transportation systems / Jian Zhang (2018)PermalinkDependency of geodynamic parameters on the GNSS constellation / Stefano Scaramuzza in Journal of geodesy, vol 92 n° 1 (January 2018)PermalinkDesign and implementation of a model predictive observer for AHRS / Jafar Keighobadi in GPS solutions, vol 22 n° 1 (January 2018)PermalinkDetection and localization of traffic signals with GPS floating car data and Random Forest / Yann Méneroux (2018)PermalinkDétermination d’un modèle géopotentiel à haute résolution en zone littorale aidé par des mesures d’horloges atomiques / Hugo Lecomte (2018)PermalinkDomain adaptation for large scale classification of very high resolution satellite images with deep convolutional neural networks / Tristan Postadjian (2018)PermalinkPermalinkPermalinkPermalinkExploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)PermalinkExploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)PermalinkExploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation / Qi Zhou in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)PermalinkPermalinkFrom Google Maps to a fine-grained catalog of street trees / Steve Branson in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)PermalinkPermalinkFusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)PermalinkGéo-référencement précis d'acquisition photogrammétrique de « longues » scènes d'intérieur / Truong Giang Nguyen (2018)PermalinkGéolocalisation précise basée image : une approche de type “seconde itération du processus photogrammétrique” / Truong Giang Nguyen (2018)PermalinkGeometric multi-wavelet total variation for SAR image time series analysis / Abdourrahmane M. Atto (2018)PermalinkPermalinkHeight biases of SRTM DEM related to EGM96: from a global perspective to regional practice / A. Üstün in Survey review, vol 50 n° 358 (January 2018)PermalinkA hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning / Rasmus M. Houborg in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)PermalinkPermalinkIntroduction to multiple regression equations in datum transformations and their reversibility / Andrew Carey Ruffhead in Survey review, vol 50 n° 358 (January 2018)PermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkPermalinkLearning multiscale deep features for high-resolution satellite image scene classification / Qingshan Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkLeveraging correlation across space and time to interpolate geophysical data via CoKriging / Sonja Pravilovic in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)PermalinkLocalisation d'objets urbains à partir de sources multiples dont des images aériennes / Lionel Pibre (2018)PermalinkLocalisation par l'image en milieu urbain : application à la réalité augmentée / Antoine Fond (2018)PermalinkMachine learning and pose estimation for autonomous robot grasping with collaborative robots / Victor Talbot (2018)PermalinkPermalinkMarkov random field for combined defogging and stereo reconstruction / Laurent Caraffa (2018)PermalinkMéthodes d'inventaire multisource : améliorer la précision des estimations de l'IFN et atteindre l'échelle des territoires [diaporama] / Cédric Vega (2018)PermalinkMixed integer–real least squares estimation for precise GNSS positioning using a modified ambiguity function approach / Krzysztof Nowel in GPS solutions, vol 22 n° 1 (January 2018)PermalinkPermalinkModélisation spatio-temporelle multi-niveau à base d'ontologies pour le suivi de la dynamique en imagerie satellitaire / Fethi Ghazouani (2018)PermalinkNavigation des personnes aux moyens des technologies des smartphones et des données d’environnements cartographiés / Fadoua Taia Alaoui (2018)PermalinkA numerical test of the topographic bias / Lars E. Sjöberg in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkObject-based superresolution land-cover mapping from remotely sensed imagery / Yuehong Chen in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkOn the topographic bias and density distribution in modelling the geoid and orthometric heights / Lars E. Sjöberg in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkParameter estimation with GNSS-reflectometry and GNSS synthetic aperture techniques / Miguel Angel Ribot Sanfelix (2018)PermalinkA posteriori bias correction of three models used for environmental reporting / Bogdan M. Strimbu in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)PermalinkPermalinkPermalinkQGIS in Remote Sensing, Volume 2. QGIS and applications