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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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GipsyX/RTGx, a new tool set for space geodetic operations and research / Willy I. Bertiger in Advances in space research, vol 66 n° 3 (1 August 2020)
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[article]
Titre : GipsyX/RTGx, a new tool set for space geodetic operations and research Type de document : Article/Communication Auteurs : Willy I. Bertiger, Auteur ; Yoaz E. Bar-Sever, Auteur ; A. Dorsey, Auteur ; Bruce J. Haines, Auteur ; N.R. Harvey, Auteur ; Dan Hemberger, Auteur ; Michael B. Heflin, Auteur ; Wenwen Lu, Auteur ; Mark Miller, Auteur ; Angelyn Moore, Auteur ; Dave Murphy, Auteur ; Paul Ries, Auteur ; L.J. Romans, Auteur ; Aurore E. Sibois, Auteur ; Ant Sibthorpe, Auteur ; Bela Szilagyi, Auteur ; Michele Vallisneri, Auteur ; Pascal Willis , Auteur
Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : pp 469 - 489 Note générale : bibliographie
The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] données DORIS
[Termes IGN] données GNSS
[Termes IGN] données ITGB
[Termes IGN] données TLS (télémétrie)
[Termes IGN] filtre de Kalman
[Termes IGN] horloge atomique
[Termes IGN] horloge du satellite
[Termes IGN] logiciel d'orbitographie
[Termes IGN] positionnement ponctuel précis
[Termes IGN] série temporelle
[Termes IGN] temps réel
[Termes IGN] traitement de données GNSSRésumé : (auteur) GipsyX/RTGx is the Jet Propulsion Laboratory’s (JPL) next generation software package for positioning, navigation, timing, and Earth science using measurements from three geodetic techniques: Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS); with Very Long Baseline Interferometry (VLBI) under development. The software facilitates combined estimation of geodetic and geophysical parameters using a Kalman filter approach on real or simulated data in both post-processing and in real-time. The estimated parameters include station coordinates and velocities, satellite orbits and clocks, Earth orientation, ionospheric and tropospheric delays. The software is also capable of full realization of a dynamic terrestrial reference through analysis and combination of time series of ground station coordinates.
Applying lessons learned from its predecessors, GIPSY-OASIS and Real Time GIPSY (RTG), GipsyX/RTGx was re-designed from the ground up to offer improved precision, accuracy, usability, and operational flexibility. We present some key aspects of its new architecture, and describe some of its major applications, including Real-time orbit determination and ephemeris predictions in the U.S. Air Force Next Generation GPS Operational Control Segment (OCX), as well as in JPL’s Global Differential GPS (GDGPS) System, supporting User Range Error (URE) of
5 cm RMS; precision post-processing GNSS orbit determination, including JPL’s contributions to the International GNSS Service (IGS) with URE in the 2 cm RMS range; Precise point positioning (PPP) with ambiguity resolution, both statically and kinematically, for geodetic applications with 2 mm horizontal, and 6.5 mm vertical repeatability for static positioning; Operational orbit and clock determination for Low Earth Orbiting (LEO) satellites, such as NASA’s Gravity Recovery and Climate Experiment (GRACE) mission with GRACE relative clock alignment at the 20 ps level; calibration of radio occultation data from LEO satellites for weather forecasting and climate studies; Satellite Laser Ranging (SLR) to GNSS and LEO satellites, DORIS-based and multi-technique orbit determination for LEO; production of terrestrial reference frames and Earth rotation parameters in support of JPL’s contribution to the International Terrestrial Reference Frame (ITRF).Numéro de notice : A2020-575 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : INFORMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2020.04.015 Date de publication en ligne : 22/04/2020 En ligne : https://doi.org/10.1016/j.asr.2020.04.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96369
in Advances in space research > vol 66 n° 3 (1 August 2020) . - pp 469 - 489[article]How do species and data characteristics affect species distribution models and when to use environmental filtering? / Lukáš Gábor in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)
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Titre : How do species and data characteristics affect species distribution models and when to use environmental filtering? Type de document : Article/Communication Auteurs : Lukáš Gábor, Auteur ; Vítězslav Moudrý, Auteur ; Vojtěch Barták, Auteur ; Vincent Lecours, Auteur Année de publication : 2020 Article en page(s) : pp 1567 - 1584 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] distribution spatiale
[Termes IGN] données environnementales
[Termes IGN] données localisées
[Termes IGN] échantillonnage (statistique)
[Termes IGN] entropie maximale
[Termes IGN] erreur d'échantillon
[Termes IGN] filtrage d'information
