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Enhanced trajectory estimation of mobile laser scanners using aerial images / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)
[article]
Titre : Enhanced trajectory estimation of mobile laser scanners using aerial images Type de document : Article/Communication Auteurs : Zille Hussnain, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur Année de publication : 2021 Article en page(s) : pp 66 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement de points
[Termes IGN] atténuation du signal
[Termes IGN] balayage laser
[Termes IGN] canyon urbain
[Termes IGN] centrale inertielle
[Termes IGN] données lidar
[Termes IGN] erreur
[Termes IGN] image captée par drone
[Termes IGN] mesurage par GNSS
[Termes IGN] semis de points
[Termes IGN] trajectoire (véhicule non spatial)
[Termes IGN] trajet multipleRésumé : (auteur) Multipath effects and signal obstruction by buildings in urban canyons can lead to inaccurate GNSS measurements and therefore errors in the estimated trajectory of Mobile Laser Scanning (MLS) systems; consequently, derived point clouds are distorted and lose spatial consistency. We obtain decimetre-level trajectory accuracy making use of corresponding points between the MLS data and aerial images with accurate exterior orientations instead of using ground control points. The MLS trajectory is estimated based on observation equations resulting from these corresponding points, the original IMU observations, and soft constraints on the pitch and yaw rotations of the vehicle. We analyse the quality of the trajectory enhancement under several conditions where the experiments were designed to test the influence of the number and quality of corresponding points and to test different settings for a B-spline representation of the vehicle trajectory. The method was tested on two independently acquired MLS datasets in Rotterdam by enhancing the trajectories and evaluating them using checkpoints. The RMSE values of the original GNSS/IMU based Kalman filter results at the checkpoints were 0.26 m, 0.30 m, and 0.47 m for the X-, Y- and Z-coordinates in the first dataset and 1.10 m, 1.51 m, and 1.81 m in the second dataset. The latter dataset was recorded with a lower quality IMU in an area with taller buildings. After trajectory adjustment these RMSE values were reduced to 0.09 m, 0.11 m, and 0.16 m for the first dataset and 0.12 m, 0.14 m, and 0.18 m for the second dataset. The results confirmed that, if sufficient tie points between the point cloud and aerial imagery are available, the method supports geo-referencing of MLS point clouds in urban canyons with a near-decimetre accuracy. Numéro de notice : A2021-102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.005 Date de publication en ligne : 17/01/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.005 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96877
in ISPRS Journal of photogrammetry and remote sensing > vol 173 (March 2021) . - pp 66 - 78[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021031 SL Revue Centre de documentation Revues en salle Disponible 081-2021033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Learning from GPS trajectories of floating car for CNN-based urban road extraction with high-resolution satellite imagery / Ju Zhang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)
[article]
Titre : Learning from GPS trajectories of floating car for CNN-based urban road extraction with high-resolution satellite imagery Type de document : Article/Communication Auteurs : Ju Zhang, Auteur ; Qingwu Hu, Auteur ; Jiayuan Li, Auteur ; Mingyao Ai, Auteur Année de publication : 2021 Article en page(s) : pp 1836 - 1847 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] extraction du réseau routier
[Termes IGN] image à haute résolution
[Termes IGN] rastérisation
[Termes IGN] segmentation d'image
[Termes IGN] trace GPS
[Termes IGN] trace numérique
[Termes IGN] trajectoire (véhicule non spatial)
[Termes IGN] Wuhan (Chine)
[Termes IGN] zone urbaineRésumé : (Auteur) Deep learning has achieved great success in recent years, among which the convolutional neural network (CNN) method is outstanding in image segmentation and image recognition. It is also widely used in satellite imagery road extraction and, generally, can obtain accurate and extraction results. However, at present, the extraction of roads based on CNN still requires a lot of manual preparation work, and a large number of samples can be marked to achieve extraction, which has to take long drawing cycle and high production cost. In this article, a new CNN sample set production method is proposed, which uses the GPS trajectories of floating car as training set (GPSTasST), for the multilevel urban roads extraction from high-resolution remote sensing imagery. This method rasterizes the GPS trajectories of floating car into a raster map and uses the processed raster map to label the satellite image to obtain a road extraction sample set. CNN can extract roads from remote sensing imagery by learning the training set. The results show that the method achieves a harmonic mean of precision and recall higher than road extraction method from single data source while eliminating the manual labeling work, which shows the effectiveness of this work. Numéro de notice : A2021-211 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3003425 Date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3003425 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97196
