Centre dedocumentation
scientifique

Bias in least-squares adjustment of implicit functional models / Michael Lösler in Survey review, Vol 53 n° 378 (May 2021)  

Public [article]  inSurvey review > Vol 53 n° 378 (May 2021) . - pp 223 - 234 Titre : Bias in least-squares adjustment of implicit functional models Type de document : Article/Communication Auteurs : Michael Lösler, Auteur ; Rüdiger Lehmann, Auteur ; Frank Neitzel, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 223 - 234 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] compensation par moindres carrés [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] fonction de Bessel [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] modèle non linéaire [Termes descripteurs IGN] modèle stochastique [Termes descripteurs IGN] série de Taylor [Termes descripteurs IGN] substitution [Termes descripteurs IGN] transformation de coordonnées Résumé : (auteur) To evaluate the benefit of a measurement procedure onto the estimated parameters, the dispersion of the parameters is usually used. To draw objective conclusions, unbiased or at least almost unbiased estimates are required. In geodesy, most of the functional relations are nonlinear but the statistical properties of the estimates are usually obtained by a linearised substitute-problem. Since the statistical properties of linear models cannot be passed to the nonlinear case, the estimates are biased. In this contribution, the bias of the parameters as well as the bias of the dispersion in nonlinear implicit models is investigated, using a second-order Taylor expansion. Nonlinear implicit models are general models and are used, for instance, in the framework of surface-fitting or coordinate transformation, which considers errors for the coordinates in source and target system. The bias is introduced as a further indicator to validate the benefit of an adapted measurement process using more precise measuring instruments. Since some parametrisations yield an ill-posed problem, also the case of a singular equation system is investigated. To demonstrate the second-order effect onto the estimates, a best-fitting plane is adjusted under varying configurations. Such a configuration is recommended in evaluating uncertainties of optical 3D measuring systems, e.g. in the framework of the VDI/VDE 2634 guideline. The estimated bias is used as an indicator whether a large number of poor observations provides better results than a small but precise sample. Numéro de notice : A2021-404 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1715680 date de publication en ligne : 29/01/2020 En ligne : https://doi.org/10.1080/00396265.2020.1715680 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97717 [article]

Integrated water vapour observations in the Caribbean arc from a network of ground-based GNSS receivers during EUREC4A / Olivier Bock in Earth System Science Data, vol 13 n° 5 (May 2021)  

Public [article]  inEarth System Science Data > vol 13 n° 5 (May 2021) . - pp 2407 - 2436 Titre : Integrated water vapour observations in the Caribbean arc from a network of ground-based GNSS receivers during EUREC4A Type de document : Article/Communication Auteurs : Olivier Bock , Auteur ; Pierre Bosser , Auteur ; Cyrille Flamant, Auteur ; Erik Doerflinger, Auteur ; Friedhelm Jansen, Auteur ; Romain Fagès, Auteur ; Sandrine Bony, Auteur ; Sabrina Schnitt, Auteur Année de publication : 2021 Projets : VEGAN / Bock, Olivier, EUREC4A / Article en page(s) : pp 2407 - 2436 Note générale : bibliographie This work was supported by the CNRS program LEFE/INSU through the project VEGAN. The EUREC4A project was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 694768). Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] Caraïbes [Termes descripteurs IGN] données auxiliaires [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] humidité de l'air [Termes descripteurs IGN] retard troposphérique zénithal [Termes descripteurs IGN] teneur intégrée en vapeur d'eau Résumé : (auteur) Ground-based Global Navigation Satellite System (GNSS) measurements from nearly fifty stations distributed over the Caribbean Arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality Integrated Water Vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the Tradewinds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD) to IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams international airport (GAIA). A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2) where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a colocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS derived IWV peaks. Two successive peaks are observed on 22 January and 23/24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organisation for five representative GNSS stations across the Caribbean Arc and found that the environment of Fish cloud patterns to be moister than that of Flowers cloud patterns which, in turn, is moister than the environment of Gravel cloud patterns. The differences in the IWV means between Fish and Gravel were assessed to be significant. Finally, the Gravel moisture environment was found to be similar to that of clear, cloud-free conditions. The moisture environment associated with the Sugar cloud pattern has not been assessed because it was hardly observed during the first two months of 2020. The reprocessed ZTD and IWV data set from 49 GNSS stations used in this study are available from the AERIS data center (https://doi.org/10.25326/79; Bock (2020b)). Numéro de notice : A2021-172 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-13-2407-2021 date de publication en ligne : 24/02/2021 En ligne : http://dx.doi.org/10.5194/essd-13-2407-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97213 [article]

