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Detection of ground surface deformation caused by the 2016 Kumamoto earthquake by InSAR using ALOS-2 data / Basara Miyahara in Bulletin of the GeoSpatial Information authority of Japan, vol 64 (December 2016)
[article]
Titre : Detection of ground surface deformation caused by the 2016 Kumamoto earthquake by InSAR using ALOS-2 data Type de document : Article/Communication Auteurs : Basara Miyahara, Auteur ; Yuji Miura, Auteur ; Yasuaki Kakiage, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 21 - 26 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] déformation de la croute terrestre
[Termes IGN] faille géologique
[Termes IGN] image ALOS
[Termes IGN] image radar moirée
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Japon
[Termes IGN] Kyushu (Japon)
[Termes IGN] réseau géodésique local
[Termes IGN] séismeRésumé : (auteur) SAR interferometry (InSAR) analysis of operational L-band SAR satellite of Japan, ALOS-2, reveals a series of coseismic crustal deformations caused by the 2016 Kumamoto Earthquake (April 14-16, 2016). Large coseismic deformation of over 10 centimeters due to the two large foreshocks and over 2 meters due to the mainshock can be clearly identified on the SAR interferograms as well as postseismic deformation up to a few centimeters. These displacements are concentrated around Futagawa-Hinagu fault zone which is a known active fault in Kyushu Island. 2.5-D displacements, more specifically quasi-east-west and quasi-vertical displacements due to the mainshock are also estimated from two interferograms observed from both east and west directions. The estimated displacements are consistent with those of ground GNSS observations. The sequence of the earthquakes causes significant distortion in the geodetic datum of Japan around the focal area, and thus positions of geodetic control points, which are fundamental infrastructure for implementing the datum needed to be revised as soon as possible. The area of the deformation could be promptly identified from the interferograms, and the control points which needed to be revised were quickly determined from the interferograms without any additional ground observation. Numéro de notice : A2016--076 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.gsi.go.jp/common/000150877.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84505
in Bulletin of the GeoSpatial Information authority of Japan > vol 64 (December 2016) . - pp 21 - 26[article]Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data / Benedikt Soja in Journal of geodesy, vol 90 n° 12 (December 2016)
[article]
Titre : Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data Type de document : Article/Communication Auteurs : Benedikt Soja, Auteur ; Tobias Nilsson, Auteur ; Kyriakos Balidakis, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1311 - 1327 Note générale : Bibliographie ; Erratum : voir pdf Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] bruit (théorie du signal)
[Termes IGN] coordonnées géographiques
[Termes IGN] filtre de Kalman
[Termes IGN] image radar moirée
[Termes IGN] interférométrie à très grande base
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] modèle stochastique
[Termes IGN] station permanenteRésumé : (Auteur) Terrestrial reference frames (TRF), such as the ITRF2008, are primary products of geodesy. In this paper, we present TRF solutions based on Kalman filtering of very long baseline interferometry (VLBI) data, for which we estimate steady station coordinates over more than 30 years that are updated for every single VLBI session. By applying different levels of process noise, non-linear signals, such as seasonal and seismic effects, are taken into account. The corresponding stochastic model is derived site-dependent from geophysical loading deformation time series and is adapted during periods of post-seismic deformations. Our results demonstrate that the choice of stochastic process has a much smaller impact on the coordinate time series and velocities than the overall noise level. If process noise is applied, tests with and without additionally estimating seasonal signals indicate no difference between the resulting coordinate time series for periods when observational data are available. In a comparison with epoch reference frames, the Kalman filter solutions provide better short-term stability. Furthermore, we find out that the Kalman filter solutions are of similar quality when compared to a consistent least-squares solution, however, with the enhanced attribute of being easier to update as, for instance, in a post-earthquake period. Numéro de notice : A2016-804 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0924-7 En ligne : http://dx.doi.org/10.1007/s00190-016-0924-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82591
in Journal of geodesy > vol 90 n° 12 (December 2016) . - pp 1311 - 1327[article]Dictionary learning for promoting structured sparsity in hyperspectral compressive sensing / Lei Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
[article]
