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SIMuRG: System for Ionosphere Monitoring and Research from GNSS / Yury V. Yasyukevich in GPS solutions, Vol 24 n° 3 (July 2020)
[article]
Titre : SIMuRG: System for Ionosphere Monitoring and Research from GNSS Type de document : Article/Communication Auteurs : Yury V. Yasyukevich, Auteur ; Alexander V. Kiselev, Auteur ; Ilyav Zhivetiev, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] collecte de données
[Termes IGN] ionosphère
[Termes IGN] perturbation ionosphérique
[Termes IGN] récepteur GNSS
[Termes IGN] site web
[Termes IGN] surveillance
[Termes IGN] teneur totale en électronsRésumé : (auteur) Currently, more than 6000 operating GNSS receivers deliver observations to multiple servers. Ionospheric data are derived from these measurements providing outstanding space coverage and time resolution. There are about 200 million independent measurements daily. Researchers need sophisticated software tools to deal with such a large amount of data. We present recent advances and products from the System for Ionosphere Monitoring and Research from GNSS (SIMuRG). Currently, SIMuRG provides the total electron content (TEC) variations filtered within 2–10 min, 10–20 min, and 20–60 min, the Rate of the TEC Index, the Along Arc TEC Rate index, and the vertical TEC. SIMuRG is an online service at http://simurg.iszf.irk.ru. The system can be used free of charge and allows calculating both maps and series for arbitrary time intervals and geographic regions. All the data products are available in the form of data or figures. We discuss the system and its geophysics applications. Numéro de notice : A2020-327 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-00983-2 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.1007/s10291-020-00983-2 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95208
in GPS solutions > Vol 24 n° 3 (July 2020)[article]Improved 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)
[article]
Titre : Improved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests Type de document : Article/Communication Auteurs : Sruthi M. Krishna Moorthy, Auteur ; Kim Calders, Auteur ; Matheus B. Vicari, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 3057 - 3070 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage dirigé
[Termes IGN] atmosphère terrestre
[Termes IGN] canopée
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] faisceau laser
[Termes IGN] feuille (végétation)
[Termes IGN] foresterie
[Termes IGN] forêt de feuillus
[Termes IGN] forêt tropicale
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] précision de la classification
[Termes IGN] Python (langage de programmation)
[Termes IGN] semis de points
[Termes IGN] transfert radiatifRésumé : (auteur) Accurately classifying 3-D point clouds into woody and leafy components has been an interest for applications in forestry and ecology including the better understanding of radiation transfer between canopy and atmosphere. The past decade has seen an increase in the methods attempting to classify leaves and wood in point clouds based on radiometric or geometric features. However, classification purely based on radiometric features is sensor-specific, and the method by which the local neighborhood of a point is defined affects the accuracy of classification based on geometric features. Here, we present a leaf-wood classification method combining geometrical features defined by radially bounded nearest neighbors at multiple spatial scales in a machine learning model. We compared the performance of three different machine learning models generated by the random forest (RF), XGBoost, and lightGBM algorithms. Using multiple spatial scales eliminates the need for an optimal neighborhood size selection and defining the local neighborhood by radially bounded nearest neighbors makes the method broadly applicable for point clouds of varying quality. We assessed the model performance at the individual tree- and plot-level on field data from tropical and deciduous forests, as well as on simulated point clouds. The method has an overall average accuracy of 94.2% on our data sets. For other data sets, the presented method outperformed the methods in literature in most cases without the need for additional postprocessing steps that are needed in most of the existing methods. We provide the entire framework as an open-source python package. Numéro de notice : A2020-232 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947198 Date de publication en ligne : 31/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947198 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94970
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 3057 - 3070[article]Comparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series / Zhao Li in Journal of geodesy, vol 94 n°4 (April 2020)
[article]
Titre : Comparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series Type de document : Article/Communication Auteurs : Zhao Li, Auteur ; Chen Wu, Auteur ; Tonie M. van Dam, Auteur ; Paul Rebischung , Auteur ; Zuheir Altamimi , Auteur Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : n° 42 Note générale : bibliographie
