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Real time monitoring ground motion using GPS with real time corrections / R. Tu in Survey review, vol 48 n° 347 (March 2016)
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Titre : Real time monitoring ground motion using GPS with real time corrections Type de document : Article/Communication Auteurs : R. Tu, Auteur ; L. Wang, Auteur ; Z. Liu, Auteur Année de publication : 2016 Article en page(s) : pp 79 – 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] modèle d'erreur
[Termes IGN] mouvement de terrain
[Termes IGN] positionnement par GPS
[Termes IGN] résidu
[Termes IGN] station GPS
[Termes IGN] surveillance géologique
[Termes IGN] vitesseRésumé : (auteur) The high rate GPS velocity determination technology which is based on the broadcast ephemeris and epoch differenced model can retrieve displacement of ground motion with the precision of a few centimetres to decimetres in real time. Moreover, the precision of the recovered displacement can be improved if the un-modelled errors such as broadcast ephemeris residuals, atmospheric residuals, multipath effects and high frequency noise are tackled more accurately. In this paper, we propose a method to improve the precision of the recovered displacement by appropriately making use of reference station corrections. For the reference stations, the coordinates are highly constrained to extract the error corrections that are to be broadcast via a communication link to the rover. After correcting the rover’s observations, some errors such as ephemeris residuals and atmospheric residuals are effectively eliminated or at least reduced. This improves the accuracy of the observations and thus enhances the reliability of the velocity estimation. The displacement can be recovered by integrating the estimated velocity after de-trending using a linear trend that is caused by the un-corrected residuals. The series of validation results in the experiment have shown that the displacement of the simulated motion can be real time recovered with a precision of 1–2 cm, and is thus applicable for real time monitoring of the ground motion. Numéro de notice : A2016-047 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1179/1752270614Y.0000000141 En ligne : https://doi.org/10.1179/1752270614Y.0000000141 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79641
in Survey review > vol 48 n° 347 (March 2016) . - pp 79 – 85[article]Robust spatial approximation of laser scanner point clouds by means of Free-form Curve approaches in deformation analysis / Johannes Bureick in Journal of applied geodesy, vol 10 n° 1 (March 2016)
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Titre : Robust spatial approximation of laser scanner point clouds by means of Free-form Curve approaches in deformation analysis Type de document : Article/Communication Auteurs : Johannes Bureick, Auteur ; Hamza Alkhatib, Auteur ; Ingo Neumann, Auteur Année de publication : 2016 Article en page(s) : pp 27 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] approximation
[Termes IGN] B-Spline
[Termes IGN] déformation géométrique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode robuste
[Termes IGN] semis de pointsRésumé : (auteur) In many geodetic engineering applications it is necessary to solve the problem of describing a measured data point cloud, measured, e. g. by laser scanner, by means of free-form curves or surfaces, e. g., with B-Splines as basis functions. The state of the art approaches to determine B-Splines yields results which are seriously manipulated by the occurrence of data gaps and outliers.
Optimal and robust B-Spline fitting depend, however, on optimal selection of the knot vector. Hence we combine in our approach Monte-Carlo methods and the location and curvature of the measured data in order to determine the knot vector of the B-Spline in such a way that no oscillating effects at the edges of data gaps occur. We introduce an optimized approach based on computed weights by means of resampling techniques. In order to minimize the effect of outliers, we apply robust M-estimators for the estimation of control points.
The above mentioned approach will be applied to a multi-sensor system based on kinematic terrestrial laserscanning in the field of rail track inspection.Numéro de notice : A2016-551 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/jag-2015-0020 En ligne : http://dx.doi.org/10.1515/jag-2015-0020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81696
in Journal of applied geodesy > vol 10 n° 1 (March 2016) . - pp 27 - 35[article]The reliability of RANSAC method when estimating the parameters of geometric object / Tilen Urbančič in Geodetski vestnik, vol 60 n° 1 (March - May 2016)
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Titre : The reliability of RANSAC method when estimating the parameters of geometric object Type de document : Article/Communication Auteurs : Tilen Urbančič, Auteur ; Anja Vrecko, Auteur ; Klemen Kregar, Auteur Année de publication : 2016 Article en page(s) : pp 69 - 97 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Algorithmique
[Termes IGN] estimation des paramètres
[Termes IGN] méthode fiable
[Termes IGN] modèle mathématique
[Termes IGN] Ransac (algorithme)
[Termes IGN] résidu
[Termes IGN] solideRésumé : (Auteur) The RANSAC (RANdom SAmple Consensus) is often used to identify points belonging to the objects whose shape can be modeled with geometric primitives. These points, called inliers, are of great interest in some applications but often the goal is also to estimate the parameters of geometric shape and their accuracies. The quality of RANSAC results is rarely analyzed. The accuracies of estimated parameters are usually calculated based only on the residuals of inliers, selected by RANSAC, from a mathematical model. However, the analysis does not indicate if the right points were selected. The result of RANSAC depends on the random selection of the minimum number of points that uniquely describe a mathematical model; in the case of multiple repetitions of the method, the results are not necessarily the same. This paper presents an analysis of RANSAC reliability based on repeating the selection of points from the point cloud by RANSAC one hundred times. A standard deviation of one hundred parameter values is used to estimate the parameters’ accuracies. An analysis is made for three different examples of geometric objects: a sphere, a cone, and a plane. Finally, we suggest repeating the algorithm several times and checking the consistency of the results to obtain a more reliable estimation of parameters and their accuracies. Numéro de notice : A2016-175 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.15292/geodetski-vestnik.2016.01.69-97 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2016.01.69-97 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80520
