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Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation / Feng Wang in Journal of geodesy, vol 96 n° 4 (April 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 4 (April 2022) . - n° 17 Titre : Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation Type de document : Article/Communication Auteurs : Feng Wang, Auteur ; Dongkai Yang, Auteur ; Guodong Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Chine [Termes IGN] données altimétriques [Termes IGN] données marégraphiques [Termes IGN] hauteurs de mer [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle géométrique [Termes IGN] rapport signal sur bruit [Termes IGN] récepteur GNSS [Termes IGN] réflectométrie par GNSS [Termes IGN] signal BeiDou [Termes IGN] surface de la mer [Termes IGN] vague Résumé : (auteur) In this paper, the methods retrieving tide and SWH using reflected BeiDou GEO satellite signals are proposed, and a data-driven method is proposed to calibrate sea state bias of the retrieved tide. In addition, an estimator combining multi-satellite observation based on linear unbiased minimum variance (LUMV) is developed to improve the retrieved precision. The B1I signal experiments in Qingdao and Shenzhen show after calibrating sea state influence using the proposed method, the root-mean-square error (RMSE) could fall to 0.40 m from 0.45 m, and compared to the single-satellite observation, the multi-satellite observation based on the LUMV estimator could significantly reduce the RMSE of the retrieved tide to 0.16 m. Shenzhen experiment is also used to evaluate the performance of retrieving SWH and the determination coefficient of 0.60 is obtained. This paper also conducts Monte Carlo simulation and experiment to evaluate the altimetry and measuring SWH precision using reflected B3I signal. The simulated results when SNR is over 5 dB, incoherent averaging number is 10000, and the receiver bandwidth is over 45 MHz, the estimated precision of the delay can reach up ∼0.15 m, and the precision of the normalized area ranges from 0.2 to 0.3 m. The B3I experiment show that compared to B1I signal, when the reflected signal from individual satellite is used, the better precision with the RMSE of 0.25 can be obtained, and when combining the measurements from the three satellites using LUMV estimator, the RMSE reduces to 0.16 m. Further, the precision of 0.12 m can be obtained by calibrating the sea state influence. Numéro de notice : A2022-213 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01605-0 Date de publication en ligne : 06/03/2022 En ligne : https://doi.org/10.1007/s00190-022-01605-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100050 [article]

STC-Det: A slender target detector combining shadow and target information in optical satellite images / Zhaoyang Huang in Remote sensing, vol 13 n° 20 (October-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 20 (October-2 2021) . - n° 4183 Titre : STC-Det: A slender target detector combining shadow and target information in optical satellite images Type de document : Article/Communication Auteurs : Zhaoyang Huang, Auteur ; Feng Wang, Auteur ; Hongjian You, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4183 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement automatique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] détection de cible [Termes IGN] fusion de données [Termes IGN] image satellite [Termes IGN] ombre Résumé : (auteur) Object detection has made great progress. However, due to the unique imaging method of optical satellite remote sensing, the detection of slender targets is still insufficient. Specifically, the perspective of optical satellites is small, and the characteristics of slender targets are severely lost during imaging, resulting in insufficient detection task information; at the same time, the appearance of slender targets in the image is greatly affected by the satellite perspective, which is likely to cause insufficient generalization capabilities of conventional detection models. In response to these two points, we have made some improvements. First, in this paper, we introduce the shadow as auxiliary information to complement the trunk features of the target lost in imaging. Second, to reduce the impact of satellite perspective on imaging, in this paper, we use the characteristic that shadow information is not affected by satellite perspective to design STC-Det. STC-Det treats the shadow and the target as two different types of targets and uses the shadow information to assist the detection, reducing the impact of the satellite perspective on detection. Among them, in order to improve the performance of STC-Det, we propose an automatic matching method (AMM) of shadow and target and a feature fusion method (FFM). Finally, this paper proposes a new method to calculate the heatmaps of detectors, which verifies the effectiveness of the proposed network in a visual way. Experiments show that when the satellite perspective is variable, the precision of STC-Det is increased by 1.7%, and when the satellite perspective is small, the precision of STC-Det is increased by 5.2%. Numéro de notice : A2021-804 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13204183 Date de publication en ligne : 19/10/2021 En ligne : https://doi.org/10.3390/rs13204183 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98860 [article]

