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Termes IGN > mathématiques > statistique mathématique > probabilités > théorie des erreurs > valeur aberrante
valeur aberranteSynonyme(s)observation aberrante |
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Outlier detection and robust plane fitting for building roof extraction from LiDAR data / Emon Kumar Dey in International Journal of Remote Sensing IJRS, vol 41 n° 16 (01-10 May 2020)
[article]
Titre : Outlier detection and robust plane fitting for building roof extraction from LiDAR data Type de document : Article/Communication Auteurs : Emon Kumar Dey, Auteur ; Mohammad Awrangjeb, Auteur ; Bela Stantic, Auteur Année de publication : 2020 Article en page(s) : pp 6325 - 6354 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] semis de points
[Termes IGN] toit
[Termes IGN] valeur aberranteRésumé : (auteur) Individual roof plane extraction from Light Detection and Ranging (LiDAR) point-cloud data is a complex and difficult task because of unknown semantic characteristics and inharmonious behaviour of input data. Most of the existing state-of-the-art methods fail to detect small true roof planes with exact boundaries due to outliers, occlusions, complex building structures, and other inconsistent nature of LiDAR data. In this paper, we have presented an improved building detection and roof plane extraction method, which is less sensitive to the outliers and unlikely to generate spurious planes. For this, a robust outlier detection algorithm has been proposed in this paper along with a robust plane-fitting algorithm based on M-estimator SAmple Consensus (MSAC) for detecting individual roof planes. Using two benchmark datasets (Australian and International Society for Photogrammetry and Remote Sensing benchmark) with different numbers of buildings and sizes, trees and point densities, we have evaluated the proposed method. Experimental results show that the method removes outliers and vegetation almost accurately and offers a high success rate in terms of completeness and correctness (between 80% and 100% per-object) for both roof plane extraction and building detection. In most of the cases, the proposed method shows above 90% correctness. Numéro de notice : A2020-454 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2020.1737339 Date de publication en ligne : 09/06/2020 En ligne : https://doi.org/10.1080/01431161.2020.1737339 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95543
in International Journal of Remote Sensing IJRS > vol 41 n° 16 (01-10 May 2020) . - pp 6325 - 6354[article]Self-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors / Boris Kargoll in Journal of geodesy, vol 94 n° 5 (May 2020)
[article]
Titre : Self-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors Type de document : Article/Communication Auteurs : Boris Kargoll, Auteur ; Gaël Kermarrec, Auteur ; Hamza Alkhatib, Auteur ; Johannes Korte, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] algorithme espérance-maximisation
[Termes IGN] analyse vectorielle
[Termes IGN] auto-régression
[Termes IGN] bruit blanc
[Termes IGN] corrélation croisée normalisée
[Termes IGN] erreur aléatoire
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle stochastique
[Termes IGN] régression linéaire
[Termes IGN] série temporelle
[Termes IGN] station GPS
[Termes IGN] valeur aberranteRésumé : (auteur) The iteratively reweighted least-squares approach to self-tuning robust adjustment of parameters in linear regression models with autoregressive (AR) and t-distributed random errors, previously established in Kargoll et al. (in J Geod 92(3):271–297, 2018. https://doi.org/10.1007/s00190-017-1062-6), is extended to multivariate approaches. Multivariate models are used to describe the behavior of multiple observables measured contemporaneously. The proposed approaches allow for the modeling of both auto- and cross-correlations through a vector-autoregressive (VAR) process, where the components of the white-noise input vector are modeled at every time instance either as stochastically independent t-distributed (herein called “stochastic model A”) or as multivariate t-distributed random variables (herein called “stochastic model B”). Both stochastic models are complementary in the sense that the former allows for group-specific degrees of freedom (df) of the t-distributions (thus, sensor-component-specific tail or outlier characteristics) but not for correlations within each white-noise vector, whereas the latter allows for such correlations but not for different dfs. Within the observation equations, nonlinear (differentiable) regression models are generally allowed for. Two different generalized expectation maximization (GEM) algorithms are derived to estimate the regression model parameters jointly with the VAR coefficients, the variance components (in case of stochastic model A) or the cofactor matrix (for stochastic model B), and the df(s). To enable the validation of the fitted VAR model and the selection of the best model order, the multivariate portmanteau test and Akaike’s information criterion are applied. The performance of the algorithms and of the white noise test is evaluated by means of Monte Carlo simulations. Furthermore, the suitability of one of the proposed models and the corresponding GEM algorithm is investigated within a case study involving the multivariate modeling and adjustment of time-series data at four GPS stations in the EUREF Permanent Network (EPN). Numéro de notice : A2020-291 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01376-6 Date de publication en ligne : 10/05/2020 En ligne : https://doi.org/10.1007/s00190-020-01376-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95120