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 1836 - 1847[article]Unsupervised deep representation learning for real-time tracking / Ning Wang in International journal of computer vision, vol 129 n° 2 (February 2021)
[article]
Titre : Unsupervised deep representation learning for real-time tracking Type de document : Article/Communication Auteurs : Ning Wang, Auteur ; Wengang Zhou, Auteur ; Yibing Song, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 400 - 418 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] apprentissage profond
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection de cible
[Termes IGN] filtre
[Termes IGN] objet mobile
[Termes IGN] oculométrie
[Termes IGN] reconnaissance d'objets
[Termes IGN] réseau neuronal siamois
[Termes IGN] temps réel
[Termes IGN] traçage
[Termes IGN] trajectoire (véhicule non spatial)
[Termes IGN] vision par ordinateurRésumé : (auteur) The advancement of visual tracking has continuously been brought by deep learning models. Typically, supervised learning is employed to train these models with expensive labeled data. In order to reduce the workload of manual annotation and learn to track arbitrary objects, we propose an unsupervised learning method for visual tracking. The motivation of our unsupervised learning is that a robust tracker should be effective in bidirectional tracking. Specifically, the tracker is able to forward localize a target object in successive frames and backtrace to its initial position in the first frame. Based on such a motivation, in the training process, we measure the consistency between forward and backward trajectories to learn a robust tracker from scratch merely using unlabeled videos. We build our framework on a Siamese correlation filter network, and propose a multi-frame validation scheme and a cost-sensitive loss to facilitate unsupervised learning. Without bells and whistles, the proposed unsupervised tracker achieves the baseline accuracy of classic fully supervised trackers while achieving a real-time speed. Furthermore, our unsupervised framework exhibits a potential in leveraging more unlabeled or weakly labeled data to further improve the tracking accuracy. Numéro de notice : A2021-353 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s11263-020-01357-4 Date de publication en ligne : 21/09/2020 En ligne : https://doi.org/10.1007/s11263-020-01357-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97604
in International journal of computer vision > vol 129 n° 2 (February 2021) . - pp 400 - 418[article]Comparing the performance of turbulent kinetic energy and K-profile parameterization vertical parameterization schemes over the tropical indian ocean / Lokesh Kumar Pandey in Marine geodesy, vol 44 n° 1 (January 2021)
[article]
Titre : Comparing the performance of turbulent kinetic energy and K-profile parameterization vertical parameterization schemes over the tropical indian ocean Type de document : Article/Communication Auteurs : Lokesh Kumar Pandey, Auteur ; Suneet Dwivedi, Auteur Année de publication : 2021 Article en page(s) : pp 42 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Océanographie
[Termes IGN] Bengale, golfe du
[Termes IGN] énergie cinétique
[Termes IGN] Indien (océan)
[Termes IGN] modélisation spatiale
[Termes IGN] mousson
[Termes IGN] salinité
[Termes IGN] température de surface de la merRésumé : (Auteur) The performance of vertical parameterization schemes, namely, turbulent kinetic energy (TKE) and K-profile parameterization (KPP), is evaluated over the domain [30E-120E; 20S-30N] in the Indian Ocean using the Nucleus for European Modeling of the Ocean (NEMO) regional model. The surface and sub-surface hydrography and mixed layer depth (MLD) of the simulations using TKE and KPP schemes have been compared. The KPP scheme produces higher bias (∼0.5 °C) of sea surface temperature (SST) in monsoon and post-monsoon seasons, which reduces on using the TKE scheme. The maximum surface salinity difference (0.45 psu) between TKE and KPP simulations is obtained over the head Bay of Bengal (BoB) in the post-monsoon months. The KPP scheme also overestimates MLD of the region. Barring highly convective regions as well as regions marked with very low and rapidly changing salinity, the TKE scheme performs better than KPP scheme in simulating the hydrography and MLD of the region. The differences between TKE and KPP simulations in the vertical stability and mixing are studied using buoyancy frequency, vertical shear of horizontal currents and energy required for mixing as quantifiers. The mixed layer heat budget analysis explains seasonal variability of SST and differences in vertical mixing parameterizations. Numéro de notice : A2021-059 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2020.1835758 Date de publication en ligne : 29/10/2020 En ligne : https://doi.org/10.1080/01490419.2020.1835758 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96849
