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Remote sensing scene classification using multilayer stacked covariance pooling / Nanjun He in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Remote sensing scene classification using multilayer stacked covariance pooling Type de document : Article/Communication Auteurs : Nanjun He, Auteur ; Leyuan Fang, Auteur ; Shutao Li, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 6899 - 6910 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] matrice de covariance
[Termes IGN] représentation cartographique
[Termes IGN] scèneRésumé : (auteur) This paper proposes a new method, called multilayer stacked covariance pooling (MSCP), for remote sensing scene classification. The innovative contribution of the proposed method is that it is able to naturally combine multilayer feature maps, obtained by pretrained convolutional neural network (CNN) models. Specifically, the proposed MSCP-based classification framework consists of the following three steps. First, a pretrained CNN model is used to extract multilayer feature maps. Then, the feature maps are stacked together, and a covariance matrix is calculated for the stacked features. Each entry of the resulting covariance matrix stands for the covariance of two different feature maps, which provides a natural and innovative way to exploit the complementary information provided by feature maps coming from different layers. Finally, the extracted covariance matrices are used as features for classification by a support vector machine. The experimental results, conducted on three challenging data sets, demonstrate that the proposed MSCP method can not only consistently outperform the corresponding single-layer model but also achieve better classification performance than other pretrained CNN-based scene classification methods. Numéro de notice : A2018-552 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2845668 Date de publication en ligne : 09/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2845668 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91640
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 6899 - 6910[article]Towards operational marker-free registration of terrestrial lidar data in forests / Jean-François Tremblay in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)
[article]
Titre : Towards operational marker-free registration of terrestrial lidar data in forests Type de document : Article/Communication Auteurs : Jean-François Tremblay, Auteur ; Martin Béland, Auteur Année de publication : 2018 Article en page(s) : pp 430 - 435 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] canopée
[Termes IGN] cible réfléchissante
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Etats-Unis
[Termes IGN] forêt
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] matrice de covariance
[Termes IGN] modèle numérique de terrain
[Termes IGN] Québec (Canada)
[Termes IGN] semis de pointsRésumé : (auteur) Terrestrial laser scanning (TLS) often makes use of multiple scans in forests to allow for a complete view of a given area. Combining measurements from multiple locations requires accurate co-registration of the scans to a common reference coordinate system, which currently relies on markers, an often cumbersome process in forests. Existing algorithms for achieving marker-free registration of TLS scans in forests promise to significantly decrease field work time, but are not yet operational and their results have not been validated against traditional methods. Here we present a new implementation of an existing approach which runs in parallel mode and is able to process TLS data acquired over large forest areas. To validate our algorithm, point cloud registration matrices (translation and rotation) derived from our algorithm were compared to those obtained using reflective markers in multiple forest types. The results show that our approach can be used operationally in forests with relatively clear understory, and it provides accuracy similar to that obtained from using reflective markers. Furthermore, we identified factors that can lead to this approach falling short of providing acceptable results in terms of accuracy. Numéro de notice : A2018-542 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.10.011 Date de publication en ligne : 02/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.10.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91566
in ISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 430 - 435[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018131 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018133 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018132 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Least-squares cross-wavelet analysis and its applications in geophysical time series / Ebrahim Ghaderpour in Journal of geodesy, vol 92 n° 10 (October 2018)
[article]
Titre : Least-squares cross-wavelet analysis and its applications in geophysical time series Type de document : Article/Communication Auteurs : Ebrahim Ghaderpour, Auteur ; Elmas Sinem Ince, Auteur ; Spiros D. Pagiatakis, Auteur Année de publication : 2018 Article en page(s) : pp 1223 - 1236 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] champ de pesanteur terrestre
[Termes IGN] données GOCE
[Termes IGN] données ITGB
[Termes IGN] gradient de gravitation
[Termes IGN] matrice de covariance
[Termes IGN] méthode des moindres carrés
[Termes IGN] série temporelle
[Termes IGN] transformation en ondelettesRésumé : (Auteur) The least-squares wavelet analysis, an alternative to the classical wavelet analysis, was introduced in order to analyze unequally spaced and non-stationary time series exhibiting components with variable amplitude and frequency over time. There are a few methods such as cross-wavelet transform and wavelet coherence that can analyze two time series together. However, these methods cannot generally be used to analyze unequally spaced and non-stationary time series with associated covariance matrices that may have trends and/or datum shifts. A new method of analyzing two time series together, namely the least-squares cross-wavelet analysis, is developed and applied to study the disturbances in the gravitational gradients observed by GOCE satellite that arise from plasma flow in the ionosphere represented by Poynting flux. The proposed method also shows its outstanding performance on the Westford–Wettzell very long baseline interferometry baseline length and temperature series. Numéro de notice : A2018-462 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1156-9 Date de publication en ligne : 26/05/2018 En ligne : https://doi.org/10.1007/s00190-018-1156-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91061
