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Precise onboard time synchronization for LEO satellites / Florian Kunzi in Navigation : journal of the Institute of navigation, vol 69 n° 3 (Fall 2022)
[article]
Titre : Precise onboard time synchronization for LEO satellites Type de document : Article/Communication Auteurs : Florian Kunzi, Auteur ; Oliver Montenbruck, Auteur Année de publication : 2022 Article en page(s) : n° 531 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales
[Termes IGN] données GNSS
[Termes IGN] horloge
[Termes IGN] orbite basse
[Termes IGN] orbitographie
[Termes IGN] oscillateur
[Termes IGN] récepteur DORIS
[Termes IGN] récepteur GNSS
[Termes IGN] récepteur trifréquence
[Termes IGN] synchronisation
[Termes IGN] temps réelRésumé : (auteur) Onboard time synchronization is an important requirement for a wide range of low Earth orbit (LEO) missions such as altimetry or communication services, and extends to future position, navigation, and timing (PNT) services in LEO. For GNSS-based time synchronization, continuous knowledge about the satellite’s position is required and, eventually, the quality of the position solution defines the timing precision attainable through GNSS measurements. Previous research has shown that real-time GNSS orbit determination of LEO satellites can achieve decimeter-level accuracy. This paper characterizes the performance of GNSS-based real-time clock synchronization in LEO using the satellite Sentinel-6A as a real-world case study. The satellite’s ultra-stable oscillator (USO) and triple-frequency GPS/Galileo receiver provide measurements for a navigation filter representative of real-time onboard processing. Continuous evaluation of actual flight data over 14 days shows that a 3D orbit root-mean-square (RMS) error of 11 cm and a 0.9-ns clock standard deviation can be achieved. Numéro de notice : A2022-822 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.33012/navi.531 Date de publication en ligne : 12/04/2022 En ligne : https://doi.org/10.33012/navi.531 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101991
in Navigation : journal of the Institute of navigation > vol 69 n° 3 (Fall 2022) . - n° 531[article]Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning / J.F. Roberts in Computers & geosciences, vol 167 (October 2022)
[article]
Titre : Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning Type de document : Article/Communication Auteurs : J.F. Roberts, Auteur ; R. Mwangi, Auteur ; F. Mukabi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte thématique
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] image Sentinel-MSI
[Termes IGN] informatique en nuage
[Termes IGN] Kenya
[Termes IGN] langage de programmation
[Termes IGN] observation de la Terre
[Termes IGN] Python (langage de programmation)
[Termes IGN] surveillance forestièreRésumé : (auteur) Monitoring forest cover change from Earth observation data streams in near-real-time presents a challenge for automated change detection by way of a continuously updated big dataset. Even though deforestation is a significant global problem, forest cover changes in pairs of subsequent images happen relatively infrequently. Detecting a change can require the download and processing of tens, hundreds or even thousands of images. In geoscientific applications of Earth observation, machine learning algorithms are increasingly used. Once trained, a machine learning model can be applied to new images automatically. This paper introduces the open-access Python 3 package Pyeo - “Python for Earth Observation”. Pyeo provides a set of portable, extensible and modular Python functions for the automation of machine learning applications from Earth observation data streams, including automated search and download functionality, pre-processing and atmospheric correction, re-projection, creation of thematic base layers and machine learning classification or regression. Pyeo enables users to train their own machine learning models and then apply the models to newly downloaded imagery over their area of interest. This paper describes in detail how Pyeo works, its requirements, benefits, and a description of the libraries used. An application to the automated forest cover change detection in a region in Kenya is given. Pyeo can be used on cloud computing architectures such as Amazon Web Services, Microsoft Azure and Google Colab to provide scalable applications and processing solutions for the geosciences. Numéro de notice : A2022-706 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105192 Date de publication en ligne : 09/07/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105192 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101575
in Computers & geosciences > vol 167 (October 2022) . - n° 105192[article]Result of the MICROSCOPE weak equivalence principle test / Pierre Touboul in Classical and Quantum Gravity, vol 39 n° 20 (October 2022)
[article]
Titre : Result of the MICROSCOPE weak equivalence principle test Type de document : Article/Communication Auteurs : Pierre Touboul, Auteur ; Gilles Métris, Auteur ; Manuel Rodrigues, Auteur ; et al., Auteur ; Isabelle Panet , Auteur Année de publication : 2022 Article en page(s) : n° 2004009 Note générale : bibliographie
Pierre Touboul, Gilles Métris, Manuel Rodrigues, Joel Bergé, Alain Robert, Quentin Baghi, Yves André, Judicael Bedouet, Damien Boulanger, Stefanie Bremer, Patrice Carle, Ratana Chhun, Bruno Christophe, Valerio Cipolla, Thibault Damour, Pascale Danto, Louis Demange, Hansjoerg Dittus, Océane Dhuicque, Pierre Fayet, Bernard Foulon, Pierre-Yves Guidotti, Daniel Hagedorn, Emilie Hardy, Phuong-Anh Huynh, Patrick Kayser, Stephanie Lala, Claus Lämmerzah, Vincent Lebat, Françoise Liorzou, Meike List, Frank Löffler, Isabelle Panet, Martin Pernot-Borràs, Laurent Perraud, Sandrine Pires, Benjamin Pouilloux, Pascal Prieur, Alexandre Rebray, Serge Reynaud, Benny Rievers, Hanns Selig, Laura Serron, Timothy Sumner, Nicolas Tanguy, Patrizia Torresi and Pieter Visser.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] accéléromètre
