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Estimation of the height datum geopotential value of Hong Kong using the combined Global Geopotential Models and GNSS/levelling data / Panpan Zhang in Survey review, vol 54 n° 383 (March 2022)  

Public [article]  inSurvey review > vol 54 n° 383 (March 2022) . - pp 106 - 116 Titre : Estimation of the height datum geopotential value of Hong Kong using the combined Global Geopotential Models and GNSS/levelling data Type de document : Article/Communication Auteurs : Panpan Zhang, Auteur ; Lifeng Bao, Auteur ; Dongmei Guo, Auteur Année de publication : 2022 Article en page(s) : pp 106 - 116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] données GNSS [Termes IGN] données GOCE [Termes IGN] données GRACE [Termes IGN] données topographiques [Termes IGN] Earth Gravity Model 2008 [Termes IGN] géoïde altimétrique [Termes IGN] Hong-Kong [Termes IGN] MNS SRTM [Termes IGN] modèle de géopotentiel local [Termes IGN] nivellement [Termes IGN] système de référence altimétrique Résumé : (auteur) The advent of the Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Exploration (GOCE) has changed the global contribution in the determination of high-accuracy global geopotential models (GGMs). In this paper, a spectral expansion method is used to determine the combined GGMs, using the high-resolution EGM2008 model and residual terrain model (RTM) to effectively bridge the spectral gap between the satellite and terrestrial data. The accuracy of the combined GGMs shows improvement compared with GOCE/GRACE-based GGMs and EGM2008 in determining the geopotential of the Hong Kong Principal Datum (HKPD). As a result of the DIR_R5/EGM2008/RTM model and GNSS/levelling, the geopotential value of HKPD is estimated to be 62,636,860.52 m2s−2 with respect to the global geoid W0 = 62,636,853.4 m2s−2. Therefore, the vertical offset between the HKPD and global geoid is about −72.8 cm, which means that the HKPD is 72.8 cm below the global height datum. Numéro de notice : A2022-238 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2021.1884794 Date de publication en ligne : 17/02/2021 En ligne : https://doi.org/10.1080/00396265.2021.1884794 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100162 [article]

Geoid determination through the combined least-squares adjustment of GNSS/levelling/gravity networks – a case study in Linyi, China / Dongmei Guo in Survey review, Vol 53 n° 381 (November 2021)  

Public [article]  inSurvey review > Vol 53 n° 381 (November 2021) . - pp 504 - 512 Titre : Geoid determination through the combined least-squares adjustment of GNSS/levelling/gravity networks – a case study in Linyi, China Type de document : Article/Communication Auteurs : Dongmei Guo, Auteur ; Zhixin Xue, Auteur Année de publication : 2021 Article en page(s) : pp 504 - 512 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] analyse de variance [Termes IGN] Chine [Termes IGN] compensation par moindres carrés [Termes IGN] données GNSS [Termes IGN] géoïde altimétrique [Termes IGN] géoïde local [Termes IGN] levé gravimétrique [Termes IGN] méthode des moindres carrés [Termes IGN] modèle stochastique [Termes IGN] pondération [Termes IGN] réseau de nivellement [Termes IGN] réseau gravimétrique Résumé : (Auteur) A detailed discussion of the adjustment problems used to combine GNSS/levelling/gravity network data is provided in this paper. The two primary problems inherent to heterogeneous data networks, namely, parametric models that describe the datums and systematic distortions among the available data sets and stochastic models that describe the observational residuals, are described. For parametric models, a relationship between the transformation parameters and the effects of datums and systematic distortions inherent among different height data types is established based on a least squares criterion. For stochastic models, the stochastic errors in GNSS/levelling/gravity data are evaluated, and a Helmert variance component estimation approach is introduced to refine weighting models. Finally, the proposed model is applied to determine the hybrid geoid in Linyi, China. The numerical results validate the capability and effectiveness of the proposed combined adjustment technique for hybrid geoid computations, revealing an achievable external accuracy of ±1.22 cm compared with GNSS/levelling measurements, which can be increased by 0.44 cm compared with classic adjustments of GNSS/levelling/geoid height data. Numéro de notice : A2021-913 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1842642 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/00396265.2020.1842642 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99316 [article]