in Marine geodesy > vol 44 n° 1 (January 2021) . - pp 42 - 69[article]Dynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing / Md Jamal Uddin Kahn (2021)
Titre : Dynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing Type de document : Thèse/HDR Auteurs : Md Jamal Uddin Kahn, Auteur ; Fabien Durand, Directeur de thèse ; Laurent Testut, Directeur de thèse Editeur : Toulouse : Université de Toulouse 3 Paul Sabatier Année de publication : 2021 Importance : 167 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse présentée en vue de l’obtention du Doctorat en Océan, Atmosphère, Climat, de l’Université de ToulouseLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bengale, golfe du
[Termes IGN] cyclone
[Termes IGN] delta
[Termes IGN] estran
[Termes IGN] gestion des risques
[Termes IGN] hydrodynamique
[Termes IGN] image Sentinel-MSI
[Termes IGN] marée océanique
[Termes IGN] modèle numérique de surface
[Termes IGN] niveau moyen des mers
[Termes IGN] risque naturel
[Termes IGN] submersion marineIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) The Bengal delta is the largest in the world. It is formed by the confluence of three transboundary rivers - Ganges, Brahmaputra, and Meghna. Flooding induced by large seasonal continental discharge, strong tide, and frequent deadly storm surges, regularly strikes this densely populated (density > 1000 person/km2), low-lying coastal region ( Note de contenu : 1. Introduction and Motivation
1.1 Introduction
1.2 The river deltas
1.3 Inundation in the Bengal delta
1.4 Bengal delta continuum and knowledge gaps
1.5 Scientific questions and study approach
1.6 Organization of the thesis
2. Hydrodynamic Modeling: Data and Methods
2.1 Introduction
2.2 Bathymetry assembly
2.3 Observations
2.4 Modelling framework
2.5 Model forcings and boundary condition
2.6 Assessment of tide
3. Intertidal Topography: Synergy Between Remote Sensing and Tidal Mod?elling
3.1 Introduction
3.2 Shoreline detection with Sentinel-2 imagery
3.3 Vertical referencing with tidal model
3.4 Results
3.5 Discussion
3.6 Conclusion
4. Coastal Tide: From the Present to the Future
4.1 Introduction
4.2 Observed trend in tidal range: The example of Hiron Point
4.3 Tidal model in the Bay of Bengal
4.4 Projected changes in tidal range in the Bengal delta
4.5 Tidal range evolution along the estuaries
4.6 Discussion
4.7 Conclusions
5. Storm Surge Modeling: A Case Study of Recent Super Cyclone Amphan
5.1 Introduction
5.2 Storm surge and inundation processes in the Bay of Bengal
5.3 Atmospheric evolution of cyclone Amphan
5.4 Storm surge model and performance
5.5 Near real-time storm surge forecasting
5.6 Discussion
5.7 Conclusions
5.8 Appendix
6. Storm Surge Hazard: A Probabilistic-Deterministic Approach
6.1 Introduction
6.2 Storm surge model
6.3 Probabilistic-deterministic cyclone ensemble
6.4 Storm surge hazard
6.5 Discussion
6.6 Conclusions and perspective
7. Conclusions and Perspectives for Future Work
7.1 Conclusion
7.2 Overview
7.3 Summary of conclusions and impacts
7.4 Future Research Perspectives
7.5 Transferrable lessons and concluding remarksNuméro de notice : 26768 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Océan, Atmosphère, Climat : Toulouse : 2021 Organisme de stage : Laboratoire d'Etudes en Géophysique et Océanographie Spatiales LEGOS nature-HAL : Thèse DOI : sans Date de publication en ligne : 06/01/2022 En ligne : https://tel.hal.science/tel-03514722/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99866 PermalinkModélisation et simulation de comportements piétons réalistes en espace partagé avec un véhicule autonome / manon Prédhumeau (2021)PermalinkUsing remote sensing and modeling to monitor and understand harmful algal blooms. Application to Karaoun Reservoir (Lebanon) / Najwa Sharaf (2021)PermalinkSemantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)PermalinkNetwork-constrained bivariate clustering method for detecting urban black holes and volcanoes / Qiliang Liu in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)PermalinkImproving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations / Guanxu Chen in Journal of geodesy, vol 94 n° 6 (June 2020)PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkImproved kinematic precise point positioning performance with the use of map constraints / Emerson Pereira Cavalheri in Journal of applied geodesy, vol 14 n° 2 (April 2020)PermalinkLe sol s'affaisse, l'eau monte [Delta du Gange-Brahmapoutre-Meghna] / Marielle Mayo in Géomètre, n° 2179 (avril 2020)PermalinkEstimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)Permalink