[Termes IGN] MICROSCOPE (mission)
[Termes IGN] mission spatiale
[Termes IGN] principe d'équivalenceRésumé : (auteur) The space mission MICROSCOPE dedicated to the test of the equivalence principle (EP) operated from April 25, 2016 until the deactivation of the satellite on October 16, 2018. In this analysis we compare the free-fall accelerations (aA and aB) of two test masses in terms of the Eötvös parameter $\eta (\text{A,B})=2\frac{{a}_{\mathrm{A}}-{a}_{\mathrm{B}}}{{a}_{\mathrm{A}}+{a}_{\mathrm{B}}}$. No EP violation has been detected for two test masses, made from platinum and titanium alloys, in a sequence of 19 segments lasting from 13 to 198 h down to the limit of the statistical error which is smaller than 10−14 for η(Ti, Pt). Accumulating data from all segments leads to η(Ti, Pt) = [−1.5 ± 2.3 (stat) ± 1.5 (syst)] × 10−15 showing no EP violation at the level of 2.7 × 10−15 if we combine stochastic and systematic errors quadratically. This represents an improvement of almost two orders of magnitude with respect to the previous best such test performed by the Eöt-Wash group. The reliability of this limit has been verified by comparing the free falls of two test masses of the same composition (platinum) leading to a null Eötvös parameter with a statistical uncertainty of 1.1 × 10−15. Numéro de notice : A2022-690 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1088/1361-6382/ac84be En ligne : https://doi.org/10.1088/1361-6382/ac84be Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101804
in Classical and Quantum Gravity > vol 39 n° 20 (October 2022) . - n° 2004009[article]Riparian ecosystems mapping at fine scale: a density approach based on multi-temporal UAV photogrammetric point clouds / Elena Belcore in Remote sensing in ecology and conservation, vol 8 n° 5 (October 2022)
[article]
Titre : Riparian ecosystems mapping at fine scale: a density approach based on multi-temporal UAV photogrammetric point clouds Type de document : Article/Communication Auteurs : Elena Belcore, Auteur ; Melissa Latella, Auteur Année de publication : 2022 Article en page(s) : pp 644 - 655 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte de la végétation
[Termes IGN] densité de la végétation
[Termes IGN] détection d'objet
[Termes IGN] forêt ripicole
[Termes IGN] houppier
[Termes IGN] image captée par drone
[Termes IGN] Italie
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] orthophotoplan numérique
[Termes IGN] semis de points
[Termes IGN] structure-from-motionRésumé : (auteur) In recent years, numerous directives worldwide have addressed the conservation and restoration of riparian corridors, activities that rely on continuous vegetation mapping to understand its volumetric features and health status. Mapping riparian corridors requires not only fine-scale resolution but also the coverage of relatively large areas. The use of Unmanned Aerial Vehicles (UAV) allows for meeting both conditions, although the cost-effectiveness of their use is highly influenced by the type of sensor mounted on them. Few works have so far investigated the use of photogrammetric sensors for individual tree crown detection, despite being cheaper than the most common Light Detection and Ranging (LiDAR) ones. This work aims to improve the individual crown detection from UAV-photogrammetric datasets in a two fold way. Firstly, the effectiveness of a new approach that has already achieved interesting results in LiDAR applications was tested for photogrammetric point clouds. The test was carried out by comparing the accuracy achieved by the new approach, which is based on the point density features of the analysed dataset, with those related to the more common local maxima and textural methods. The results indicated the potentiality of the density-based method, which achieved accuracy values (0.76F-score) consistent with the traditional methods (0.49–0.80F-score range) but was less affected by under- and over-fitting. Secondly, the potential improvement of working on intra-annual multi-temporal datasets was assessed by applying the density-based approach to seven different scenarios, three of which were constituted by single-epoch datasets and the remaining given by the joining of the others. The F-score increased from 0.67 to 0.76 when passing from single- to multi-epoch datasets, aligning with the accuracy achieved by the new method when applied to LiDAR data. The results demonstrate the potential of multi-temporal acquisitions when performing individual crown detection from photogrammetric data. Numéro de notice : A2022-879 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.267 Date de publication en ligne : 22/03/2022 En ligne : https://doi.org/10.1002/rse2.267 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102193
in Remote sensing in ecology and conservation > vol 8 n° 5 (October 2022) . - pp 644 - 655[article]Single-image super-resolution for remote sensing images using a deep generative adversarial network with local and global attention mechanisms / Yadong Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 10 (October 2022)
