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Vertical land motion in the Southwest and Central Pacific from available GNSS solutions and implications for relative sea levels / Valérie Ballu in Geophysical journal international, vol 218 n° 3 (September 2019)
[article]
Titre : Vertical land motion in the Southwest and Central Pacific from available GNSS solutions and implications for relative sea levels Type de document : Article/Communication Auteurs : Valérie Ballu, Auteur ; Médéric Gravelle, Auteur ; Guy Wöppelmann , Auteur ; Olivier de Viron, Auteur ; Paul Rebischung , Auteur ; Mélanie Becker, Auteur ; Pierre Sakic-Kieffer, Auteur Année de publication : 2019 Projets : STORISK / Duvat, Virginie, TOSCA / Duvat, Virginie Article en page(s) : pp 1537 - 1551 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] incertitude géométrique
[Termes IGN] montée du niveau de la mer
[Termes IGN] Pacifique ouest
[Termes IGN] Pacifique Sud
[Termes IGN] série temporelleRésumé : (auteur) Coastal populations are impacted by relative sea level variations, which consist both of absolute sea level variations and of vertical land motions. This paper focuses on the Southwest and Central Pacific region, a recognized vulnerable region to sea level rise and where a large range of vertical land motion dynamics is observed. We analyse vertical displacement rates obtained from Global Navigation Satellite Systems (GNSS) by different analysis centres. We study the role played by modelled parameters, such as step discontinuities (due to equipment changes, earthquakes, etc.), in the position time-series analysis. We propose a new modelling approach based on a joint inversion of GNSS position time-series from different analysis centres. The final uncertainty on the vertical land motion rates is estimated as a combination of the uncertainty due to the GNSS data processing itself and the uncertainty due to the stability of the reference frame in which the GNSS data are expressed. We find that the dominant trend in the Southwest and Central Pacific is a moderate subsidence, with an average rate of −1.1 mm yr–1, but significant variations are observed, with displacement rates varying from an uplift of 1.6 ± 0.3 mm yr–1 to a subsidence of −5.4 ± 0.3 mm yr–1. Taking into account the geodynamic context, we assess, for each station, the relevance of current estimates of linear vertical displacement rate and uncertainty for forecasting future coastal sea levels. Numéro de notice : A2019-634 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/gji/ggz247 Date de publication en ligne : 27/05/2019 En ligne : https://doi.org/10.1093/gji/ggz247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95452
in Geophysical journal international > vol 218 n° 3 (September 2019) . - pp 1537 - 1551[article]Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach / Jian Zhao in Marine geodesy, vol 42 n° 4 (July 2019)
[article]
Titre : Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach Type de document : Article/Communication Auteurs : Jian Zhao, Auteur ; Yanguo Fan, Auteur ; Yuxiang Mu, Auteur Année de publication : 2019 Article en page(s) : pp 344 - 366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] détection d'anomalie
[Termes IGN] données altimétriques
[Termes IGN] données Jason
[Termes IGN] données Topex-Poseidon
[Termes IGN] image ERS-SAR
[Termes IGN] méthode des moindres carrés
[Termes IGN] montée du niveau de la mer
[Termes IGN] Pacifique nord
[Termes IGN] prévision
[Termes IGN] réseau neuronal artificiel
[Termes IGN] série temporelleRésumé : (auteur) Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2 cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast. Numéro de notice : A2019-281 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1626306 Date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1626306 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93115
in Marine geodesy > vol 42 n° 4 (July 2019) . - pp 344 - 366[article]Construction of bulk temperature/salinity from surface temperature and atlas profiles for monitoring water volume variations in the Caspian Sea / Ayoub Moradi (2019)
Titre : Construction of bulk temperature/salinity from surface temperature and atlas profiles for monitoring water volume variations in the Caspian Sea Type de document : Article/Communication Auteurs : Ayoub Moradi, Auteur ; Olivier de Viron, Auteur ; Laurent Métivier , Auteur ; Saeid Homayouni, Auteur Editeur : Téhéran : Kharazmi University Année de publication : 2019 Conférence : CICIS 2019, 4th Conference on Contemporary Issues in Computer Information and Sciences 23/01/2019 25/01/2019 Teheran Iran Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de sensibilité
[Termes IGN] Caspienne, mer
[Termes IGN] image NOAA
[Termes IGN] montée du niveau de la mer
[Termes IGN] salinité