[Termes IGN] interaction spatialeRésumé : (auteur) Species distribution models (SDMs) are widely used in ecology and conservation. However, their performance is known to be affected by a variety of factors related to species occurrence characteristics. In this study, we used a virtual species approach to overcome the difficulties associated with testing of combined effects of those factors on performance of presence-only SDMs when using real data. We focused on the individual and combined roles of factors related to response variable (i.e. sample size, sampling bias, environmental filtering, species prevalence, and species response to environmental gradients). Results suggest that environmental filtering is not necessarily helpful and should not be performed blindly, without evidence of bias in species occurrences. The more gradual the species response to environmental gradients is, the greater is the model sensitivity to an inappropriate use of environmental filtering, although this sensitivity decreases with higher species prevalence. Results show that SDMs are affected to the greatest degree by the species response to environmental gradients, species prevalence, and sample size. Models’ accuracy decreased with sample size below 300 presences. Furthermore, a high level of interactions among individual factors was observed. Ignoring the combined effects of factors may lead to misleading outcomes and conclusions. Numéro de notice : A2020-414 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1615070 Date de publication en ligne : 14/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1615070 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95465
in International journal of geographical information science IJGIS > vol 34 n° 8 (August 2020) . - pp 1567 - 1584[article]Integration of airborne gravimetry data filtering into residual least-squares collocation: example from the 1 cm geoid experiment / Martin Willberg in Journal of geodesy, vol 94 n° 8 (August 2020)
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[article]
Titre : Integration of airborne gravimetry data filtering into residual least-squares collocation: example from the 1 cm geoid experiment Type de document : Article/Communication Auteurs : Martin Willberg, Auteur ; Philipp Zingerle, Auteur ; Roland Pail, Auteur Année de publication : 2020 Article en page(s) : n° 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] collocation par moindres carrés
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] filtre passe-bas
[Termes IGN] géoïde gravimétrique
[Termes IGN] géoïde local
[Termes IGN] gravimétrie aérienne
[Termes IGN] levé gravimétrique
[Termes IGN] modèle stochastique
[Termes IGN] pondération
[Termes IGN] processus gaussienRésumé : (auteur) Low-pass filters are commonly used for the processing of airborne gravity observations. In this paper, for the first time, we include the resulting correlations consistently in the functional and stochastic model of residual least-squares collocation. We demonstrate the necessity of removing high-frequency noise from airborne gravity observations, and derive corresponding parameters for a Gaussian low-pass filter. Thereby, we intend an optimal combination of terrestrial and airborne gravity observations in the mountainous area of Colorado. We validate the combination in the frame of our participation in ‘the 1 cm geoid experiment’. This regional geoid modeling inter-comparison exercise allows the calculation of a reference solution, which is defined as the mean value of 13 independent height anomaly results in this area. Our result performs among the best and with 7.5 mm shows the lowest standard deviation to the reference. From internal validation we furthermore conclude that the input from airborne and terrestrial gravity observations is consistent in large parts of the target area, but not necessarily in the highly mountainous areas. Therefore, the relative weighting between these two data sets turns out to be a main driver for the final result, and is an important factor in explaining the remaining differences between various height anomaly results in this experiment. Numéro de notice : A2020-536 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01396-2 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.1007/s00190-020-01396-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95729
in Journal of geodesy > vol 94 n° 8 (August 2020) . - n° 75[article]Landuse and land cover identification and disaggregating socio-economic data with convolutional neural network / Jingtao Yao in Geocarto international, vol 35 n° 10 ([01/08/2020])
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Titre : Landuse and land cover identification and disaggregating socio-economic data with convolutional neural network Type de document : Article/Communication Auteurs : Jingtao Yao, Auteur ; Xiangbin Kong, Auteur ; Rattan Lal, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1109 - 1123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] densité de population
[Termes IGN] désagrégation
[Termes IGN] données socio-économiques
[Termes IGN] image Landsat-8
[Termes IGN] occupation du sol
[Termes IGN] utilisation du solRésumé : (auteur) Numéro de notice : A2020-427 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1568587 Date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1568587 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95493
in Geocarto international > vol 35 n° 10 [01/08/2020] . - pp 1109 - 1123[article]Leveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
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Titre : Leveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction Type de document : Article/Communication Auteurs : Qing Zhu, Auteur ; Zhendong Wang, Auteur ; Han Hu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 26 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] appariement de points
[Termes IGN] éclairage
[Termes IGN] image aérienne
[Termes IGN] image terrestre
[Termes IGN] maillage
[Termes IGN] milieu urbain
[Termes IGN] modèle stéréoscopique
[Termes IGN] séparateur à vaste marge