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Titre : Single-image super-resolution for remote sensing images using a deep generative adversarial network with local and global attention mechanisms Type de document : Article/Communication Auteurs : Yadong Li, Auteur ; Sébastien Mavromatis, Auteur ; Feng Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 3000224 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] image isolée
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] pouvoir de résolution spectrale
[Termes IGN] reconstruction d'image
[Termes IGN] réseau antagoniste génératifRésumé : (auteur) Super-resolution (SR) technology is an important way to improve spatial resolution under the condition of sensor hardware limitations. With the development of deep learning (DL), some DL-based SR models have achieved state-of-the-art performance, especially the convolutional neural network (CNN). However, considering that remote sensing images usually contain a variety of ground scenes and objects with different scales, orientations, and spectral characteristics, previous works usually treat important and unnecessary features equally or only apply different weights in the local receptive field, which ignores long-range dependencies; it is still a challenging task to exploit features on different levels and reconstruct images with realistic details. To address these problems, an attention-based generative adversarial network (SRAGAN) is proposed in this article, which applies both local and global attention mechanisms. Specifically, we apply local attention in the SR model to focus on structural components of the earth’s surface that require more attention, and global attention is used to capture long-range interdependencies in the channel and spatial dimensions to further refine details. To optimize the adversarial learning process, we also use local and global attentions in the discriminator model to enhance the discriminative ability and apply the gradient penalty in the form of hinge loss and loss function that combines L1 pixel loss, L1 perceptual loss, and relativistic adversarial loss to promote rich details. The experiments show that SRAGAN can achieve performance improvements and reconstruct better details compared with current state-of-the-art SR methods. A series of ablation investigations and model analyses validate the efficiency and effectiveness of our method. Numéro de notice : A2022-767 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3093043 Date de publication en ligne : 12/07/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3093043 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101789
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 10 (October 2022) . - n° 3000224[article]The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)PermalinkComparing Landsat-8 and Sentinel-2 top of atmosphere and surface reflectance in high latitude regions: case study in Alaska / Jiang Chen in Geocarto international, vol 37 n° 20 ([20/09/2022])PermalinkForest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (September-15 2022)PermalinkThe FIRST model: Spatiotemporal fusion incorrporting spectral autocorrelation / Shuaijun Liu in Remote sensing of environment, vol 279 (September-15 2022)PermalinkAssessing road accidents in spatial context via statistical and non-statistical approaches to detect road accident hotspot using GIS / Yegane Khosravi in Geodetski vestnik, vol 66 n° 3 (September - November 2022)PermalinkAssessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans : An agent-based modeling approach / Kirana Widyastuti in Frontiers in Ecology and Evolution, vol 2022 ([01/09/2022])PermalinkBenchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest / Daniel Kükenbrink in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)PermalinkLe chantier de la Nouvelle carte de France / Pierre Clergeot in Géomètre, n° 2205 (septembre 2022)PermalinkDeep learning–based monitoring sustainable decision support system for energy building to smart cities with remote sensing techniques / Wang Yue in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 9 (September 2022)PermalinkDeflection of vertical effect on direct georeferencing in aerial mobile mapping systems: A case study in Sweden / Mohammad Bagherbandi in Photogrammetric record, vol 37 n° 179 (September 2022)PermalinkDesign and construction of a colourblind-friendly Surabaya city angkot route map prototype / Arzakhy Indhira Pramesti in Cartographica, vol 57 n° 3 (September 2022)PermalinkFlood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach / Quoc Bao Pham in Natural Hazards, vol 113 n° 2 (September 2022)PermalinkA general model for creating robust choropleth maps / Wangshu Mu in Computers, Environment and Urban Systems, vol 96 (September 2022)PermalinkHistorical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)PermalinkLarge-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt / André Bertoncini in Remote sensing of environment, vol 278 (September 2022)PermalinkLarge-scale diachronic surveys of the composition and dynamics of plant communities in Pyrenean snowbeds / Thomas Masclaux in Plant ecology, Vol 223 n° 9 (September 2022)PermalinkA map matching-based method for electric vehicle charging station placement at directional road segment level / Zhoulin Yu in Sustainable Cities and Society, vol 84 (September 2022)PermalinkMapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression / Haoyu Wang in Remote sensing of environment, vol 278 (September 2022)PermalinkMapping individual abandoned houses across cities by integrating VHR remote sensing and street view imagery / Shengyuan Zou in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)PermalinkMICROSCOPE Mission: Final Results of the Test of the Equivalence Principle / Pierre Touboul in Physical Review Letters, vol 129 n° 12 ([01/09/2022])Permalink