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Precise orbit determination of the Fengyun-3C satellite using onboard GPS and BDS observations / Min Li in Journal of geodesy, vol 91 n° 11 (November 2017)
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Titre : Precise orbit determination of the Fengyun-3C satellite using onboard GPS and BDS observations Type de document : Article/Communication Auteurs : Min Li, Auteur ; Wenwen Li, Auteur ; Chuang Shi, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1313 - 1327 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales
[Termes IGN] analyse comparative
[Termes IGN] correction du trajet multiple
[Termes IGN] Feng-Yun-3
[Termes IGN] orbite géostationnaire
[Termes IGN] orbitographie
[Termes IGN] orbitographie par GNSS
[Termes IGN] positionnement par BeiDou
[Termes IGN] positionnement par GPS
[Termes IGN] précision du positionnement
[Termes IGN] satellite météorologiqueRésumé : (Auteur) The GNSS Occultation Sounder instrument onboard the Chinese meteorological satellite Fengyun-3C (FY-3C) tracks both GPS and BDS signals for orbit determination. One month’s worth of the onboard dual-frequency GPS and BDS data during March 2015 from the FY-3C satellite is analyzed in this study. The onboard BDS and GPS measurement quality is evaluated in terms of data quantity as well as code multipath error. Severe multipath errors for BDS code ranges are observed especially for high elevations for BDS medium earth orbit satellites (MEOs). The code multipath errors are estimated as piecewise linear model in 2∘×2∘ grid and applied in precise orbit determination (POD) calculations. POD of FY-3C is firstly performed with GPS data, which shows orbit consistency of approximate 2.7 cm in 3D RMS (root mean square) by overlap comparisons; the estimated orbits are then used as reference orbits for evaluating the orbit precision of GPS and BDS combined POD as well as BDS-based POD. It is indicated that inclusion of BDS geosynchronous orbit satellites (GEOs) could degrade POD precision seriously. The precisions of orbit estimates by combined POD and BDS-based POD are 3.4 and 30.1 cm in 3D RMS when GEOs are involved, respectively. However, if BDS GEOs are excluded, the combined POD can reach similar precision with respect to GPS POD, showing orbit differences about 0.8 cm, while the orbit precision of BDS-based POD can be improved to 8.4 cm. These results indicate that the POD performance with onboard BDS data alone can reach precision better than 10 cm with only five BDS inclined geosynchronous satellite orbit satellites and three MEOs. As the GNOS receiver can only track six BDS satellites for orbit positioning at its maximum channel, it can be expected that the performance of POD with onboard BDS data can be further improved if more observations are generated without such restrictions. Numéro de notice : A2017-705 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1027-9 En ligne : https://doi.org/10.1007/s00190-017-1027-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88086
in Journal of geodesy > vol 91 n° 11 (November 2017) . - pp 1313 - 1327[article]Salient object detection in complex scenes via D-S evidence theory based region classification / Chunlei Yang in The Visual Computer, vol 33 n° 11 (November 2017)
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Titre : Salient object detection in complex scenes via D-S evidence theory based region classification Type de document : Article/Communication Auteurs : Chunlei Yang, Auteur ; Jiexin Pu, Auteur ; Yongsheng Dong, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1415 - 1428 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] fusion de données
[Termes IGN] information complexe
[Termes IGN] scène intérieure
[Termes IGN] segmentation d'image
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] zone saillante 3DRésumé : (Auteur) In complex scenes, multiple objects are often concealed in cluttered backgrounds. Their saliency is difficult to be detected by using conventional methods, mainly because single color contrast can not shoulder the mission of saliency measure; other image features should be involved in saliency detection to obtain more accurate results. Using Dempster-Shafer (D-S) evidence theory based region classification, a novel method is presented in this paper. In the proposed framework, depth feature information extracted from a coarse map is employed to generate initial feature evidences which indicate the probabilities of regions belonging to foreground or background. Based on the D-S evidence theory, both uncertainty and imprecision are modeled, and the conflicts between different feature evidences are properly resolved. Moreover, the method can automatically determine the mass functions of the two-stage evidence fusion for region classification. According to the classification result and region relevance, a more precise saliency map can then be generated by manifold ranking. To further improve the detection results, a guided filter is utilized to optimize the saliency map. Both qualitative and quantitative evaluations on three publicly challenging benchmark datasets demonstrate that the proposed method outperforms the contrast state-of-the-art methods, especially for detection in complex scenes. Numéro de notice : A2017-713 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s00371-016-1288-y En ligne : https://doi.org/10.1007/s00371-016-1288-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88094