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A / Pierre Bosser in Earth System Science Data, vol 13 n° 4 (April 2021)  

Public [article]  inEarth System Science Data > vol 13 n° 4 (April 2021) . - pp 1499 - 1517 Titre : Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A Type de document : Article/Communication Auteurs : Pierre Bosser , Auteur ; Olivier Bock , Auteur ; Cyrille Flamant, Auteur ; Sandrine Bony, Auteur ; Sabrina Speich, Auteur Année de publication : 2021 Projets : GEMMOC / Bosser, Pierre, VEGAN / Bock, Olivier, EUREC4A / Article en page(s) : pp 1499 - 1517 Note générale : bibliographie projets GEMMOC and VEGAN du CNRS program LEFE/INSU Both the raw GNSS measurements and the IWV estimates are available through the AERIS data center (https://en.aeris-data.fr/). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] coordonnées GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] navire [Termes descripteurs IGN] station permanente [Termes descripteurs IGN] teneur intégrée en vapeur d'eau Résumé : (auteur) In the framework of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open Tropical Atlantic Ocean using Global Navigation Satellite Systems (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian, and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Center for Medium-range Weather Forecast (ECMWF) fifth ReAnalysis (ERA5), from the Moderate-Resolution Imaging Spectroradiometer (MODIS) infra-red products, and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWVs retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (RMS) difference about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with RMS difference of 6 kg m−2 which are very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared product show large RMS differences of 5–7 kg m−2, reflecting the enhanced uncertainties of this satellite product in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Numéro de notice : A2021-064 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-13-1499-2021 En ligne : https://doi.org/10.5194/essd-13-1499-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96840 [article]

Precipitable water vapor fusion based on a generalized regression neural network / Bao Zhang in Journal of geodesy, vol 95 n° 4 (April 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 4 (April 2021) . - n° 36 Titre : Precipitable water vapor fusion based on a generalized regression neural network Type de document : Article/Communication Auteurs : Bao Zhang, Auteur ; Yibing Yao, Auteur Année de publication : 2021 Article en page(s) : n° 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] Amérique du nord [Termes descripteurs IGN] coefficient d'étalonnage [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] fusion de données [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] prévision météorologique [Termes descripteurs IGN] régression [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] vapeur d'eau [Termes descripteurs IGN] variation temporelle Résumé : (auteur) Water vapor plays an important role in Earth’s weather and climate processes and energy transfer. Plenty of techniques have developed to monitor precipitable water vapor (PWV), but joint use of different techniques has some problems, including systematic biases, different spatiotemporal coverages and resolutions among different datasets. To address the above problems and improve the data utilization, we propose to use a generalized regression neural network (GRNN) to fuse PWVs from Global Navigation Satellite System (GNSS), Moderate-Resolution Imaging Spectroradiometer (MODIS), and European Centre for Medium‐Range Weather Forecasts Reanalysis 5 (ERA5). The core idea of this method is to use the high-quality GNSS PWV to calibrate and optimize the relatively low-quality MODIS and ERA5 PWV through the constructed GRNNs. Using the proposed method, we generated more than 400 PWV maps that combine GNSS, MODIS, and ERA5 PWVs in North America in 2018. Results show that the overall bias, standard deviation (STD), and root-mean-square (RMS) error are 0.0 mm, 2.1 mm, and 2.2 mm for the improved MODIS PWV, and 0.0 mm, 1.6 mm, and 1.6 mm for the improved ERA5 PWV. Compared to the original MODIS and ERA5 PWV, the total improvements are 37.1% and 15.8% in terms of RMS. The RMS improvements are mainly contributed from the calibration of bias for the MODIS PWV and optimization for the ERA5 PWV. It also demonstrates that the original MODIS PWV tends to be greater than the GNSS PWV while the ERA5 PWV has very small biases. After calibration and optimization, the correlation coefficients between the modified PWV and the GNSS PWV are 0.96 for the MODIS PWV and 0.98 for the ERA5 PWV. The proposed method also diminishes the temporal and spatial variations in accuracy, generating homogeneous PWV products. Since the biases among the three datasets are well removed and data accuracies are improved to the same level, they are thus easily fused and jointly used. Numéro de notice : A2021-259 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01482-z date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1007/s00190-021-01482-z Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97299 [article]

