Centre dedocumentation
scientifique

New algorithms for spherical harmonic analysis of area mean values over blocks delineated by equiangular and Gaussian grids / Rong Sun in Journal of geodesy, vol 95 n° 5 (May 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 5 (May 2021) . - n° 47 Titre : New algorithms for spherical harmonic analysis of area mean values over blocks delineated by equiangular and Gaussian grids Type de document : Article/Communication Auteurs : Rong Sun, Auteur Année de publication : 2021 Article en page(s) : n° 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] analyse harmonique [Termes descripteurs IGN] grille [Termes descripteurs IGN] matrice [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] quadrature [Termes descripteurs IGN] transformation polynomiale Résumé : (auteur) Spherical harmonic analysis is widely used in all aspects of geoscience. Exact quadrature methods are available for the spherical harmonic analysis of band-limited point values at the grid points of equiangular and Gaussian grids. However, no similarly exact quadrature methods are available for the spherical harmonic analysis of area mean values over the blocks delineated by these grids. In this study, new algorithms appropriate for the exact spherical harmonic analysis of the band-limited area mean values over the blocks delineated by equiangular and Gaussian grids are proposed. For band-limited data, precision that is between that of the least-squares estimation method and of the approximate quadrature methods can be achieved by using the new algorithms. Regarding the computational complexity, fewer operations are needed by the new methods as compared to those needed by the least-squares estimation method and the approximate quadrature methods in the preparation stage when the maximum degree of the spherical harmonic analysis is very large. Simulation experiments are performed to compare the ability to recover the spherical harmonic coefficients by using the least-squares estimation method, the approximate quadrature methods and these new algorithms from aliased data with aliasing components of realistic magnitudes. The results suggest that these new algorithms, with time complexity one order less than that of the least-squares estimation method in the solving stage, perform roughly the same as the least-squares estimation method in recovering spherical harmonic coefficients from the aliased data. Numéro de notice : A2021-312 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01495-8 date de publication en ligne : 07/04/2021 En ligne : https://doi.org/10.1007/s00190-021-01495-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97507 [article]

Parallel computing for fast spatiotemporal weighted regression / Xiang Que in Computers & geosciences, vol 150 (May 2021)  

Public [article]  inComputers & geosciences > vol 150 (May 2021) . - n° 104723 Titre : Parallel computing for fast spatiotemporal weighted regression Type de document : Article/Communication Auteurs : Xiang Que, Auteur ; Chao Ma, Auteur ; Xiaogang Ma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104723 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] calcul matriciel [Termes descripteurs IGN] étalonnage de modèle [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] régression géographiquement pondérée [Termes descripteurs IGN] traitement parallèle Résumé : (auteur) The Spatiotemporal Weighted Regression (STWR) model is an extension of the Geographically Weighted Regression (GWR) model for exploring the heterogeneity of spatiotemporal processes. A key feature of STWR is that it utilizes the data points observed at previous time stages to make better fit and prediction at the latest time stage. Because the temporal bandwidths and a few other parameters need to be optimized in STWR, the model calibration is computationally intensive. In particular, when the data amount is large, the calibration of STWR becomes heavily time-consuming. For example, with 10,000 points in 10 time stages, it takes about 2307 s for a single-core PC to process the calibration of STWR. Both the distance and the weighted matrix in STWR are memory intensive, which may easily cause memory insufficiency as data amount increases. To improve the efficiency of computing, we developed a parallel computing method for STWR by employing the Message Passing Interface (MPI). A cache in the MPI processing approach was proposed for the calibration routine. Also, a matrix splitting strategy was designed to address the problem of memory insufficiency. We named the overall design as Fast STWR (F-STWR). In the experiment, we tested F-STWR in a High-Performance Computing (HPC) environment with a total number of 204,611 observations in 19 years. The results show that F-STWR can significantly improve STWR's capability of processing large-scale spatiotemporal data. Numéro de notice : A2021-300 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.1016/j.cageo.2021.104723 date de publication en ligne : 05/03/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104723 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97413 [article]

Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 2940 - 2950 Titre : Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network Type de document : Article/Communication Auteurs : Nantheera Anantrasirichai, Auteur ; Juliet Biggs, Auteur ; Krisztina Kelevitz, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2940 - 2950 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] bati [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] complétion [Termes descripteurs IGN] covariance [Termes descripteurs IGN] déformation de la croute terrestre [Termes descripteurs IGN] données d'apprentissage [Termes descripteurs IGN] effet atmosphérique [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] interpolation spatiale [Termes descripteurs IGN] matrice [Termes descripteurs IGN] optimisation (mathématiques) [Termes descripteurs IGN] représentation parcimonieuse [Termes descripteurs IGN] Royaume-Uni [Termes descripteurs IGN] zone urbaine Résumé : (auteur) The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015–2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems. Numéro de notice : A2021-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-020-00323-6 date de publication en ligne : 31/08/2020 En ligne : https://doi.org/10.1007/s12518-020-00323-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97391 [article]

Study on offshore seabed sediment classification based on particle size parameters using XGBoost algorithm / Fengfan Wang in Computers & geosciences, vol 149 (April 2021)  

Public [article]  inComputers & geosciences > vol 149 (April 2021) . - n° 104713 Titre : Study on offshore seabed sediment classification based on particle size parameters using XGBoost algorithm Type de document : Article/Communication Auteurs : Fengfan Wang, Auteur ; Jia Yu, Auteur ; Zhijie Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104713 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse spatiale [Termes descripteurs IGN] calcul matriciel [Termes descripteurs IGN] Chine [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] diagramme [Termes descripteurs IGN] échantillon [Termes descripteurs IGN] Extreme Gradient Machine [Termes descripteurs IGN] fond marin [Termes descripteurs IGN] gravier [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] sédiment [Termes descripteurs IGN] texture Résumé : (auteur) Folk's textual classification scheme which is widely used for sediment study operates with the proportions of gravel, sand, silt and clay fractions conventionally. However, dealing with data from different sources usually needs to face missing values that may make the classification difficult. To solve this problem and discover other methods of analyzing the scheme, with samples of offshore seabed sediment, a two-stage model was established to predict a sample's class using the XGBoost algorithm as well as the grain size parameters as input features. The final model was evaluated with quantitative performance measures of recall, precision and F1 score, and by comparing sediment texture maps using the predicted and the actual data. The results show that the model performs well on extraction of sediment samples without gravel fraction, and prediction of classes that have independent characteristics of grain size parameters or samples not near the boundaries of classes in the ternary diagram. The predicted sediment texture is close to the actual and could be reliable due to errors with little impact on further applications. It is demonstrated that the model could be an auxiliary or alternative approach to offshore sediment texture mapping, as well as supplementary to the analysis of sedimentary environment. Numéro de notice : A2021-289 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104713 date de publication en ligne : 12/02/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104713 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97400 [article]

A practical method for calculating reliable integer float estimator in GNSS precise positioning / Xianwen Yu in Survey review, Vol 53 n° 377 (February 2021)  

Public [article]  inSurvey review > Vol 53 n° 377 (February 2021) . - pp 97 - 107 Titre : A practical method for calculating reliable integer float estimator in GNSS precise positioning Type de document : Article/Communication Auteurs : Xianwen Yu, Auteur ; Siqi Xia, Auteur ; Wang Gao, Auteur Année de publication : 2021 Article en page(s) : pp 97 - 107 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] estimateur [Termes descripteurs IGN] matrice [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] résolution d'ambiguïté [Termes descripteurs IGN] variance Résumé : (auteur) To overcome the problem that a fixed estimator is contaminated by a system error for the ambiguity be misjudged in the GNSS precise positioning, a reliable integer float estimator is recommended. Accordingly, the method for determining a finite number of integer vectors based on a given reliability probability is proposed, the formula for calculating the variance matrix of the recommended estimator is derived, and the judgment method of the estimator’s availability is proposed. The detailed process and the effect of the method are also demonstrated using examples to facilitate user application. Numéro de notice : A2021-193 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1718268 date de publication en ligne : 29/01/2020 En ligne : https://doi.org/10.1080/00396265.2020.1718268 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97127 [article]

Hyperspectral and multispectral image fusion via graph Laplacian-guided coupled tensor decomposition / Yuanyang Bu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)  

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Temporal calibration and synchronization of robotic total stations for kinematic multi-sensor-systems / Tomas Thalmann in Journal of applied geodesy, vol 15 n° 1 (January 2021)  