Titre : Dictionary learning for promoting structured sparsity in hyperspectral compressive sensing Type de document : Article/Communication Auteurs : Lei Zhang, Auteur ; Wei Wei, Auteur ; Yanning Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 7223 - 7235 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] bruit blanc
[Termes IGN] compression d'image
[Termes IGN] image hyperspectrale
[Termes IGN] reconstruction d'imageRésumé : (Auteur) The ability to accurately represent a hyperspectral image (HSI) as a combination of a small number of elements from an appropriate dictionary underpins much of the recent progress in hyperspectral compressive sensing (HCS). Preserving structure in the sparse representation is critical to achieving an accurate reconstruction but has thus far only been partially exploited because existing methods assume a predefined dictionary. To address this problem, a structured sparsity-based hyperspectral blind compressive sensing method is presented in this study. For the reconstructed HSI, a data-adaptive dictionary is learned directly from its noisy measurements, which promotes the underlying structured sparsity and obviously improves reconstruction accuracy. Specifically, a fully structured dictionary prior is first proposed to jointly depict the structure in each dictionary atom as well as the correlation between atoms, where the magnitude of each atom is also regularized. Then, a reweighted Laplace prior is employed to model the structured sparsity in the representation of the HSI. Based on these two priors, a unified optimization framework is proposed to learn both the dictionary and sparse representation from the measurements by alternatively optimizing two separate latent variable Bayes models. With the learned dictionary, the structured sparsity of HSIs can be well described by the reweighted Laplace prior. In addition, both the learned dictionary and sparse representation are robust to noise corruption in the measurements. Extensive experiments on three hyperspectral data sets demonstrate that the proposed method outperforms several state-of-the-art HCS methods in terms of the reconstruction accuracy achieved. Numéro de notice : A2016-929 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2598577 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2598577 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83343
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7223 - 7235[article]Discriminative-dictionary-learning-based multilevel point-cluster features for ALS point-cloud classification / Zhenxin Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
[article]
Titre : Discriminative-dictionary-learning-based multilevel point-cluster features for ALS point-cloud classification Type de document : Article/Communication Auteurs : Zhenxin Zhang, Auteur ; Liqiang Zhang, Auteur ; Xiaohua Tong, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 7309 - 7322 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage automatique
[Termes IGN] classificateur
[Termes IGN] codage
[Termes IGN] extraction de points
[Termes IGN] problème de Dirichlet
[Termes IGN] semis de pointsRésumé : (Auteur) Efficient presentation and recognition of on-ground objects from airborne laser scanning (ALS) point clouds are a challenging task. In this paper, we propose an approach that combines a discriminative-dictionary-learning-based sparse coding and latent Dirichlet allocation (LDA) to generate multilevel point-cluster features for ALS point-cloud classification. Our method takes advantage of the labels of training data and each dictionary item to enforce discriminability in sparse coding during the dictionary learning process and more accurately further represent point-cluster features. The multipath AdaBoost classifiers with the hierarchical point-cluster features are trained, and we apply them to the classification of unknown points by the heritance of the recognition results under different paths. Experiments are performed on different ALS point clouds; the experimental results have shown that the extracted point-cluster features combined with the multipath classifiers can significantly enhance the classification accuracy, and they have demonstrated the superior performance of our method over other techniques in point-cloud classification. Numéro de notice : A2016-931 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2599163 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2599163 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83345
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7309 - 7322[article]Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy / Xiao Song in ISPRS Journal of photogrammetry and remote sensing, vol 122 (December 2016)
[article]
Titre : Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy Type de document : Article/Communication Auteurs : Xiao Song, Auteur ; Wei Feng, Auteur ; Li He, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 57 – 67 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] angle de visée
[Termes IGN] Canada
[Termes IGN] Chine
[Termes IGN] feuille (végétation)