in Journal of geodesy > vol 94 n° 5 (May 2020)[article]Assessing the quality of ionospheric models through GNSS positioning error: methodology and results / Adria Rovira-Garcia in GPS solutions, vol 24 n° 1 (January 2020)
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Titre : Assessing the quality of ionospheric models through GNSS positioning error: methodology and results Type de document : Article/Communication Auteurs : Adria Rovira-Garcia, Auteur ; Deimos Ibáñez-Segura, Auteur ; Raül Orús-Pérez, Auteur ; et al., Auteur Année de publication : 2020 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] erreur de positionnement
[Termes IGN] International GNSS Service
[Termes IGN] modèle ionosphérique
[Termes IGN] phase
[Termes IGN] positionnement par GNSS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] retard ionosphèrique
[Termes IGN] trajet multiple
[Termes IGN] valeur aberranteRésumé : (Auteur) Single-frequency users of the global navigation satellite system (GNSS) must correct for the ionospheric delay. These corrections are available from global ionospheric models (GIMs). Therefore, the accuracy of the GIM is important because the unmodeled or incorrectly part of ionospheric delay contributes to the positioning error of GNSS-based positioning. However, the positioning error of receivers located at known coordinates can be used to infer the accuracy of GIMs in a simple manner. This is why assessment of GIMs by means of the position domain is often used as an alternative to assessments in the ionospheric delay domain. The latter method requires accurate reference ionospheric values obtained from a network solution and complex geodetic modeling. However, evaluations using the positioning error method present several difficulties, as evidenced in recent works, that can lead to inconsistent results compared to the tests using the ionospheric delay domain. We analyze the reasons why such inconsistencies occur, applying both methodologies. We have computed the position of 34 permanent stations for the entire year of 2014 within the last Solar Maximum. The positioning tests have been done using code pseudoranges and carrier-phase leveled (CCL) measurements. We identify the error sources that make it difficult to distinguish the part of the positioning error that is attributable to the ionospheric correction: the measurement noise, pseudorange multipath, evaluation metric, and outliers. Once these error sources are considered, we obtain equivalent results to those found in the ionospheric delay domain assessments. Accurate GIMs can provide single-frequency navigation positioning at the decimeter level using CCL measurements and better positions than those obtained using the dual-frequency ionospheric-free combination of pseudoranges. Finally, some recommendations are provided for further studies of ionospheric models using the position domain method. Numéro de notice : A2020-024 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-019-0918-z Date de publication en ligne : 02/11/2019 En ligne : https://doi.org/10.1007/s10291-019-0918-z Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94468
in GPS solutions > vol 24 n° 1 (January 2020)[article]Assessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)
[article]
Titre : Assessment of inner reliability in the Gauss-Helmert model Type de document : Article/Communication Auteurs : Andreas Ettlinger, Auteur ; Hans Neuner, Auteur Année de publication : 2020 Article en page(s) : pp 13 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie
[Termes IGN] coefficient de corrélation
[Termes IGN] compensation par moindres carrés
[Termes IGN] détection d'erreur
[Termes IGN] erreur systématique
[Termes IGN] fiabilité des données
[Termes IGN] filtre de Kalman
[Termes IGN] modèle d'erreur
[Termes IGN] modèle de Gauss-Helmert
[Termes IGN] valeur aberranteRésumé : (auteur) In this contribution, the minimum detectable bias (MDB) as well as the statistical tests to identify disturbed observations are introduced for the Gauss-Helmert model. Especially, if the observations are uncorrelated, these quantities will have the same structure as in the Gauss-Markov model, where the redundancy numbers play a key role. All the derivations are based on one-dimensional and additive observation errors respectively offsets which are modeled as additional parameters to be estimated. The formulas to compute these additional parameters with the corresponding variances are also derived in this contribution. The numerical examples of plane fitting and yaw computation show, that the MDB is also in the GHM an appropriate measure to analyze the ability of an implemented least-squares algorithm to detect if outliers are present. Two sources negatively influencing detectability are identified: columns close to the zero vector in the observation matrix B and sub-optimal configuration in the design matrix A. Even if these issues can be excluded, it can be difficult to identify the correct observation as being erroneous. Therefore, the correlation coefficients between two test values are derived and analyzed. Together with the MDB these correlation coefficients are an useful tool to assess the inner reliability – and therefore the detection and identification of outliers – in the Gauss-Helmert model. Numéro de notice : A2020-040 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0013 Date de publication en ligne : 19/10/2019 En ligne : https://doi.org/10.1515/jag-2019-0013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94511