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Local terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

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

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A convolutional neural network with mapping layers for hyperspectral image classification / Rui Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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A point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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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)  

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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)  

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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)  

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A discriminative tensor representation model for feature extraction and classification of multispectral LiDAR data / Qingwang Wang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Hierarchical classification of pole‐like objects in mobile laser scanning point clouds / Rufei Liu in Photogrammetric record, vol 35 n° 169 (March 2020)  

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Generalized tensor regression for hyperspectral image classification / Jianjun Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)  

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Velocity field and crustal deformation of broader Athens plain (Greece) from a dense geodetic network / Michael Foumelis in Journal of applied geodesy, Vol 13 n° 4 (October 2019)  

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Implementing Moran eigenvector spatial filtering for massively large georeferenced datasets / Daniel A. Griffith in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)  

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Unmanned aerial system multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition / Sheng Wang in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

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Multi-GNSS real-time clock estimation using sequential least square adjustment with online quality control / Wenju Fu in Journal of geodesy, vol 93 n°7 (July 2019)  

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Robust structure from motion based on relative rotations and tie points / Xin Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 5 (May 2019)  

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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)  

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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)  

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Near real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)  

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Computing with cognitive spatial frames of reference in GIS / Simon Scheider in Transactions in GIS, vol 22 n° 5 (October 2018)  

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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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Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect / Pooja Mishra in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)  

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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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Robust object-based multipass InSAR deformation reconstruction / Jian Kang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 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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An adaptive weighted tensor completion method for the recovery of remote sensing images with missing data / Michael Kwok-Po Ng in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 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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Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data / André Dittrich in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 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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Panda∗: A generic and scalable framework for predictive spatio-temporal queries / Abdeltawab M. Hendawi in Geoinformatica [en ligne], vol 21 n° 2 (April - June 2017)  

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A method for assessing generalized data accuracy with linear object resolution verification / Tadeusz Chrobak in Geocarto international, vol 32 n° 3 (March 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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Testing spatial heterogeneity in geographically weighted principal components analysis / Javier Roca-Pardiñas in International journal of geographical information science IJGIS, vol 31 n° 3-4 (March-April 2017)  

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Analyse numérique / Mustapha Lakrib (2017)

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Data science par la pratique : fondamentaux avec Python / Joël Grus (2017)

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Linear Algebra / Arak M. Mathai (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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A tensor decomposition-based anomaly detection algorithm for hyperspectral image / Xing Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)  

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The D-FCM partitioned D-BSP tree for massive point cloud data access and rendering / Yi Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)  

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Shadow detection and removal in RGB VHR images for land use unsupervised classification / A. Movia in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 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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Sparse output coding for scalable visual recognition / Bin Zhao in International journal of computer vision, vol 119 n° 1 (August 2016)  

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Estimating the intrinsic dimension of hyperspectral images using a noise-whitened eigengap approach / Non-répertorié in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)  

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Location K-anonymity in indoor spaces / Joon-Seok Kim in Geoinformatica [en ligne], vol 20 n° 3 (July - September 2016)  

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Sparse and low-rank graph for discriminant analysis of hyperspectral imagery / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)  

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Mesure de robustesse d'un réseau géodésique 3D : cas du réseau GPS de la ville d'Oran (Algérie) / Bachir Gourine in XYZ, n° 147 (juin - août 2016)

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Vector attribute profiles for hyperspectral image classification / Erchan Aptoula in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

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Matrix-based discriminant subspace ensemble for hyperspectral image spatial–spectral feature fusion / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)  

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Contribution à la cartographie d’une matrice de flux / Françoise Bahoken (2016)  

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Deep learning / Ian Goodfellow (2016)  

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Forcing scale invariance in multipolarization SAR change detection / Vincenzo Carotenuto in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)    

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Géomatique, modèles numériques de terrain / Patrick Julien (2016)

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Introduction to partial differential equations / David Borthwick (2016)  

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Introduction to Time Series and Forecasting / Peter J. Brockwell (2016)  

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On estimation of the diagonal elements of a sparse precision matrix / Samuel Balmand in Electronic Journal of Statistics, vol 10 n° 1 (January 2016)    

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Propagation des ondes électromagnétiques dans l’atmosphère terrestre / Jonathan Chenal (2016) 

