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Integration of ZY3-02 satellite laser altimetry data and stereo images for high-accuracy mapping / Guoyuan Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 9 (September 2018)
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Titre : Integration of ZY3-02 satellite laser altimetry data and stereo images for high-accuracy mapping Type de document : Article/Communication Auteurs : Guoyuan Li, Auteur ; Xinming Tang, Auteur ; Xiaoming Gao, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 569 - 578 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] Chine
[Termes IGN] données altimétriques
[Termes IGN] données ICEsat
[Termes IGN] image ZiYuan-3
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] ZiYuan-3Résumé : (Auteur) Integration of satellite laser altimetry data and stereo images without ground control points (GCPs) is an attractive method for global mapping. In this paper, we propose a new strategy of integrating Ziyuan3-02 (ZY3-02) satellite stereo images and laser altimetry data using a rigorous sensor model (RSM) with laser ranging constraint under the synchronized and rational function model (RFM) with laser elevation constraint under the non-synchronized capture for high-accuracy mapping without GCPs. Four experimental regions in China are selected to validate the method. The results show that the ZY3-02 satellite laser altimetry data can be used to improve the elevation accuracy of stereo images to better than 3.0 m without GCPs. All of the conclusions are valuable for the development of China's next generation of surveying and mapping satellites. Numéro de notice : A2018-362 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.9.569 Date de publication en ligne : 01/09/2018 En ligne : https://doi.org/10.14358/PERS.84.9.569 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90673
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 9 (September 2018) . - pp 569 - 578[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018091 RAB Revue Centre de documentation En réserve L003 Disponible Investigation of the success of monitoring slow motion landslides using Persistent Scatterer Interferometry and GNSS methods / K.O. Hastaoglu in Survey review, vol 50 n° 363 (September 2018)
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Titre : Investigation of the success of monitoring slow motion landslides using Persistent Scatterer Interferometry and GNSS methods Type de document : Article/Communication Auteurs : K.O. Hastaoglu, Auteur ; F. Poyraz, Auteur ; T. Turk, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 475 - 486 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] effondrement de terrain
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] réseau géodésique spécifique
[Termes IGN] surveillance géologique
[Termes IGN] TurquieRésumé : (Auteur) The purpose of this study is to determine deformations in landslide areas with two methods, Persistent Scatterer Interferometry (PSI) and GNSS (Global Navigation Satellite System). In the Koyulhisar landslide area, 53 GNSS points were established throughout the region. Velocity values for these points are three-dimensional. In addition, TerraSAR-X SAR (Synthetic Aperture Radar) images were processed with Stanford Method for Persistent Scatterers software. Slip surfaces of the landslide region in the direction of the line of sight were calculated from PSI in addition to one-dimensional velocity values. These values were compared to GNSS data converted to the same format. GNSS was found more effective for tracking local deformations based on point data while PSI was better at areal movements. Using both methods together is the most effective in this region because there are small local movements independent of regional movements. Numéro de notice : A2018-449 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1295631 Date de publication en ligne : 05/03/2017 En ligne : https://doi.org/10.1080/00396265.2017.1295631 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91035
in Survey review > vol 50 n° 363 (September 2018) . - pp 475 - 486[article]A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 8 (August 2018)
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Titre : A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification Type de document : Article/Communication Auteurs : Zhen Wang, Auteur ; Liqiang Zhang, Auteur ; Liang Zhang, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 4594 - 4604 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] arbre aléatoire
[Termes IGN] classification par réseau neuronal
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] méthode robuste
[Termes IGN] Perceptron multicouche
[Termes IGN] pondération
[Termes IGN] précision de la classification
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsMots-clés libres : deep neural network with spatial pooling (DNNSP) Résumé : (Auteur) The large number of object categories and many overlapping or closely neighboring objects in large-scale urban scenes pose great challenges in point cloud classification. Most works in deep learning have achieved a great success on regular input representations, but they are hard to be directly applied to classify point clouds due to the irregularity and inhomogeneity of the data. In this paper, a deep neural network with spatial pooling (DNNSP) is proposed to classify large-scale point clouds without rasterization. The DNNSP first obtains the point-based feature descriptors of all points in each point cluster. The distance minimum spanning tree-based pooling is then applied in the point feature representation to describe the spatial information among the points in the point clusters. The max pooling is next employed to aggregate the point-based features into the cluster-based features. To assure the DNNSP is invariant to the point permutation and sizes of the point clusters, the point-based feature representation is determined by the multilayer perception (MLP) and the weight sharing for each point is retained, which means that the weight of each point in the same layer is the same. In this way, the DNNSP can learn the features of points scaled from the entire regions to the centers of the point clusters, which makes the point cluster-based feature representations robust and discriminative. Finally, the cluster-based features are input to another MLP for point cloud classification. We have evaluated qualitatively and quantitatively the proposed method using several airborne laser scanning and terrestrial laser scanning point cloud data sets. The experimental results have demonstrated the effectiveness of our method in improving classification accuracy. Numéro de notice : A2018-471 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2829625 Date de publication en ligne : 22/05/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2829625 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91253
