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A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)  

Public [article]  inSurvey review > vol 52 n° 373 (July 2020) . - pp 309 - 316 Titre : A robust total Kalman filter algorithm with numerical evaluation Type de document : Article/Communication Auteurs : Sida Li, Auteur ; Lintao Liu, Auteur ; Zhiping Liu, Auteur ; Guocheng Wang, Auteur Année de publication : 2020 Article en page(s) : pp 309 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] matrice [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle d'erreur [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] valeur aberrante Résumé : (auteur) In this study, the observation model of Kalman Filter (KF) is extended to an errors-in-variables (EIV) model because the observations may exist in the design matrix of the observation model. Then, a robust total least squares method (RTLS) is introduced into the KF, and a robust total Kalman filter (RTKF) algorithm is derived. The RTKF is a simple, flexible and effective algorithm. It is simple because its computational formulae are similar to the computational formulae of a standard KF; it is flexible because it can be used in a wide range of applications; it is effective because the influence of outliers on estimated results is weakened. Finally, the simulated example of the indoor location and the empirical example of pseudorange differential positioning are used to demonstrate the performance of the RTKF algorithm. The results prove the validity, robustness, and reliability of the RTKF in dealing with the outliers that exist in both observation vector and design matrix of the EIV model. Furthermore, the results of the empirical example show that the RTKF improves the precision of a pseudorange differential positioning compared with KF and robust Kalman filter (RKF) algorithms regardless the observation model has outliers or not in this empirical example. Numéro de notice : A2020-457 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1563392 date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/00396265.2018.1563392 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95556 [article]

A review of assessment methods for cellular automata models of land-use change and urban growth / Xiaohua Tong in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 5 (May 2020) . - pp 866 - 898 Titre : A review of assessment methods for cellular automata models of land-use change and urban growth Type de document : Article/Communication Auteurs : Xiaohua Tong, Auteur ; Yongjiu Feng, Auteur Année de publication : 2020 Article en page(s) : pp 866 - 898 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de sensibilité [Termes descripteurs IGN] analyse du paysage [Termes descripteurs IGN] automate cellulaire [Termes descripteurs IGN] changement d'occupation du sol [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] dynamique de la végétation [Termes descripteurs IGN] dynamique spatiale [Termes descripteurs IGN] Kappa de Cohen [Termes descripteurs IGN] matrice [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] population urbaine [Termes descripteurs IGN] propagation d'erreur Résumé : (auteur) Cellular automata (CA) models are in growing use for land-use change simulation and future scenario prediction. It is necessary to conduct model assessment that reports the quality of simulation results and how well the models reproduce reliable spatial patterns. Here, we review 347 CA articles published during 1999–2018 identified by a Scholar Google search using ‘cellular automata’, ‘land’ and ‘urban’ as keywords. Our review demonstrates that, during the past two decades, 89% of the publications include model assessment related to dataset, procedure and result using more than ten different methods. Among all methods, cell-by-cell comparison and landscape analysis were most frequently applied in the CA model assessment; specifically, overall accuracy and standard Kappa coefficient respectively rank first and second among all metrics. The end-state assessment is often criticized by modelers because it cannot adequately reflect the modeling ability of CA models. We provide five suggestions to the method selection, aiming to offer a background framework for future method choices as well as urging to focus on the assessment of input data and error propagation, procedure, quantitative and spatial change, and the impact of driving factors. Numéro de notice : A2020-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684499 date de publication en ligne : 05/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684499 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94880 [article]

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Progress towards a rigorous error propagation for total least-squares estimates / Burkhard Schaffrin in Journal of applied geodesy, vol 14 n° 2 (April 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 2 (April 2020) . - pp 159 – 166 Titre : Progress towards a rigorous error propagation for total least-squares estimates Type de document : Article/Communication Auteurs : Burkhard Schaffrin, Auteur ; Kyle Snow, Auteur Année de publication : 2020 Article en page(s) : pp 159 – 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] équation non linéaire [Termes descripteurs IGN] itération [Termes descripteurs IGN] linéarisation [Termes descripteurs IGN] matrice [Termes descripteurs IGN] mesure de précision [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] modèle d'erreur [Termes descripteurs IGN] propagation d'erreur Résumé : (auteur) After several attempts at a formal derivation of the dispersion matrix for Total Least-Squares (TLS) estimates within an Errors-In-Variables (EIV) Model, here a refined approach is presented that makes rigorous use of the nonlinear normal equations, though assuming a Kronecker product structure for both observational dispersion matrices at this point. In this way, iterative linearization of a model (that can be established as being equivalent to the original EIV-Model) is avoided, which might be preferred since such techniques are based on the last iteration step only and, therefore, produce dispersion matrices for the estimated parameters that are generally too optimistic. Here, the error propagation is based on the (linearized total differential of the) exact nonlinear normal equations, which should lead to more trustworthy measures of precision. Numéro de notice : A2020-216 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0062 date de publication en ligne : 03/04/2020 En ligne : https://doi.org/10.1515/jag-2019-0062 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94909 [article]