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QGIS 2 cookbook / Alex Mandel (2016)

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Some contributions to large precision matrix estimation / Samuel Balmand (2016)  

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Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration / Wei He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)  

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Two dimensional linear discriminant analyses for hyperspectral data / Maryam Imani in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 10 (October 2015)

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Mappes et temporalités : la logique mappologique à l'épreuve de la topochronie / Régis Keerle in Cartes & Géomatique, n° 225 (septembre 2015) 

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GIS based drainage morphometry and its influence on hydrology in parts of Western Ghats region, Maharashtra, India / Dipak R. Samal in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)  

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Substance dependence constrained sparse NMF for hyperspectral unmixing / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

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Adaptive relative motion representation of space–time trajectories / Antoni B. Moore in Cartographic journal (the), Vol 52 n° 2 (May 2015)  

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Interferometric phase image estimation via sparse coding in the complex domain / Hao Hongxing in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)

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On reverse-k-nearest-neighbor joins / Tobias Emrich in Geoinformatica [en ligne], vol 19 n° 2 (April - June 2015)  

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Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis / Marco Helbich in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)  

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Collaborative representation for hyperspectral anomaly detection / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

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A multidimensional extension of the concept of coherence in polarimetric SAR interferometry / Jose Luis Alvarez-Perez in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

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Progressive band processing of constrained energy minimization for subpixel detection / Chein-I Chang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

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Automatic spatial–spectral feature selection for hyperspectral image via discriminative sparse multimodal learning / Qian Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)  

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Efficient continuous top-k spatial keyword queries on road networks / Long Guo in Geoinformatica [en ligne], vol 19 n° 1 (January - March 2015)  

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Methods of Mathematical Modelling / Thomas Witelski (2015)  

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Note de géométrie différentielle : L'opérateur Peterson / Abdelmajid Ben Hadj Salem (2015) 

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Positioning configurations with the lowest GDOP and their classification / Shuqiang Xue in Journal of geodesy, vol 89 n° 1 (January 2015)  

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Generalizations of bounds on the index of convergence to weighted digraphs / Glenn Merlet in Discrete Applied Mathematics, vol 178 ([11/12/2014])  

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Association-matrix-based sample consensus approach for automated registration of terrestrial laser scans using linear features / Kaleel Al-Durgham in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)  

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Automated hyperspectral vegetation index retrieval from multiple correlation matrices with HyperCor / Helge Aasen in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)  

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Modélisation numérique du champ de gravité produit par une structure géologique arbitraire / Clément Roussel in XYZ, n° 139 (juin - août 2014)

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Semisupervised dual-geometric subspace projection for dimensionality reduction of hyperspectral image data / Shuyuan Yang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)

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Spatial and spectral image fusion using sparse matrix factorization / Bo Huang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)  

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UL-Isomap based nonlinear dimensionality reduction for hyperspectral imagery classification / Weiwei Sun in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)

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Nonlinear unmixing of hyperspectral data using semi-nonnegative matrix factorization / Naoto Yokoya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)  

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Structured sparse method for hyperspectral unmixing / Feiyun Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)

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Introduction to partial differential equations / Peter J. Olver (2014)  

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Spatiotemporal filtering of regional GNSS network’s position time series with missing data using principle component analysis / Yunzhong Shen in Journal of geodesy, vol 88 n° 1 (January 2014)  

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The diffusion approximation for the linear Boltzmann equation with vanishing scattering coefficient / Claude Bardos in Communications in Mathematical Sciences, vol 13 n° 3 (2014)  

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Toutes les mathématiques, nouveau programme / Luc Verschueren (2014)

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On the exponential decay to equilibrium of the degenerate linear Boltzmann equation / Etienne Bernard in Journal of functional analysis, vol 265 n° 9 (November 2013)  

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La construction d'une matrice de flux à partir de traces de téléphones portables / Françoise Bahoken in Cartes & Géomatique, n° 217 (septembre 2013)    

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Hyperspectral image noise reduction based on rank-1 tensor decomposition / Xian Guoa in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)

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Visual discovery of synchronisation in weather data at multiple temporal resolutions / Xiaojing Wu in Cartographic journal (the), vol 50 n° 3 (August 2013)

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