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GENESIS: co-location of geodetic techniques in space / Pacôme Delva in Earth, Planets and Space, vol 75 n° 1 (2023)
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Titre : GENESIS: co-location of geodetic techniques in space Type de document : Article/Communication Auteurs : Pacôme Delva, Auteur ; Zuheir Altamimi , Auteur ; et al., Auteur ; Laurent Métivier
, Auteur
Année de publication : 2023 Article en page(s) : n° 5 (2023) Note générale : bibliographie
by Pacôme Delva, Zuheir Altamimi, Alejandro Blazquez, Mathis Blossfeld, Johannes Böhm, Pascal Bonnefond, Jean-Paul Boy, Sean Bruinsma, Grzegorz Bury, Miltiadis Chatzinikos, Alexandre Couhert, Clément Courde, Rolf Dach, Véronique Dehant, Simone Dell’Agnello, Gunnar Elgered, Werner Enderle, Pierre Exertier, Susanne Glaser, Rüdiger Haas, Wen Huang, Urs Hugentobler, Adrian Jäggi, Ozgur Karatekin, Frank G. Lemoine, Christophe Le Poncin-Lafitte, Susanne Lunz, Benjamin Männel, Flavien Mercier, Laurent Métivier, Benoît Meyssignac, Jürgen Müller, Axel Nothnagel, Felix Perosanz, Roelof Rietbroek, Markus Rothacher, Harald Schuh, Hakan Sert, Krzysztof Sosnica, Paride Testani, Javier Ventura-Traveset, Gilles Wautelet & Radoslaw ZajdelLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] co-positionnement
[Termes IGN] géodésie spatiale
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] précision du positionnement
[Termes IGN] satellite de positionnementRésumé : (auteur) Improving and homogenizing time and space reference systems on Earth and, more specifically, realizing the Terrestrial Reference Frame (TRF) with an accuracy of 1 mm and a long-term stability of 0.1 mm/year are relevant for many scientific and societal endeavors. The knowledge of the TRF is fundamental for Earth and navigation sciences. For instance, quantifying sea level change strongly depends on an accurate determination of the geocenter motion but also of the positions of continental and island reference stations, such as those located at tide gauges, as well as the ground stations of tracking networks. Also, numerous applications in geophysics require absolute millimeter precision from the reference frame, as for example monitoring tectonic motion or crustal deformation, contributing to a better understanding of natural hazards. The TRF accuracy to be achieved represents the consensus of various authorities, including the International Association of Geodesy (IAG), which has enunciated geodesy requirements for Earth sciences. Moreover, the United Nations Resolution 69/266 states that the full societal benefits in developing satellite missions for positioning and Remote Sensing of the Earth are realized only if they are referenced to a common global geodetic reference frame at the national, regional and global levels. Today we are still far from these ambitious accuracy and stability goals for the realization of the TRF. However, a combination and co-location of all four space geodetic techniques on one satellite platform can significantly contribute to achieving these goals. This is the purpose of the GENESIS mission, a component of the FutureNAV program of the European Space Agency. The GENESIS platform will be a dynamic space geodetic observatory carrying all the geodetic instruments referenced to one another through carefully calibrated space ties. The co-location of the techniques in space will solve the inconsistencies and biases between the different geodetic techniques in order to reach the TRF accuracy and stability goals endorsed by the various international authorities and the scientific community. The purpose of this paper is to review the state-of-the-art and explain the benefits of the GENESIS mission in Earth sciences, navigation sciences and metrology. This paper has been written and supported by a large community of scientists from many countries and working in several different fields of science, ranging from geophysics and geodesy to time and frequency metrology, navigation and positioning. As it is explained throughout this paper, there is a very high scientific consensus that the GENESIS mission would deliver exemplary science and societal benefits across a multidisciplinary range of Navigation and Earth sciences applications, constituting a global infrastructure that is internationally agreed to be strongly desirable. Numéro de notice : A2023-078 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s40623-022-01752-w Date de publication en ligne : 11/01/2023 En ligne : https://doi.org/10.1186/s40623-022-01752-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102519
in Earth, Planets and Space > vol 75 n° 1 (2023) . - n° 5 (2023)[article]Deep learning detects invasive plant species across complex landscapes using Worldview-2 and Planetscope satellite imagery / Thomas A. Lake in Remote sensing in ecology and conservation, vol 8 n° 6 (December 2022)
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Titre : Deep learning detects invasive plant species across complex landscapes using Worldview-2 and Planetscope satellite imagery Type de document : Article/Communication Auteurs : Thomas A. Lake, Auteur ; Ryan D. Briscoe Runquist, Auteur ; David A. Moeller, Auteur Année de publication : 2022 Article en page(s) : pp 875 - 889 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par réseau neuronal récurrent
[Termes IGN] espèce exotique envahissante
[Termes IGN] image Worldview
[Termes IGN] PlanetScope