[Termes IGN] température de surface de la merRésumé : (auteur) Unlike the other lakes, the Caspian Sea has regular water level fluctuations caused by variation in temperature and salinity, which is known as thermohaline fluctuations. Vertically variable temperature and salinity data are needed in order to monitor thermohaline fluctuations. These data are regularly recorded for the open seas by remote sensing and in-situ approaches. However, there is no such information for inland water bodies, such as the Caspian Sea. In this research, daily Sea Surface Temperature (SST) from the NOAA satellite, plus long-term mean temperature, and salinity datasets from Atlas 2009 were utilized to construct bulk temperature and salinity in the Caspian Sea. The Atlas vertical profiles are not deep enough in the Caspian Sea; we expanded these data down to a thermocline depth, using a linear fitting. Constructed bulk temperature and salinity data utilized in water density calculations. The results show that thermohaline level fluctuation estimated by constructed bulk data is consisted of what a combination of altimetry and gravimetry system observed in the Caspian Sea. In the absence of necessary data, this method is helpful for bulk temperature and salinity estimations in the Caspian Sea with a satisfactory level of accuracy. The estimated thermohaline has an accuracy of about 93%, under the situation that there was 15% error in the estimation of both bulk temperature and salinity. Numéro de notice : C2019-080 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : IMAGERIE Nature : Communication DOI : sans En ligne : https://www.researchgate.net/publication/368243402_Construction_of_Bulk_Temperat [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102859 Exploring 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)
[article]
Titre : Exploring the sensitivity of coastal inundation modelling to DEM vertical error Type de document : Article/Communication Auteurs : Harry West, Auteur ; Michael Horswell, Auteur ; Nevil Quinn, Auteur Année de publication : 2018 Article en page(s) : pp 1172 - 1193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de sensibilité
[Termes IGN] erreur en altitude
[Termes IGN] estuaire
[Termes IGN] incertitude géométrique
[Termes IGN] inondation
[Termes IGN] littoral
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle numérique de surface
[Termes IGN] montée du niveau de la mer
[Termes IGN] Royaume-UniRésumé : (Auteur) As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover. Numéro de notice : A2018-203 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1444165 Date de publication en ligne : 14/03/2018 En ligne : https://doi.org/10.1080/13658816.2018.1444165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89874
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1172 - 1193[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve L003 Disponible Contribution actuelle de la calotte Antarctique à la variation du niveau marin / Clémence Chupin (2018)
Titre : Contribution actuelle de la calotte Antarctique à la variation du niveau marin Type de document : Mémoire Auteurs : Clémence Chupin, Auteur Editeur : Le Mans : Ecole Supérieure des Géomètres et Topographes ESGT Année de publication : 2018 Autre Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Importance : 83 p. Format : 21 x 30 cm Note générale : bibliographie
Mémoire d'ingénieur ESGT, master PPMD Photogrammétrie, Positionnement et Mesure de DéformationLangues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] Antarctique
[Termes IGN] bilan de masse
[Termes IGN] calotte glaciaire
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données GRACE
[Termes IGN] élasticité
[Termes IGN] fonte des glaces
[Termes IGN] géoïde local
[Termes IGN] image Envisat-ASAR
[Termes IGN] levé gravimétrique
[Termes IGN] manteau terrestre
[Termes IGN] montée du niveau de la mer
[Termes IGN] rhéologie
[Termes IGN] viscositéIndex. décimale : MPPMD Mémoires du mastère spécialisé Photogrammétrie, Positionnement et Mesures de Déformation Résumé : (auteur) Avec ses 14 millions de km2, la calotte Antarctique représente le plus grand réservoir d’eau
douce de la planète, ce qui en fait un contributeur non négligeable de l’augmentation du niveau marin. Les dernières estimations de son bilan de masse évalue la perte de glace de la calotte à 2.720 ± 1.390 Gt entre 1992 et 2017, ce qui correspond à une hausse du niveau marin d’environ 7.6 ± 3.9 mm [Shepherd et al., 2018]. L’objectif de ce stage est d’utiliser ce bilan de masse moyen pour quantifier l’amplitude des variations du niveau marin. Grâce aux données d’altimétrie et de gravimétrie satellitaire, un modèle des variations spatio-temporelles du bilan de masse est également construit. Le logiciel SELEN ensuite permet de calculer la variation du niveau marin induite par ces deux modèles de fonte.Note de contenu : Introduction
1- Antarctique & niveau marin
2- Modélisation de la variation spatio-temporelle de l’Antarctique
3- Estimation des variations du niveau marin
ConclusionNuméro de notice : 21856 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Mémoire ingénieur ESGT Organisme de stage : Laboratoire Geoazur (CNRS) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91420 Réservation
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