The stochastic model for Global Navigation Satellite Systems and terrestrial laser scanning observations: A proposal to account for correlations in least squares adjustment / Gaël Kermarrec in Journal of applied geodesy, vol 13 n° 2 (April 2019)  

Public [article]  inJournal of applied geodesy > vol 13 n° 2 (April 2019) . - pp 93 - 104 Titre : The stochastic model for Global Navigation Satellite Systems and terrestrial laser scanning observations: A proposal to account for correlations in least squares adjustment Type de document : Article/Communication Auteurs : Gaël Kermarrec, Auteur ; Ingo Neumann, Auteur ; Hamza Alkhatib, Auteur ; Steffen Schön, Auteur Année de publication : 2019 Article en page(s) : pp 93 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] analyse de variance [Termes descripteurs IGN] compensation par faisceaux [Termes descripteurs IGN] compensation par moindres carrés [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] matrice [Termes descripteurs IGN] modèle stochastique Résumé : (Auteur) The best unbiased estimates of unknown parameters in linear models have the smallest expected mean-squared errors as long as the residuals are weighted with their true variance–covariance matrix. As this condition is rarely met in real applications, the least-squares (LS) estimator is less trustworthy and the parameter precision is often overoptimistic, particularly when correlations are neglected. A careful description of the physical and mathematical relationships between the observations is, thus, necessary to reach a realistic solution and unbiased test statistics. Global Navigation Satellite Systems and terrestrial laser scanners (TLS) measurements show similarities and can be both processed in LS adjustments, either for positioning or deformation analysis. Thus, a parallel between stochastic models for Global Navigation Satellite Systems observations proposed previously in the case of correlations and functions for TLS range measurements based on intensity values can be drawn. This comparison paves the way for a simplified way to account for correlations for a use in LS adjustment. Numéro de notice : A2019-144 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2018-0019 date de publication en ligne : 24/01/2019 En ligne : https://doi.org/10.1515/jag-2018-0019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92471 [article]

Jacques Bertin’s legacy in information visualization and the reorderable matrix / Charles Perin in Cartography and Geographic Information Science, vol 46 n° 2 (March 2019)  

Public [article]  inCartography and Geographic Information Science > vol 46 n° 2 (March 2019) . - pp 176 - 181 Titre : Jacques Bertin’s legacy in information visualization and the reorderable matrix Type de document : Article/Communication Auteurs : Charles Perin, Auteur ; Jean-Daniel Fekete, Auteur ; Pierre Dragicevic, Auteur Année de publication : 2019 Article en page(s) : pp 176 - 181 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] interface homme-machine [Termes descripteurs IGN] matrice [Termes descripteurs IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Jacques Bertin’s legacy extends beyond the domain of cartography, and in particular to the field of information visualization where he continues to inspire researchers and practitioners. Although in the late twentieth century his books were out of print, their reedition around 2010 has steered a renewed interest and inspired new generations of researchers to reinterpret the principles of Semiology of Graphics and La Graphique in a time of interactive computers. In particular, the work of Jacques Bertin on the reorderable matrix has been very challenging in his time, and the quest to its automation has not been satisfactory to him. This article summarizes Bertin’s approach to the reorderable matrix, underlines the limitations of fully automated reordering methods, and introduces Bertifier, a hybrid system to reorder matrices using a combination of machine assistance and human control. Numéro de notice : A2019-098 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Numéro de périodique nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1470942 date de publication en ligne : 12/07/2018 En ligne : https://doi.org/10.1080/15230406.2018.1470942 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92355 [article]

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The characteristics of asymmetric pedestrian behavior : A preliminary study using passive smartphone location data / Nick Malleson in Transactions in GIS, vol 22 n° 2 (April 2018)  

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Contribution à la cartographie d’une matrice de flux / Françoise Bahoken in Mappemonde [en ligne], n° 123 (février 2018)  

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Template-based GIS computation : a geometric algebra approach / Wen Luo in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)  

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Superpixel-based intrinsic image decomposition of hyperspectral images / Xudong Jin in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

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A GIS approach to exploring monetary value on enclosure era property-related maps / Christopher Macdonald Hewitt in Cartographic journal (the), Vol 54 n° 2 (May 2017)  

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Multilayer NMF for blind unmixing of hyperspectral imagery with additional constraints / L. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 4 (April 2017)  

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Robust sparse hyperspectral unmixing with ℓ2,1 norm / Yong Ma in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)  

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The weight matrix determination of systematic bias calibration for a laser altimeter / Ma Yue in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 11 (November 2016)  

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Taking correlations in GPS least squares adjustments into account with a diagonal covariance matrix / Gaël Kermarrec in Journal of geodesy, vol 90 n° 9 (September 2016)  

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Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing / Paris V. Giampouras in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

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