in Geodetski vestnik > vol 60 n° 1 (March - May 2016) . - pp 69 - 97[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 139-2016011 RAB Revue Centre de documentation En réserve L003 Disponible A correctly weighted least squares adjustment - Part 2 Estimating uncertainties / Charles D. Ghilani in xyHt, vol 2016 n° 2 (February 2016)
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Titre : A correctly weighted least squares adjustment - Part 2 Estimating uncertainties Type de document : Article/Communication Auteurs : Charles D. Ghilani, Auteur Année de publication : 2016 Article en page(s) : pp 42 - 43 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie
[Termes IGN] compensation de coordonnées
[Termes IGN] compensation par moindres carrés
[Termes IGN] estimation statistique
[Termes IGN] incertitude des donnéesRésumé : (auteur) In the previous article (January 2016), I point out the unreliability of sample standard deviations as estimates for population standard errors when the number of repeated observations is very small, which is typically the problem in surveying. In this article I look at how we can estimate the standard errors for observations based on estimates for setup errors, leveling errors, and instrument-specific accuracies using error propagation principles. Note that this method of estimating uncertainties in observations is not new, since R. Ben Buckner, Edward Mikhail, and Gordon Gracie published these concepts in the early 1980s. Numéro de notice : A2016-619 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81824
in xyHt > vol 2016 n° 2 (February 2016) . - pp 42 - 43[article] Voir aussi
- A correctly weighted least squares adjustment - Part 3 Estimating standard errors in angular observations / Charles D. Ghilani in xyHt, vol 2016 n° 4 (April 2016)
- A correctly weighted least squares adjustment - Part 1 Problems from using computed standard deviations / Charles D. Ghilani in xyHt, vol 2016 n° 1 (January 2016)
La géostatistique : une vision novatrice au service des géosciences / Bernard Bourgine in Géosciences, n°20 (février 2016)
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Titre : La géostatistique : une vision novatrice au service des géosciences Type de document : Article/Communication Auteurs : Bernard Bourgine, Auteur ; Nicolas Jeannée, Auteur ; Jérémy Rhomer, Auteur Année de publication : 2016 Article en page(s) : pp 22 - 29 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de données
[Termes IGN] estimation statistique
[Termes IGN] géostatistique
[Termes IGN] incertitude des données
[Termes IGN] modèle numérique
[Termes IGN] risque naturelRésumé : (auteur) La géostatistique est née en France au début des années 1960. Initialement appliquée à l'évaluation de gisements miniers, son utilisation s'est ensuite généralisée : géologie pétrolière, géophysique, géotechnique, géothermie, hydrogéologie, environnement. Le succès de cette discipline est lié à sa capacité à intégrer de nouveaux types de données et à construire des modèles numériques de la variable d'intérêt assortis d'une évaluation de l'incertitude. Un atout majeur pour la prise de décision et l'analyse de risque, notamment en cas de fort enjeu économique ou environnemental. Numéro de notice : A2016-134 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article DOI : sans En ligne : https://www.brgm.fr/fr/actualite/revue/geosciences-ndeg20-geosciences-innover Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80293
in Géosciences > n°20 (février 2016) . - pp 22 - 29[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 076-2016011 RAB Revue Centre de documentation En réserve L003 Disponible Space–time adaptive processing and motion parameter estimation in multistatic passive radar using sparse Bayesian learning / Qisong Wu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)
PermalinkUse of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation / Göran Stahl in Forest ecosystems, vol 3 (2016)
PermalinkA joint Gaussian process model for active visual recognition with expertise estimation in crowdsourcing / Chengjiang Long in International journal of computer vision, vol 116 n° 2 (15th January 2016)
PermalinkPermalinkApplication of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania / Mercy Ojoyi in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)
PermalinkPermalinkPermalinkCaractérisation des signaux et des bruits des séries temporelles du géocentre et des paramètres de rotation de la Terre (EOP) / Bachir Gourine in Bulletin des sciences géographiques, n° 30 (2015 - 2016)
PermalinkCombination of GNSS and SLR measurements : contribution to the realization of the terrestrial reference frame / Sara Bruni (2016)
PermalinkConvex programming approach to robust estimation of a multivariate Gaussian model / Samuel Balmand (2016)
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PermalinkA correctly weighted least squares adjustment - Part 1 Problems from using computed standard deviations / Charles D. Ghilani in xyHt, vol 2016 n° 1 (January 2016)
PermalinkPermalinkEléments de géodésie et de la théorie des moindres carrés / Abdelmajid Ben Hadj Salem (février 2016)
PermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)
PermalinkPermalinkGini coefficient predictions from airborne lidar remote sensing display the effect of management intensity on forest structure / Rubén Valbuena in Ecological indicators, vol 60 (January 2016)
PermalinkPermalinkPermalinkPermalinkInvestigating efficacy of robust M-estimation of deformation from observation differences / Krzysztof Nowel in Survey review, vol 48 n° 346 (January 2016)
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