in Journal of applied geodesy > vol 14 n° 1 (January 2020) . - pp 13 - 28[article]A filtering-based approach for improving crowdsourced GNSS traces in a data update context / Stefan Ivanovic in ISPRS International journal of geo-information, vol 8 n° 9 (September 2019)
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Titre : A filtering-based approach for improving crowdsourced GNSS traces in a data update context Type de document : Article/Communication Auteurs : Stefan Ivanovic (1988 - 2020) , Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Sébastien Mustière , Auteur ; Thomas Devogele , Auteur Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage automatique
[Termes IGN] approche participative
[Termes IGN] base de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] filtrage du bruit
[Termes IGN] mise à jour de base de données
[Termes IGN] montagne
[Termes IGN] qualité des données
[Termes IGN] sport
[Termes IGN] système d'information géographique
[Termes IGN] trace GPS
[Termes IGN] valeur aberranteRésumé : (auteur) Traces collected by citizens using GNSS (Global Navigation Satellite System) devices during sports activities such as running, hiking or biking are now widely available through different sport-oriented collaborative websites. The traces are collected by citizens for their own purposes and frequently shared with the sports community on the internet. Our research assumption is that crowdsourced GNSS traces may be a valuable source of information to detect updates in authoritative datasets. Despite their availability, the traces present some issues such as poor metadata, attribute incompleteness and heterogeneous positional accuracy. Moreover, certain parts of the traces (GNSS points composing the traces) are results of the displacements made out of the existing paths. In our context (i.e., update authoritative data) these off path GNSS points are considered as noise and should be filtered. Two types of noise are examined in this research: Points representing secondary activities (e.g., having a lunch break) and points representing errors during the acquisition. The first ones we named secondary human behaviour (SHB), whereas we named the second ones outliers. The goal of this paper is to improve the smoothness of traces by detecting and filtering both SHB and outliers. Two methods are proposed. The first one allows for the detection secondary human behaviour by analysing only traces geometry. The second one is a rule-based machine learning method that detects outliers by taking into account the intrinsic characteristics of points composing the traces, as well as the environmental conditions during traces acquisition. The proposed approaches are tested on crowdsourced GNSS traces collected in mountain areas during sports activities. Numéro de notice : A2019-626 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi8090380 Date de publication en ligne : 30/08/2019 En ligne : https://doi.org/10.3390/ijgi8090380 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95359
in ISPRS International journal of geo-information > vol 8 n° 9 (September 2019) . - 17 p.[article]Modelling discontinuous terrain from DSMs using segment labelling, outlier removal and thin-plate splines / Kassel Hingee in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)PermalinkReliable image matching via photometric and geometric constraints structured by Delaunay triangulation / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)PermalinkAn improved robust Kalman filtering strategy for GNSS kinematic positioning considering small cycle slips / Wanke Liu in Advances in space research, vol 63 n° 9 (1 May 2019)PermalinkA new relationship between the quality criteria for geodetic networks / Ivandro Klein in Journal of geodesy, vol 93 n° 4 (April 2019)PermalinkA comparative study between least square and total least square methods for time-series analysis and quality control of sea level observations / Mahmoud Pirooznia in Marine geodesy, vol 42 n° 2 (March 2019)PermalinkPermalinkThree-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint / Fangning He in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkThe efficiency of different outlier detection approaches in geodetic networks: case study for Pobednik statue / Mehmed Batilović in Geodetski vestnik, vol 62 n° 2 (June 2018)PermalinkReduction of ZTD outliers through improved GNSS data processing and screening strategies [Interactive discussion] / Katarzyna Stępniak in Atmospheric measurement techniques, vol 11 n° 3 (March 2018)PermalinkAlgebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)Permalink