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Modeling of precipitable water vapor from GPS observations using machine learning and tomography methods / Mir Reza Ghaffari Razin in Advances in space research, vol 69 n° 7 (April 2022)  

Public [article]  inAdvances in space research > vol 69 n° 7 (April 2022) . - pp 2671 - 2681 Titre : Modeling of precipitable water vapor from GPS observations using machine learning and tomography methods Type de document : Article/Communication Auteurs : Mir Reza Ghaffari Razin, Auteur ; Behzad Voosoghi, Auteur Année de publication : 2022 Article en page(s) : pp 2671 - 2681 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] algorithme génétique [Termes IGN] apprentissage automatique [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] Inférence floue [Termes IGN] Iran [Termes IGN] précipitation [Termes IGN] radiosondage [Termes IGN] réseau neuronal artificiel [Termes IGN] retard hydrostatique [Termes IGN] retard troposphérique zénithal [Termes IGN] tomographie par GPS [Termes IGN] vapeur d'eau [Termes IGN] voxel Résumé : (auteur) This paper studies the application of two machine learning methods to model precipitable water vapor (PWV) using observations of 23 GPS stations from the local GPS network of north-west of Iran in 2011. In a first step, the zenith tropospheric delay (ZTD) and zenith hydrostatic delay (ZHD) is calculated with the Bernese GNSS software and Saastamoinen model as revised by Davis, respectively. Then, by subtracting the ZHD from the ZTD, the zenith wet delay (ZWD) is obtained at each GPS station, for all times. In a second step, ZWD is modeled by two different machine learning methods, based on the latitude, longitude, DOY, time, relative humidity, temperature and pressure. After training a Support Vector Machine (SVM) and an Artificial Neural Network (ANN), ZWD temporal and spatial variations are estimated. Using the formula by Bevis, the ZWD can be converted to PWV at any time and space, for each machine learning method. The accuracy of the two new models is evaluated using control stations, exterior and radiosonde station, whose observations were not used in the training step. Also, all the results of the SVM and ANN are compared with a voxel-based tomography (VBT) model. In the control and exterior stations, ZWD estimated by the SVM (ZWDSVM) and ANN (ZWDANN) is compared with the ZWD obtained from the GPS (ZWDGPS). Also, in the control and exterior stations, precise point positioning (PPP) is used to evaluate the accuracy of the new models. In the radiosonde station, the PWV of the new models (PWVSVM, PWVANN) is compared with the radiosonde PWV (PWVradiosonde) and voxel-based PWV (PWVVBT). The averaged relative error of the SVM, ANN and VBT models in the control stations is 10.50%, 12.71% and 12.91%, respectively. For SVM, ANN and VBT models, the averaged RMSE at the control stations is 1.87 (mm), 2.22 (mm) and 2.29 (mm), respectively. Analysis of the results of PWV estimated by the SVM, ANN and VBT, as well as the surface precipitation obtained from meteorological stations, indicate the high accuracy of the SVM in comparison with the ANN and VBT model. In the results shown in this paper, the SVM has the best ability to accurately estimate ZWD and PWV, using local GPS network observations. Numéro de notice : A2022-446 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.asr.2022.01.003 Date de publication en ligne : 13/01/2022 En ligne : https://doi.org/10.1016/j.asr.2022.01.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100106 [article]

A two-stage tropospheric correction model combining data from GNSS and numerical weather model / Jan Douša in GPS solutions, vol 22 n° 3 (July 2018)  

Public [article]  inGPS solutions > vol 22 n° 3 (July 2018) Titre : A two-stage tropospheric correction model combining data from GNSS and numerical weather model Type de document : Article/Communication Auteurs : Jan Douša, Auteur ; Michal Elias, Auteur ; Pavel Vaclavovic, Auteur ; Krystof Eben, Auteur ; Pavel Krč, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] correction troposphérique [Termes IGN] données GNSS [Termes IGN] données météorologiques [Termes IGN] gradient de troposphère [Termes IGN] modèle météorologique [Termes IGN] retard hydrostatique [Termes IGN] retard troposphérique zénithal [Termes IGN] station permanente Résumé : (Auteur) We have developed a new concept for providing tropospheric augmentation corrections. The two-stage correction model combines data from a Numerical Weather Model (NWM) and precise ZTDs estimated from Global Navigation Satellite System (GNSS) permanent stations in regional networks. The first-stage correction is generated using the background NWM forecast only. The second-stage correction results from an optimal combination of the background model data and GNSS (near) real-time tropospheric products. The optimum correction is achieved when using NWM for the hydrostatic delay modeling and for vertical scaling, while GNSS products are used for correcting the non-hydrostatic delay. The method is assessed in several variants including study of the combination of NWM and GNSS data, spatial densification of the original NWM grid, and GNSS ZTD densification using tropospheric linear horizontal gradients. The first-stage correction can be characterized by overall accuracy of about 10 mm for ZTD (1-sigma). The second-stage correction supported with GNSS tropospheric products improved the first-stage correction by a factor of 2–4 in terms of the ZTD accuracy and by a factor of 2.5 in terms of its spatio-temporal stability. Numéro de notice : A2018-373 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-018-0742-x Date de publication en ligne : 29/05/2018 En ligne : https://doi.org/10.1007/s10291-018-0742-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90767 [article]

Effect of small-scale atmospheric inhomogeneity on positioning accuracy with GPS / Olivier Bock in Geophysical research letters, vol 28 n° 11 (1 June 2001)  

Public [article]  inGeophysical research letters > vol 28 n° 11 (1 June 2001) . - pp 2289 - 2292 Titre : Effect of small-scale atmospheric inhomogeneity on positioning accuracy with GPS Type de document : Article/Communication Auteurs : Olivier Bock , Auteur ; Jérôme Tarniewicz , Auteur ; Christian Thom , Auteur ; Jacques Pelon, Auteur Année de publication : 2001 Article en page(s) : pp 2289 - 2292 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] modèle atmosphérique [Termes IGN] positionnement par GPS [Termes IGN] prévision météorologique [Termes IGN] retard hydrostatique [Termes IGN] retard troposphérique zénithal [Termes IGN] teneur en vapeur d'eau Résumé : (auteur) Global Positioning System (GPS) measurements through a field of km-size atmospheric boundary layer (ABL) inhomogeneities with a 10-ppm index of refraction excess have been simulated and inverted. Biases of up to 1–2 cm in height, 1–5 mm in horizontal, and ∼5 mm in zenith tropospheric delay (ZTD) are found, in either static or dynamic atmospheres, using 24-h solutions and estimating ZTD parameters. For 1-h sessions the scatter can increase by a factor of up to 5. These biases are attributed to the inadequacy of standard mapping functions. The use of numerical weather prediction (NWP) models and additional sounding techniques is discussed as a means of improving mapping functions. Raman lidars are thought to offer the highest potential for this purpose and for external calibration of both hydrostatic and wet path delay. Numéro de notice : A2001-257 Affiliation des auteurs : LOEMI+Ext (1985-2011) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2000GL011985 Date de publication en ligne : 01/06/2001 En ligne : https://doi.org/10.1029/2000GL011985 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102943 [article]