in agriculture and forest / Nicolas Baghdadi (2018)PermalinkQuelles recherches pour et avec l'Inventaire Forestier National ? [diaporama] / François Houllier (2018)PermalinkPermalinkRéseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne / Jean Ogier du Terrail (2018)PermalinkPermalinkSatellite remote sensing of the variability of the continental hydrology cycle in the lower Mekong basin over the last two decades / Binh Pham-Duc (2018)PermalinkPermalinkPermalinkSpatio-temporal grid mining applied to image classification and cellular automata analysis / Romain Deville (2018)PermalinkA stixel approach for enhancing semantic image segmentation using prior map information / Sylvain Jonchery (2018)PermalinkSuivi des cultures dans le périmètre du Loukkos-Maroc : Apport de la télédétection radar et optique / Siham Acharki (2018)PermalinkSuivi écologique des prairies semi-naturelles : analyse statistique de séries temporelles denses d’images satellite à haute résolution spatiale / Maylis Lopes (2018)PermalinkSuperpixel partitioning of very high resolution satellite images for large-scale classification perspectives with deep convolutional neural networks / Tristan Postadjian (2018)PermalinkSuperPoint Graph : segmentation sémantique de nuages de points LiDAR à grande échelle / Loïc Landrieu (2018)PermalinkSynergie des données Sentinel optiques et radar pour l’observation et l’analyse de la végétation du littoral du Pays de Brest / Antoine Billey (2018)PermalinkTélédétection multispectrale et hyperspectrale des eaux littorales turbides / Morgane Larnicol (2018)PermalinkTesting deformation hypotheses by constraints on a time series of geodetic observations / Hiddo Velsink in Journal of applied geodesy, vol 12 n° 1 (January 2018)PermalinkThe effect of regional sea level atmospheric pressure on sea level variations at globally distributed tide gauge stations with long records / Huseyin Baki Iz in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkPermalinkUse of satellite image classifications to update and enhance a land cover database / Mohamed Touiti (2018)PermalinkL’utilisation des données écologiques de l’inventaire pour mieux appréhender les conditions locales de milieu (atelier de travail) [diaporama] / Philippe Dreyfus (2018)PermalinkUtilisation de QGIS en télédétection, Ch. 2. Apports du MNT topo-bathymétrique pour l'évolution bio-géomorphologique des marais d'Ichkeul (Tunisie) / Zeineb Kassouk (2018)PermalinkUtilisation de QGIS en télédétection, Volume 2. QGIS et applications en agriculture et forêt / Nicolas Baghdadi (2018)PermalinkLe vandalisme dans l’information géographique volontaire : apprendre pour mieux détecter ? / Quy Thy Truong (2018)PermalinkVector-based approach for combining ascending and descending persistent scatterers interferometric point measurements / Michael Foumelis in Geocarto international, vol 33 n° 1 (January 2018)PermalinkPermalinkA wavelet decomposition and polynomial fitting-based method for the estimation of time-varying residual motion error in airborne interferometric SAR / Hai Qiang Fu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkBenefits of satellite clock modeling in BDS and Galileo orbit determination / Yun Qing in Advances in space research, vol 60 n° 12 (15 December 2017)PermalinkFactors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012 : The role of topography and drought / Juan José Vidal-Macua in Forest ecology and management, vol 406 (15 December 2017)PermalinkPerformance analysis of BDS/GPS precise point positioning with undifferenced ambiguity resolution / Min Wang in Advances in space research, vol 60 n° 12 (15 December 2017)PermalinkAbove-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China / Ran Jing in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkAlgebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)PermalinkAn effective ensemble classification framework using random forests and a correlation based feature selection technique / Dibyajyoti Chutia in Transactions in GIS, vol 21 n° 6 (December 2017)PermalinkArea-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)PermalinkBuilding extraction from fused LiDAR and hyperspectral data using Random Forest Algorithm / Saeid Parsian in Geomatica, vol 71 n° 4 (December 2017)PermalinkCongruence analysis of geodetic networks, hypothesis tests versus model selection by information criteria / Rüdiger Lehmann in Journal of applied geodesy, vol 11 n° 4 (December 2017)Permalink