[Termes IGN] indice de végétation
[Termes IGN] spectromètre imageur
[Termes IGN] teneur en azoteRésumé : (Auteur) Real-time, nondestructive monitoring of crop nitrogen (N) status is a critical factor for precision N management during wheat production. Over a 3-year period, we analyzed different wheat cultivars grown under different experimental conditions in China and Canada and studied the effects of viewing angle on the relationships between various vegetation indices (VIs) and leaf nitrogen concentration (LNC) using hyperspectral data from 11 field experiments. The objective was to improve the prediction accuracy by minimizing the effects of viewing angle on LNC estimation to construct a novel vegetation index (VI) for use under different experimental conditions. We examined the stability of previously reported optimum VIs obtained from 13 traditional indices for estimating LNC at 13 viewing zenith angles (VZAs) in the solar principal plane (SPP). Backscattering direction showed better index performance than forward scattering direction. Red-edge VIs including modified normalized difference vegetation index (mND705), ratio index within the red edge region (RI-1dB) and normalized difference red edge index (NDRE) were highly correlated with LNC, as confirmed by high R2 determination coefficients. However, these common VIs tended to saturation, as the relationships strongly depended on experimental conditions. To overcome the influence of VZA on VIs, the chlorophyll- and LNC-sensitive NDRE index was divided by the floating-position water band index (FWBI) to generate the integrated narrow-band vegetation index. The highest correlation between the novel NDRE/FWBI parameter and LNC (R2 = 0.852) occurred at −10°, while the lowest correlation (R2 = 0.745) occurred at 60°. NDRE/FWBI was more highly correlated with LNC than existing commonly used VIs at an identical viewing zenith angle. Upon further analysis of angle combinations, our novel VI exhibited the best performance, with the best prediction accuracy at 0° to −20° (R2 = 0.838, RMSE = 0.360) and relatively good accuracy at 0° to −30° (R2 = 0.835, RMSE = 0.366). As it is possible to monitor plant N status over a wide range of angles using portable spectrometers, viewing angles of as much as 0° to −30° are common. Consequently, we developed a united model across angles of 0° to −30° to reduce the effects of viewing angle on LNC prediction in wheat. The proposed combined NDRE/FWBI parameter, designated the wide-angle-adaptability nitrogen index (WANI), is superior for estimating LNC in wheat on a regional scale in China and Canada. Numéro de notice : A2016--021 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.10.002 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.10.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83884
in ISPRS Journal of photogrammetry and remote sensing > vol 122 (December 2016) . - pp 57 – 67[article]From inventory to consumer biomass availability - the ITOC model / Udo Mantau in Annals of Forest Science, vol 73 n° 4 (December 2016)PermalinkGestion des peuplements en forêt publique : nouvelles pistes de recherche, développement et innovation / Christine Deleuze in Revue forestière française, vol 68 n° 6 (décembre 2016)PermalinkHierarchical and adaptive phase correlation for precise disparity estimation of UAV images / Jie Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkImproved ambiguity resolution for URTK with dynamic atmosphere constraints / Weiming Tang in Journal of geodesy, vol 90 n° 12 (December 2016)PermalinkA methodological protocol for Annex I Habitats monitoring: the contribution of Vegetation science / D. Gigante in Plant sociology, vol 53 n° 2 (December 2016)PermalinkMultiband image fusion based on spectral unmixing / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkVariations of total electron content over Serbia during the increased solar activity period in 2013 and 2014 / Dragan Blagojevic in Geodetski vestnik, vol 60 n° 4 (December 2016)PermalinkThe driving forces of landscape change in Europe: A systematic review of the evidence / Tobias Plieninger in Land use policy, vol 57 (30 November 2016)PermalinkEffective number of layers: A new measure for quantifying three-dimensional stand structure based on sampling with terrestrial LiDAR / Martin Ehbrecht in Forest ecology and management, vol 380 (15 november 2016)PermalinkOpen-grown trees as key habitats for arthropods in temperate woodlands: The diversity, composition, and conservation value of associated communities / Pavel Sebek in Forest ecology and management, vol 380 (15 november 2016)PermalinkAn approach for estimating time-variable rates from geodetic time series / Olga Didova in Journal of geodesy, vol 90 n° 11 (November 2016)PermalinkCulture for all / R. Scibetta in GEO: Geoconnexion international, vol 15 n° 10 (November - December 2016)PermalinkFast three-dimensional empirical mode decomposition of hyperspectral images for class-oriented multitask learning / Zhi He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkGuided superpixel method for