This research is supported by the National Key Research and Development Program of China (Project 2016YFB0502101), the European Commission/Research Grants Council (RGC) Collaboration Scheme sponsored by the Research Grants Council of Hong Kong Special Administrative Region, China (Project No. E-PolyU 501/16), and the National Science Foundation for Distinguished Young Scholars of China (Grant No. 41525014).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] analyse comparative
[Termes IGN] coefficient de corrélation
[Termes IGN] données GNSS
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] MERRA
[Termes IGN] modèle atmosphérique
[Termes IGN] pression atmosphérique
[Termes IGN] radar JPL
[Termes IGN] résidu
[Termes IGN] série temporelle
[Termes IGN] station GNSSRésumé : (auteur) To remove atmospheric pressure loading (ATML) effect from GNSS coordinate time series, surface pressure (SP) models are required to predict the displacements. In this paper, we modeled the 3D ATML surface displacements using the latest MERRA-2 SP grids, together with four other products (NCEP-R-1, NCEP-R-2, ERA-Interim and MERRA) for 596 globally distributed GNSS stations, and compared them with ITRF2014 residual time series. The five sets of ATML displacements are highly consistent with each other, particularly for those stations far away from coasts, of which the lowest correlations in the Up component for all the four models w.r.t MERRA-2 become larger than 0.91. ERA-Interim-derived ATML displacement performs best in reducing scatter of the GNSS height for 90.3% of the stations (89.3% for NCEP-R-1, 89.1% for NCEP-R-2, 86.4% for MERRA and 85.1% for MERRA-2). We think that this may be possibly due to the 4D variational data assimilation method applied. Considering inland stations only, more than 96% exhibit WRMS reduction in the Up direction for all five models, with an average improvement of 3–4% compared with the original ITRF2014 residual time series before ATML correction. Most stations (> 67%) also exhibit horizontal WRMS reductions based on the five models, but of small magnitudes, with most improvements (> 76%) less than 5%. In particular, most stations in South America, South Africa, Oceania and the Southern Oceans show larger WRMS reductions with MERRA-2, while all other four SP datasets lead to larger WRMS reduction for the Up component than MERRA-2 in Europe. Through comparison of the daily pressure variation from the five SP models, we conclude that the bigger model differences in the SP-induced surface displacements and their impacts on the ITRF2014 residuals for coastal/island stations are mainly due to the IB correction based on the different land–sea masks. A unique high spatial resolution land–sea mask should be applied in the future, so that model differences would come from only SP grids. Further research is also required to compare the ATML effect in ice-covered and high mountainous regions, for example the Qinghai–Tibet Plateau in China, the Andes in South America, etc., where larger pressure differences between models tend to occur. Numéro de notice : A2020-159 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01370-y Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.1007/s00190-020-01370-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94813
in Journal of geodesy > vol 94 n°4 (April 2020) . - n° 42[article]The impact of second-order ionospheric delays on the ZWD estimation with GPS and BDS measurements / Shaocheng Zhang in GPS solutions, vol 24 n° 2 (April 2020)
[article]
Titre : The impact of second-order ionospheric delays on the ZWD estimation with GPS and BDS measurements Type de document : Article/Communication Auteurs : Shaocheng Zhang, Auteur ; Lei Fang, Auteur ; Guangxing Wang, Auteur ; Wei Li, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] champ géomagnétique
[Termes IGN] décalage d'horloge
[Termes IGN] données BeiDou
[Termes IGN] données GPS
[Termes IGN] gradient ionosphèrique
[Termes IGN] méthode des moindres carrés
[Termes IGN] positionnement ponctuel précis
[Termes IGN] retard ionosphèrique
[Termes IGN] retard troposphérique zénithal
[Termes IGN] teneur verticale totale en électronsRésumé : (auteur) Since millimeter accuracy is required in many GNSS applications such as real-time zenith wet delay (ZWD) estimation, the higher-order ionospheric delays on GNSS signals are no longer negligible. We calculated the second-order ionospheric delays (I2) and analyzed the impact on the ZWD estimation with GPS-only and combined GPS/BDS observations. The undifferenced PPP model with fixed coordinates was used to estimate the ZWD and horizontal gradients. The method of blockwise sequential least squares was utilized to eliminate the receiver clock biases and compute the I2 impact on the ZWDs. The I2 delays on each GNSS satellite observations were calculated with the CODE final TEC map and the 12th generation of the international geomagnetic reference field (IGRF-12) model. The statistical results with the actual observation geometry show that the I2 delays can reach over 10 mm during the daytime, and the corresponding impact on the estimated ZWD can reach up to several millimeters. At station HKWS, the maximum I2 impact with GPS only reaches up to 3.1 mm and is still 2.4 mm when both GPS and BDS observations are used. The simulated I2 impact on the ZWD could reach several millimeters, even though the TEC and geomagnetic values were calculated from relatively moderate background models. Compared with the 5–10 mm precision of real-time ZWD estimation, the I2 delays must not be ignored, especially during high VTEC periods. Numéro de notice : A2020-082 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-0954-8 Date de publication en ligne : 04/02/2020 En ligne : https://doi.org/10.1007/s10291-020-0954-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94651