in The Visual Computer > vol 33 n° 11 (November 2017) . - pp 1415 - 1428[article]Sparse bayesian learning-based time-variant deconvolution / Sanyi Yuan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)
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Titre : Sparse bayesian learning-based time-variant deconvolution Type de document : Article/Communication Auteurs : Sanyi Yuan, Auteur ; Shangxu Wang, Auteur ; Ming Ma, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 6182 - 6194 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] amélioration du contraste
[Termes IGN] apprentissage automatique
[Termes IGN] déconvolutionRésumé : (Auteur) In seismic exploration, the wavelet-filtering effect and Q-filtering (amplitude attenuation and velocity dispersion) effect blur the reflection image of subsurface layers. Therefore, both wavelet- and Q-filtering effects should be reduced to retrieve a high-quality subsurface image, which is significant for fine reservoir interpretation. We derive a nonlinear time-variant convolution model to sparsely represent nonstationary seismograms in time domain involving these two effects and present a time-variant deconvolution (TVD) method based on sparse Bayesian learning (SBL) to solve the model to obtain a high-quality reflectivity image. The SBL-based TVD essentially obtains an optimum posterior mean of the reflectivity image, which is regarded as the inverted reflectivity result, by iteratively solving a Bayesian maximum posterior and a type-II maximum likelihood. Because a hierarchical Gaussian prior for reflectivity controlled by model-dependent hyper-parameters is adopted to approximately represent the fact that reflectivity is sparse, SBL-based TVD can retrieve a sparse reflectivity image through the principled sequential addition and deletion of Q-dependent time-variant wavelets. In general, strong reflectors are acquired relatively earlier, whereas weak reflectors and deep reflectors are imaged later. The method has the capacity to avoid false artifacts represented by sequential positive or negative reflectivity spikes with short two-way travel time, which typically occur within stationary deconvolution outcomes. Synthetic, laboratorial, and field data examples are used to demonstrate the effectiveness of the method and illustrate its advantages over SBL-based stationary deconvolution and TVD using an l2-norm or an l1-norm regularization. The results show that SBL-based TVD is a potentially effective, stable, and high-quality imaging tool. Numéro de notice : A2017-745 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2722223 En ligne : https://doi.org/10.1109/TGRS.2017.2722223 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88779
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 11 (November 2017) . - pp 6182 - 6194[article]Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns / Zhixiang Fang in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)
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Titre : Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns Type de document : Article/Communication Auteurs : Zhixiang Fang, Auteur ; Xiping Yang, Auteur ; Yang Xu, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 2119 - 2141 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] analyse spatio-temporelle
[Termes IGN] échelle variable
[Termes IGN] géopositionnement
[Termes IGN] Kouangtoung (Chine)
[Termes IGN] mobilité urbaine
[Termes IGN] réseau de transport
[Termes IGN] téléphonie mobile
[Termes IGN] trace GPS
[Termes IGN] transport collectifRésumé : (Auteur) Understanding the stability of urban flows is critical for urban transportation, urban planning and public health. However, few studies have measured the stability of aggregate human convergence or divergence patterns. We propose a spatiotemporal model for assessing the stability of human convergence and divergence patterns. A mobile phone location data set obtained from Shenzhen, China, was used to assess the stability of daily human convergence and divergence patterns at three different spatial scales, i.e. points (cell phone towers), lines (bus lines) and areas (traffic analysis zones [TAZs]). Our analysis results demonstrated that the proposed model can identify points and bus lines with time-dependent variations in stability, which is useful for delineating TAZs for transportation planning, or adjusting bus timetables and routes to meet the needs of bus riders. Comparisons of the results obtained from the proposed model and the widely used entropy measure indicated that the proposed model is suitable for assessing the differences in stability for various types of spatial analysis units, e.g. cell phone towers. Therefore, the proposed model is a useful alternative approach of measuring spatiotemporal stability of aggregate human convergence and divergence patterns, which can be derived from the space–time trajectories of moving objects. Numéro de notice : A2017-698 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1346256 En ligne : https://doi.org/10.1080/13658816.2017.1346256 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88079