Modélisation des délais ionosphériques appliquée au traitement PPP-RTK centimétrique avec ambiguïtés entières de phase / Camille Parra in XYZ, n° 166 (mars 2021)

Public [article]  inXYZ > n° 166 (mars 2021) . - pp 43 - 49 Titre : Modélisation des délais ionosphériques appliquée au traitement PPP-RTK centimétrique avec ambiguïtés entières de phase Type de document : Article/Communication Auteurs : Camille Parra, Auteur Année de publication : 2021 Article en page(s) : pp 43 - 49 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] délai d'obtention de la première position [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] modèle ionosphérique [Termes descripteurs IGN] phase GNSS [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] positionnement ponctuel précis [Termes descripteurs IGN] précision centimétrique [Termes descripteurs IGN] résolution d'ambiguïté [Termes descripteurs IGN] temps de convergence Résumé : (Auteur) Geoflex est une entreprise fournissant un positionnement précis, fiable, continu et en temps réel à ses clients partout dans le monde. Ce positionnement GNSS (Global Navigation Satellite System) se base sur l’utilisation de la Technologie PPP Geoflex/CNES (Precise Point Positioning) développée en partenariat avec le CNES (Centre national d’études spatiales) et commercialisée par Geoflex. Avec cette solution, qui repose sur la résolution d’ambiguïtés entières de phase en zéro-différence, Geoflex diffuse des flux de corrections permettant à l’utilisateur de se positionner partout dans le monde et sans aucune infrastructure GNSS proche de l’utilisateur, en mode statique ou cinématique, en temps réel ou différé, avec une précision horizontale de 4 cm à 95 % du temps. L’inconvénient de cette technique est son temps de convergence relativement important, d’environ 30 min, avec des observations bi-fréquences et bi-constellations disponibles sur les récepteurs GNSS mass-market commençant à équiper les voitures pour des meilleurs systèmes d’aide à la conduite, voire de certains smartphones. Le but de cet article est de montrer l’impact que peut avoir un modèle ionosphérique sur le temps de convergence d’un calcul PPP grâce à la technique du PPP-RTK (Real Time Kinematic). Il sera montré que grâce à cet apport, il est possible de réduire le temps de convergence de 90 % par rapport à une solution PPP-IAR (Integer Ambiguity Resolution) classique, mais qu’une attention particulière doit être apportée aux biais électroniques. Numéro de notice : A2021-247 Affiliation des auteurs : ENSG (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97325 [article]

Réservation

Réserver ce document

Exemplaires (2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
112-2021011	SL	Revue	Centre de documentation	Revues en salle	Disponible
112-2021012	SL	Revue	Centre de documentation	Revues en salle	Disponible

Crowdsourcing without data bias: Building a quality assurance system for air pollution symptom mapping / Marta Samulowska in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)  

Permalink

IWV retrieval from ground GNSS receivers during NAWDEX / Pierre Bosser in Advances in geosciences, vol 55 ([01/02/2021])  

Permalink

Study of systematic bias in measuring surface deformation with SAR interferometry / Homa Ansari in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

Permalink

Impact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)  

Permalink

A new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello in Journal of the Royal Statistical Society: Series C Applied Statistics, vol inconnu ([01/01/2021])  

Permalink

Evolution of orbit and clock quality for real-time multi-GNSS solutions / Kamil Kazmierski in GPS solutions, Vol 24 n° 4 (October 2020)  

Permalink

A multi-frequency and multi-GNSS method for the retrieval of the ionospheric TEC and intraday variability of receiver DCBs / Min Li in Journal of geodesy, vol 94 n° 10 (October 2020)  

Permalink

Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture / Ju Hyoung Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)  

Permalink

A warning against over-interpretation of seasonal signals measured by the Global Navigation Satellite System / Kristel Chanard in Nature communications, vol 11 (2020)  

Permalink

Assessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)  

Permalink