in GPS solutions > vol 24 n° 2 (April 2020)[article]Advanced machine learning optimized by the genetic algorithm in ionospheric models using long-term multi-instrument observations / Wang Li in Remote sensing, vol 12 n° 5 (March 2020)
[article]
Titre : Advanced machine learning optimized by the genetic algorithm in ionospheric models using long-term multi-instrument observations Type de document : Article/Communication Auteurs : Wang Li, Auteur ; Dongsheng Zhao, Auteur ; Changyong He , Auteur ; Andong Hu, Auteur ; Kefei Zhang, Auteur Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : n° 866 Note générale : bibliographie
This research was funded by the National Natural Science Foundations of China, grant number 41730109, the Priority Academic Program Development of Jiangsu Higher Education Institutions (Surveying and Mapping) and the Jiangsu Dual Creative Talents and Jiangsu Dual Creative Teams Programme Projects awarded in 2017.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] algorithme génétique
[Termes IGN] image Formosat/COSMIC
[Termes IGN] International Reference Ionosphere
[Termes IGN] modèle ionosphérique
[Termes IGN] réseau neuronal artificiel
[Termes IGN] teneur totale en électronsRésumé : (auteur) The ionospheric delay is of paramount importance to radio communication, satellite navigation and positioning. It is necessary to predict high-accuracy ionospheric peak parameters for single frequency receivers. In this study, the state-of-the-art artificial neural network (ANN) technique optimized by the genetic algorithm is used to develop global ionospheric models for predicting foF2 and hmF2. The models are based on long-term multiple measurements including ionospheric peak frequency model (GIPFM) and global ionospheric peak height model (GIPHM). Predictions of the GIPFM and GIPHM are compared with the International Reference Ionosphere (IRI) model in 2009 and 2013 respectively. This comparison shows that the root-mean-square errors (RMSEs) of GIPFM are 0.82 MHz and 0.71 MHz in 2013 and 2009, respectively. This result is about 20%–35% lower than that of IRI. Additionally, the corresponding hmF2 median errors of GIPHM are 20% to 30% smaller than that of IRI. Furthermore, the ANN models present a good capability to capture the global or regional ionospheric spatial-temporal characteristics, e.g., the equatorial ionization anomaly and Weddell Sea anomaly. The study shows that the ANN-based model has a better agreement to reference value than the IRI model, not only along the Greenwich meridian, but also on a global scale. The approach proposed in this study has the potential to be a new three-dimensional electron density model combined with the inclusion of the upcoming Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) data. Numéro de notice : A2020-872 Affiliation des auteurs : ENSG+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12050866 Date de publication en ligne : 07/03/2020 En ligne : https://doi.org/10.3390/rs12050866 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99659
in Remote sensing > vol 12 n° 5 (March 2020) . - n° 866[article]Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkAdvanced GNSS tropospheric products for monitoring severe weather events and climate / Jonathan Jones (2020)PermalinkAssessing the quality of ionospheric models through GNSS positioning error: methodology and results / Adria Rovira-Garcia in GPS solutions, vol 24 n° 1 (January 2020)PermalinkComparison of atmospheric mass density models using a new data source: COSMIC satellite ephemerides / Yang Yang (2020)PermalinkEfficiency of updating the ionospheric models using total electron content at mid- and sub-auroral latitudes / Daria S. Kotova in GPS solutions, vol 24 n° 1 (January 2020)PermalinkEstimation and representation of regional atmospheric corrections for augmenting real-time single-frequency PPP / Peiyuan Zhou in GPS solutions, vol 24 n° 1 (January 2020)PermalinkÉtude de la vapeur d’eau atmosphérique à partir de données GNSS dans le bassin sud-ouest de l’océan Indien et applications à l’étude du climat et des cyclones tropicaux / Edouard Lees (2020)PermalinkImpact of thermospheric mass density on the orbit prediction of LEO satellites / Changyong He in Space weather, vol 18 n° 1 (January 2020)PermalinkPermalinkReducing convergence time of precise point positioning with ionospheric constraints and receiver differential code bias modeling / Yan Xiang in Journal of geodesy, vol 94 n°1 (January 2020)Permalink