[Termes IGN] valeur aberranteRésumé : (auteur) Integration of aerial and ground images has been proved as an efficient approach to enhance the surface reconstruction in urban environments. However, as the first step, the feature point matching between aerial and ground images is remarkably difficult, due to the large differences in viewpoint and illumination conditions. Previous studies based on geometry-aware image rectification have alleviated this problem, but the performance and convenience of this strategy are still limited by several flaws, e.g. quadratic image pairs, segregated extraction of descriptors and occlusions. To address these problems, we propose a novel approach: leveraging photogrammetric mesh models for aerial-ground image matching. The methods have linear time complexity with regard to the number of images. It explicitly handles low overlap using multi-view images. The proposed methods can be directly injected into off-the-shelf structure-from-motion (SFM) and multi-view stereo (MVS) solutions. First, aerial and ground images are reconstructed separately and initially co-registered through weak georeferencing data. Second, aerial models are rendered to the initial ground views, in which color, depth and normal images are obtained. Then, feature matching between synthesized and ground images are conducted through descriptor searching and geometry-constrained outlier removal. Finally, oriented 3D patches are formulated using the synthesized depth and normal images and the correspondences are propagated to the aerial views through patch-based matching. Experimental evaluations using five datasets reveal satisfactory performance of the proposed methods in aerial-ground image matching, which succeeds in all of the ten challenging pairs compared to only three for the second best. In addition, incorporation of existing SFM and MVS solutions enables more complete reconstruction results, with better internal stability. Numéro de notice : A2020-351 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.024 Date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.024 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95234
in ISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 26 - 40[article]Réservation
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PermalinkStochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty / Thanate Jongrujinan in Journal of applied geodesy, vol 14 n° 3 (July 2020)
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PermalinkA water identification method basing on grayscale Landsat 8 OLI images / Zhitian Deng in Geocarto international, vol 35 n° 7 ([15/05/2020])
PermalinkAn integrated approach to registration and fusion of hyperspectral and multispectral images / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
PermalinkApplying the environmental sensitivity index for the assessment of the prospective oil spills along the Nile Delta Coast, Egypt / Rasha M. Abou Samra in Geocarto international, vol 35 n° 6 ([01/05/2020])
PermalinkAssessing alternative methods for unsupervised segmentation of urban vegetation in very high-resolution multispectral aerial imagery / Allison Lassiter in Plos one, vol 15 n° 5 (May 2020)
PermalinkAssessment of winter season land surface temperature in the Himalayan regions around the Kullu area in India using Landsat-8 data / Divyesh Varade in Geocarto international, vol 35 n° 6 ([01/05/2020])
PermalinkAutomatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks / Mahmoud Saeedimoghaddam in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)
PermalinkComparing the roles of landmark visual salience and semantic salience in visual guidance during indoor wayfinding / Weihua Dong in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)
PermalinkA convolutional neural network with mapping layers for hyperspectral image classification / Rui Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
PermalinkDeep learning for enrichment of vector spatial databases: Application to highway interchange / Guillaume Touya in ACM Transactions on spatial algorithms and systems, TOSAS, vol 6 n° 3 (May 2020)
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PermalinkDelineating minor landslide displacements using GPS and terrestrial laser scanning-derived terrain surfaces and trees: a case study of the Slumgullion landslide, Lake City, Colorado / Jin Wang in Survey review, vol 52 n° 372 (May 2020)
PermalinkDiscrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF) / Su Shu in Marine geodesy, Vol 43 n° 3 (May 2020)
PermalinkExploring the potential of deep learning segmentation for mountain roads generalisation / Azelle Courtial in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)
PermalinkFootprint determination of a spectroradiometer mounted on an unmanned aircraft system / Deepak Gautam in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)
PermalinkHomogenizing GPS integrated water vapor time series: Benchmarking break detection methods on synthetic data sets / Roeland Van Malderen in Earth and space science, vol 7 n° 5 (May 2020)
PermalinkHow much do we learn from addresses? On the syntax, semantics and pragmatics of addressing systems / Ali Javidaneh in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)
PermalinkHyperspectral image clustering with Albedo recovery Fuzzy C-Means / Peyman Azimpour in International Journal of Remote Sensing IJRS, vol 41 n° 16 (01-10 May 2020)
PermalinkImproved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests / Sruthi M. Krishna Moorthy in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
PermalinkMethod for extraction of airborne LiDAR point cloud buildings based on segmentation / Maohua Liu in Plos one, vol 15 n° 5 (May 2020)
PermalinkOptimal lowest astronomical tide estimation using maximum likelihood estimator with multiple ocean models hybridization / Mohammed El-Diasty in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)
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