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 8 (August 2018) . - pp 4594 - 4604[article]The New Zealand gravimetric quasigeoid model 2017 that incorporates nationwide airborne gravimetry / Jack C. McCubbine in Journal of geodesy, vol 92 n° 8 (August 2018)
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Titre : The New Zealand gravimetric quasigeoid model 2017 that incorporates nationwide airborne gravimetry Type de document : Article/Communication Auteurs : Jack C. McCubbine, Auteur ; M. J. Amos, Auteur ; F. C. Tontini, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 923 - 937 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] anomalie de pesanteur
[Termes IGN] géoïde gravimétrique
[Termes IGN] gravimétrie aérienne
[Termes IGN] intégrale de Stokes
[Termes IGN] levé gravimétrique
[Termes IGN] modèle de géopotentiel
[Termes IGN] Nouvelle-Zélande
[Termes IGN] quasi-géoïdeRésumé : (Auteur) A one arc-minute resolution gravimetric quasigeoid model has been computed for New Zealand, covering the region 25∘S–60∘S and 160∘E–170∘W. It was calculated by Wong and Gore modified Stokes integration using the remove–compute–restore technique with the EIGEN-6C4 global gravity model as the reference field. The gridded gravity data used for the computation consisted of 40,677 land gravity observations, satellite altimetry-derived marine gravity anomalies, historical shipborne marine gravity observations and, importantly, approximately one million new airborne gravity observations. The airborne data were collected with the specific intention of reinforcing the shortcomings of the existing data in areas of rough topography inaccessible to land gravimetry and in coastal areas where shipborne gravimetry cannot be collected and altimeter-derived gravity anomalies are generally poor. The new quasigeoid has a nominal precision of ±48mm on comparison with GPS-levelling data, which is approximately 14mm less than its predecessor NZGeoid09. Numéro de notice : A2018-457 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1103-1 Date de publication en ligne : 12/12/2017 En ligne : https://doi.org/10.1007/s00190-017-1103-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91054
in Journal of geodesy > vol 92 n° 8 (August 2018) . - pp 923 - 937[article]Odometer, low-cost inertial sensors, and four-GNSS data to enhance PPP and attitude determination / Zhouzheng Gao in GPS solutions, vol 22 n° 3 (July 2018)
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Titre : Odometer, low-cost inertial sensors, and four-GNSS data to enhance PPP and attitude determination Type de document : Article/Communication Auteurs : Zhouzheng Gao, Auteur ; Maorong Ge, Auteur ; You Li, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] centrale inertielle
[Termes IGN] données BeiDou
[Termes IGN] données Galileo
[Termes IGN] données GLONASS
[Termes IGN] données GNSS
[Termes IGN] données GPS
[Termes IGN] GNSS assisté pour la navigation
[Termes IGN] odomètre
[Termes IGN] orientation du capteur
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision du positionnementRésumé : (Auteur) To upgrade the positioning accuracy, re-initialization speed, and attitude determination performance of precise point positioning (PPP) in dynamic applications, we proposed a multi-sensor fusion system consisting of four global navigation satellite systems (GNSSs), namely GPS, BDS, Galileo, and GLONASS, several low-cost inertial sensors, and an odometer. The study shows that the performance of PPP in terms of continuity, reliability, stability, and re-initialization speed improves by such a multi-sensor fusion system. This manifests itself in a significantly increased accuracy. For position solutions, compared to un-aided PPP solutions, the improvements achieved using low-cost inertial navigation system (INS) are about 36.4, 38.7, and 31.3% in the north, east, and vertical components, respectively, and the improvement using odometer are about 1.58, 0.35, and 4.32% relative to the INS-aided PPP solutions. Moreover, using the odometer can provide more than 2.1, 1.4, and 50.6% attitude improvements for roll, pitch, and heading angles compared to the attitude solutions obtained from the INS-aided PPP system. Under GNSS outage conditions, the mean position improvements using the odometer are about 2.3, 1.8, and 8.7%, with maximum increases of 74.6, 74.7, and 28.3%, and the average attitude improvements are about 4.7, 5.4, and 3.3%, with maximum increases of 36.4, 31.7, and 28.9%, respectively. This means that the odometer can enhance the performance of PPP and PPP/INS integration in challenging dynamic conditions. Numéro de notice : A2018-375 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-018-0725-y Date de publication en ligne : 05/04/2018 En ligne : https://doi.org/10.1007/s10291-018-0725-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90779
in GPS solutions > vol 22 n° 3 (July 2018)[article]Predicting foreground object ambiguity and efficiently crowdsourcing the segmentation(s) / Danna Gurari in International journal of computer vision, vol 126 n° 7 (July 2018)
PermalinkThe impact of solid Earth-tide model error on tropospheric zenith delay estimates and GPS coordinate time series / Fei Li in Survey review, vol 50 n° 361 (July 2018)
PermalinkAssessment of Sentinel-1A data for rice crop classification using random forests and support vector machines / Nguyen-Thanh Son in Geocarto international, vol 33 n° 6 (June 2018)
PermalinkData collection methods for forest inventory: a comparison between an integrated conventional equipment and terrestrial laser scanning / Bogdan Apostol in Annals of forest research, vol 61 n° 2 (July - December 2018)
PermalinkDepth camera indoor mapping for 3D virtual radio play / Juho-Pekka Virtanen in Photogrammetric record, vol 33 n° 162 (June 2018)
PermalinkInference on forest attributes and ecological diversity of trees outside forest by a two-phase inventory / Marco Marchetti in Annals of Forest Science, vol 75 n° 2 (June 2018)
PermalinkLive fuel moisture content (LFMC) time series for multiple sites and species in the French Mediterranean area since 1996 / N. Martin-St Paul in Annals of Forest Science, vol 75 n° 2 (June 2018)
PermalinkMapping rubber trees based on phenological analysis of Landsat time series data-sets / Janatul Aziera binti Abd Razak in Geocarto international, vol 33 n° 6 (June 2018)
PermalinkModeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data / Manuel Arias-Rodil in Annals of Forest Science, vol 75 n° 2 (June 2018)
PermalinkSpatially sensitive statistical shape analysis for pedestrian recognition from LIDAR data / Michalis A. Savelonas in Computer Vision and image understanding, vol 171 (June 2018)
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