in Journal of geodesy > vol 92 n° 10 (October 2018) . - pp 1223 - 1236[article]Unmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil / Sébastien Giordano in IEEE Transactions on geoscience and remote sensing, vol 56 n° 10 (October 2018)
[article]
Titre : Unmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil Type de document : Article/Communication Auteurs : Sébastien Giordano , Auteur ; Grégoire Mercier, Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Article en page(s) : pp 5850 - 5862 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] biomasse aérienne
[Termes IGN] décomposition spectrale
[Termes IGN] données polarimétriques
[Termes IGN] forêt
[Termes IGN] image Radarsat
[Termes IGN] matrice de covariance
[Termes IGN] occupation du sol
[Termes IGN] polarimétrie radar
[Termes IGN] sol nu
[Termes IGN] surface forestièreRésumé : (auteur) Extracting information from a polarimetric radar representation usually consists in decomposing it with target decomposition algorithms. This first step can be seen as a geometric analysis of the polarimetric information: the identification of physical radar scattering mechanisms. The problem is that average physical parameters are estimated. As a consequence, these parameters might not describe correctly any of the land cover types that can be mixed together into the radar resolution cell. Therefore, using the polarimetric parameters for land cover classification is challenging. The novelty of the method is to propose a thematic analysis of the polarimetric information preceding the geometric one. The objective is to assess if splitting off polarimetric information on a land cover type basis before applying usual target decomposition algorithms can produce more consistent radar scattering mechanisms when land cover classes are mixed inside the radar resolution cell. A cooperative fusion framework in which very high-resolution optical images are used to unmix physical radar scattering mechanisms is proposed. For bare soil and forests, we point out that a linear unmixing model applied to the covariance matrix is able to split off polarimetric information on a land cover type basis. The assessment of the unmixed radar matrices is carried out with polarimetric radar images from the Radarsat-2 satellite. It was found that despite speckle, the reconstructed radar information after the unmixing process is statistically relevant with the observations. The question whether the unmixed radar images contain relevant thematic information is more challenging, but results tend to validate this property. This method could be used to have a better estimation of vegetation biomass in the context of open forested areas. Numéro de notice : A2018-331 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2827258 Date de publication en ligne : 09/07/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2827258 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90475
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 10 (October 2018) . - pp 5850 - 5862[article]A methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model / R. Klees in Journal of geodesy, vol 92 n° 4 (April 2018)
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Titre : A methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model Type de document : Article/Communication Auteurs : R. Klees, Auteur ; D.C. Slobbe, Auteur ; Hassan Hashemi Farahani, Auteur Année de publication : 2018 Article en page(s) : pp 431 - 442 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] fonction de base radiale
[Termes IGN] matrice de covariance
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle de géopotentiel
[Termes IGN] quasi-géoïde
[Termes IGN] résiduRésumé : (Auteur) The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix for quality control and further data processing. The methodology goes beyond the classical remove–compute–restore approach, which does not account for the noise in the satellite-only GGM. We suggest and analyse three different approaches of data combination. Two of them are based on a local single-scale spherical radial basis function (SRBF) model of the disturbing potential, and one is based on a two-scale SRBF model. Using numerical experiments, we show that a single-scale SRBF model does not fully exploit the information in the satellite-only GGM. We explain this by a lack of flexibility of a single-scale SRBF model to deal with datasets of significantly different bandwidths. The two-scale SRBF model performs well in this respect, provided that the model coefficients representing the two scales are estimated separately. The corresponding methodology is developed in this paper. Using the statistics of the least-squares residuals and the statistics of the errors in the estimated two-scale quasi-geoid model, we demonstrate that the developed methodology provides a two-scale quasi-geoid model, which exploits the information in all datasets. Numéro de notice : A2018-063 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1076-0 Date de publication en ligne : 06/11/2017 En ligne : https://doi.org/10.1007/s00190-017-1076-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89399
in Journal of geodesy > vol 92 n° 4 (April 2018) . - pp 431 - 442[article]Bayesian statistics and Monte Carlo methods / Karl Rudolf Koch in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkPermalinkPairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game / Dawei Zai in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkUncertainty assessment in geodetic network adjustment by combining GUM and Monte-Carlo-simulations / Wolfgang Niemeier in Journal of applied geodesy, vol 11 n° 2 (June 2017)PermalinkModified residual method for the estimation of noise in hyperspectral images / Asad Mahmood in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkPermalinkMultiband image fusion based on spectral unmixing / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkSystematic effects in laser scanning and visualization by confidence regions / Karl Rudolf Koch in Journal of applied geodesy, vol 10 n° 4 (December 2016)PermalinkA measure of average error variance of line features / Eryong Liu in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)PermalinkTaking 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)Permalink