topographic map processing / Qiguang Miao in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkHigh-frequency Earth rotation variations deduced from altimetry-based ocean tides / Matthias Madzak in Journal of geodesy, vol 90 n° 11 (November 2016)PermalinkInterference localization from space: theoretical background / Luca Canzian in Inside GNSS, vol 11 n° 6 (November - December 2016)PermalinkLocalization of a mobile laser scanner via dimensional reduction / Ville V. Lehtola, in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)PermalinkMultiple kernel learning based on discriminative kernel clustering for hyperspectral band selection / Jie Feng in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkParallel cartographic modeling: a methodology for parallelizing spatial data processing / Eric Shook in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)PermalinkA phase-altimetric simulator : studying the sensitivity of Earth-reflected GNSS signals to ocean topography / Aaron Maximilian Semmling in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkRapid updating and improvement of airborne LIDAR DEMs through ground-based SfM 3-D modeling of volcanic features / Stephan Kolzenburg in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkReview of the state of the art and future prospects of the ground-based GNSS meteorology in Europe / Guergana Guerova in Atmospheric measurement techniques, vol 9 n° 11 (November 2016)PermalinkA shared perspective for PGIS and VGI / Jeroen Verplanke in Cartographic journal (the), Vol 53 n° 4 (November 2016)PermalinkSkeletal camera network embedded structure-from-motion for 3D scene reconstruction from UAV images / Zhihua Xua in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)PermalinkThe 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)PermalinkTravel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data / Luliang Tang in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)PermalinkNatural regeneration of Pinus pinaster and Eucalyptus globulus from plantation into adjacent natural habitats / Patricia Fernandes in Forest ecology and management, vol 378 (15 October 2016)PermalinkAn intensity recovery algorithm (IRA) for minimizing the edge effect of LIDAR data / Fabiane Bordin in European journal of remote sensing, vol 49 n° 1 (2016)PermalinkAutomatic targeted-domain spatiotemporal event detection in twitter / Ting Hua in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkDeep feature extraction and classification of hyperspectral images based on convolutional neural networks / Yushi Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)PermalinkDesign drivers and new trends for navigation message authentication schemes for GNSS systems / Gianluca Caparra in Inside GNSS, vol 11 n° 5 (September - October 2016)PermalinkDeveloping a web-based system for supervised classification of remote sensing images / Ziheng Sun in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkDisaster debris estimation using high-resolution polarimetric stereo-SAR / Christian N. Koyama in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)PermalinkL’écocomplexe de Païolive en Ardèche méridionale (France) : un pic de biodiversité du hotspot méditerranéen / Patrick Blandin in Ecologia mediterranea, vol 42 n° 2 (2016)PermalinkGenerating GPS satellite fractional cycle bias for ambiguity-fixed precise point positioning / Pan Li in GPS solutions, vol 20 n° 4 (October 2016)PermalinkModeling the effects of horizontal positional error on classification accuracy statistics / Henry B. Glick in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)PermalinkA probabilistic approach to detect mixed periodic patterns from moving object data / Jun Li in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkRelative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation / Alyssa Endres in European journal of remote sensing, vol 49 n° 1 (2016)PermalinkSMAP L-Band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations / Priscilla N. Mohammed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)Permalinkvol 90 n° 10 - October 2016 - The Geodesist’s Handbook 2016 (Bulletin de Journal of geodesy) / Hermann DrewesPermalinkUnderstanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley, Zimbabwe using Geographic Information Systems and remote sensing / Mbulisi Sibanda in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)PermalinkUsing a regional numerical weather prediction model for GNSS positioning over Brazil / Daniele Barroca Marra Alves in GPS solutions, vol 20 n° 4 (October 2016)PermalinkDead wood availability in managed Swedish forests – Policy outcomes and implications for biodiversity / Bengt Gunnar Jonsson in Forest ecology and management, vol 376 (15 September 2016)PermalinkAutomatic recognition of long period events from volcano tectonic earthquakes at Cotopaxi volcano / Román A. Lara-Cueva in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkCHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations / Karolina D. Fieber in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)Permalink