A generic framework for improving the geopositioning accuracy of multi-source optical and SAR imagery / Niangang Jiao in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 169 (November 2020) . - pp 377 - 388 Titre : A generic framework for improving the geopositioning accuracy of multi-source optical and SAR imagery Type de document : Article/Communication Auteurs : Niangang Jiao, Auteur ; Feng Wang, Auteur ; Hongjian You, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 377 - 388 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] chaîne de traitement [Termes IGN] correction géométrique [Termes IGN] étalonnage géométrique [Termes IGN] géolocalisation [Termes IGN] image Gaofen [Termes IGN] image Jilin [Termes IGN] image optique [Termes IGN] image radar moirée [Termes IGN] image satellite [Termes IGN] point d'appui [Termes IGN] précision géométrique (imagerie) Résumé : (auteur) To date, numerous Earth observation datasets from different types of satellites have been widely used in photogrammetric fields, including urban 3D modelling and geographic information systems. The development of small satellites has provided a new way to obtain repeated observations in a short period. However, compared with that of standard satellite imagery, the geometric performance of imagery from small satellites is relatively poor, restricting their photogrammetric applications. Traditional methods can improve the accuracy of optical images with the addition of well-distributed ground control points (GCPs), which require considerable financial and human resources. The collection of multi-view datasets is an alternative method for geometric processing without GCPs, but relies heavily on the stability and revisit period of satellite platforms. Therefore, this paper presents a framework for improving the geopositioning accuracy of multi-source datasets obtained from optical and synthetic aperture radar (SAR) satellites, and a novel heterogeneous weight strategy is proposed based on an analysis of the geometric error sources of SAR and optical images. The geometric performance of multi-source optical imagery from the Jilin-1 (JL-1) small satellite constellation is evaluated and analysed first, and then Gaofen-3 (GF-3) SAR images are calibrated based on statistical analysis for the production of virtual control points (VCPs). Based on our proposed heterogeneous weight strategy, multi-source optical and SAR images are integrated to improve the geopositioning accuracy. Experimental results indicate that our proposed model can achieve the best performance compared with other popular models, producing an accuracy of approximately 3 m in planimetry and 2 m in height, thereby providing a generic way to synergistically use multi-source remote sensing data. Numéro de notice : A2020-642 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.09.017 Date de publication en ligne : 12/10/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.09.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96066 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020111	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2020113	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2020112	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Association rules-based multivariate analysis and visualization of spatiotemporal climate data / Feng Wang in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 7 (July 2018) Titre : Association rules-based multivariate analysis and visualization of spatiotemporal climate data Type de document : Article/Communication Auteurs : Feng Wang, Auteur ; Wenwen Li, Auteur ; Sizhe Wang, Auteur ; Chris R. Johnson, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] analyse multivariée [Termes IGN] Arctique [Termes IGN] cyclone [Termes IGN] données météorologiques [Termes IGN] données spatiotemporelles [Termes IGN] phénomène atmosphérique [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Understanding atmospheric phenomena involves analysis of large-scale spatiotemporal multivariate data. The complexity and heterogeneity of such data pose a significant challenge in discovering and understanding the association between multiple climate variables. To tackle this challenge, we present an interactive heuristic visualization system that supports climate scientists and the public in their exploration and analysis of atmospheric phenomena of interest. Three techniques are introduced: (1) web-based spatiotemporal climate data visualization; (2) multiview and multivariate scientific data analysis; and (3) data mining-enabled visual analytics. The Arctic System Reanalysis (ASR) data are used to demonstrate and validate the effectiveness and usefulness of our method through a case study of “The Great Arctic Cyclone of 2012”. The results show that different variables have strong associations near the polar cyclone area. This work also provides techniques for identifying multivariate correlation and for better understanding the driving factors of climate phenomena. Numéro de notice : A2018-503 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7070266 Date de publication en ligne : 09/07/2018 En ligne : https://doi.org/10.3390/ijgi7070266 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90575 [article]