in International journal of geographical information science IJGIS > vol 31 n° 11-12 (November - December 2017) . - pp 2119 - 2141[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017061 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017062 RAB Revue Centre de documentation En réserve L003 Disponible The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data / Alby D. Rocha in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
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Titre : The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data Type de document : Article/Communication Auteurs : Alby D. Rocha, Auteur ; Thomas A. Groen, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 61 - 74 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] complexité
[Termes IGN] image hyperspectrale
[Termes IGN] méthode robuste
[Termes IGN] modèle de simulation
[Termes IGN] optimisation (mathématiques)
[Termes IGN] précision
[Termes IGN] régression
[Termes IGN] validation des donnéesRésumé : (Auteur) The growing number of narrow spectral bands in hyperspectral remote sensing improves the capacity to describe and predict biological processes in ecosystems. But it also poses a challenge to fit empirical models based on such high dimensional data, which often contain correlated and noisy predictors. As sample sizes, to train and validate empirical models, seem not to be increasing at the same rate, overfitting has become a serious concern. Overly complex models lead to overfitting by capturing more than the underlying relationship, and also through fitting random noise in the data. Many regression techniques claim to overcome these problems by using different strategies to constrain complexity, such as limiting the number of terms in the model, by creating latent variables or by shrinking parameter coefficients. This paper is proposing a new method, named Naïve Overfitting Index Selection (NOIS), which makes use of artificially generated spectra, to quantify the relative model overfitting and to select an optimal model complexity supported by the data. The robustness of this new method is assessed by comparing it to a traditional model selection based on cross-validation. The optimal model complexity is determined for seven different regression techniques, such as partial least squares regression, support vector machine, artificial neural network and tree-based regressions using five hyperspectral datasets. The NOIS method selects less complex models, which present accuracies similar to the cross-validation method. The NOIS method reduces the chance of overfitting, thereby avoiding models that present accurate predictions that are only valid for the data used, and too complex to make inferences about the underlying process. Numéro de notice : A2017-722 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.09.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.09.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88407
in ISPRS Journal of photogrammetry and remote sensing > vol 133 (November 2017) . - pp 61 - 74[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017112 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017113 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Tree species classification using within crown localization of waveform LiDAR attributes / Rosmarie Blomley in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
PermalinkURBANSIMUL, outil web d'analyse foncière et d'aide à la décision / Bertrand Leroux in Signature, n° 64 (octobre 2017)
PermalinkAn effective spherical panoramic LoD model for a mobile street view service / Xianxiong Liu in Transactions in GIS, vol 21 n° 5 (October 2017)
PermalinkApplicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods / Fatemeh Falah in Geocarto international, vol 32 n° 10 (October 2017)
PermalinkAssessment of PPP integer ambiguity resolution using GPS, GLONASS and BeiDou (IGSO, MEO) constellations / Yanyan Liu in GPS solutions, vol 21 n° 4 (October 2017)
PermalinkDiscovering non-compliant window co-occurrence patterns / Reem Y. Ali in Geoinformatica, vol 21 n° 4 (October - December 2017)
PermalinkEnhancing plant diversity and mitigating BVOC emissions of urban green spaces through the introduction of ornamental tree species / Yuan Ren in Urban Forestry & Urban Greening, vol 27 (October 2017)
PermalinkEvaluation of NTCM-BC and a proposed modification for single-frequency positioning / Xiaohong Zhang in GPS solutions, vol 21 n° 4 (October 2017)
PermalinkGeometric quality assessment of trajectory-generated VGI road networks based on the symmetric arc similarity / Yan Lyu in Transactions in GIS, vol 21 n° 5 (October 2017)
PermalinkHyperspectral dimensionality reduction for biophysical variable statistical retrieval / Juan Pablo Rivera-Caicedo in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
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