[Termes IGN] série temporelleRésumé : (auteur) Effective management of invasive species requires rapid detection and dynamic monitoring. Remote sensing offers an efficient alternative to field surveys for invasive plants; however, distinguishing individual plant species can be challenging especially over geographic scales. Satellite imagery is the most practical source of data for developing predictive models over landscapes, but spatial resolution and spectral information can be limiting. We used two types of satellite imagery to detect the invasive plant, leafy spurge (Euphorbia virgata), across a heterogeneous landscape in Minnesota, USA. We developed convolutional neural networks (CNNs) with imagery from Worldview-2 and Planetscope satellites. Worldview-2 imagery has high spatial and spectral resolution, but images are not routinely taken in space or time. By contrast, Planetscope imagery has lower spatial and spectral resolution, but images are taken daily across Earth. The former had 96.1% accuracy in detecting leafy spurge, whereas the latter had 89.9% accuracy. Second, we modified the CNN for Planetscope with a long short-term memory (LSTM) layer that leverages information on phenology from a time series of images. The detection accuracy of the Planetscope LSTM model was 96.3%, on par with the high resolution, Worldview-2 model. Across models, most false-positive errors occurred near true populations, indicating that these errors are not consequential for management. We identified that early and mid-season phenological periods in the Planetscope time series were key to predicting leafy spurge. Additionally, green, red-edge and near-infrared spectral bands were important for differentiating leafy spurge from other vegetation. These findings suggest that deep learning models can accurately identify individual species over complex landscapes even with satellite imagery of modest spatial and spectral resolution if a temporal series of images is incorporated. Our results will help inform future management efforts using remote sensing to identify invasive plants, especially across large-scale, remote and data-sparse areas. Numéro de notice : A2023-033 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.288 En ligne : https://doi.org/10.1002/rse2.288 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102295
in Remote sensing in ecology and conservation > vol 8 n° 6 (December 2022) . - pp 875 - 889[article]Crowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images / Ekrem Saralioglu in Geocarto international, vol 37 n° 18 ([01/09/2022])
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Titre : Crowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images Type de document : Article/Communication Auteurs : Ekrem Saralioglu, Auteur ; Oguz Gungor, Auteur Année de publication : 2022 Article en page(s) : pp 5433 - 5452 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] acquisition d'images
[Termes IGN] apprentissage profond
[Termes IGN] approche participative
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] couleur (variable spectrale)
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] étiquette
[Termes IGN] image multibande
[Termes IGN] OpenStreetMap
[Termes IGN] pixel
[Termes IGN] plateforme collaborative
[Termes IGN] texture d'image
[Termes IGN] WorldviewRésumé : (auteur) In order to solve insufficient training data problem in remote sensing, a web platform was created so that registered users can generate labeled data for various classes in a dynamic structure. Users were asked to select representative pixel groups for the forest, hazelnut, shadow, soil, tea, and building classes with the polygon tool, and then assign a class label corresponding to each created polygon thanks to the help document displaying descriptive information regarding the locations, colors, textures and distributions of the classes in the image. Crowdsourcing was again used to test the accuracy of the tagged data produced by crowdsourcing. The created data set was overlaid with the original WV-2 image, and the correctness of the labels of the polygons was once visually verified. Finally, the WV-2 image, consisting of 40 patches, was classified with CNN and an average of over 95% accuracy was achieved. Numéro de notice : A2022-702 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1917006 Date de publication en ligne : 26/05/2021 En ligne : https://doi.org/10.1080/10106049.2021.1917006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101561
in Geocarto international > vol 37 n° 18 [01/09/2022] . - pp 5433 - 5452[article]Landsat, le programme fête ses cinquante ans / Laurent Polidori in Géomètre, n° 2205 (septembre 2022)
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Titre : Landsat, le programme fête ses cinquante ans Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2022 Article en page(s) : pp 19-19 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Technologies spatiales
[Termes IGN] Landsat
[Termes IGN] programme spatial
[Termes IGN] satellite d'observation de la Terre
[Termes IGN] télédétection spatialeRésumé : (Auteur) Le programme de la Nasa propose un demi-siècle d’images de télédétection, les premières pouvant être considérées comme un « état zéro» environnemental de la planète. Numéro de notice : A2022-670 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/09/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101492
in Géomètre > n° 2205 (septembre 2022) . - pp 19-19[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 063-2022091 SL Revue Centre de documentation Revues en salle Disponible Validation of a corner reflector installation at Côte d’Azur multi-technique geodetic observatory / Xavier Collilieux in Advances in space research, vol 70 n° 2 (15 July 2022)
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Titre : Validation of a corner reflector installation at Côte d’Azur multi-technique geodetic observatory Type de document : Article/Communication Auteurs : Xavier Collilieux , Auteur ; Clément Courde, Auteur ; Bénédicte Fruneau
, Auteur ; Mourad Aimar, Auteur ; Guillaume Schmidt, Auteur ; Isabelle Delprat, Auteur ; Marie-Amélie Defresne, Auteur ; Damien Pesce, Auteur ; Fabien Bergerault, Auteur ; Guy Wöppelmann
, Auteur
Année de publication : 2022 Projets : Université de Paris / Clerici, Christine Article en page(s) : pp 360 - 370 Note générale : bibliographie
This study contributes to the IdEx Université de Paris ANR-18-IDEX-0001. It was supported by the Programme National GRAM INSAROME of CNRS/INSU with INP and IN2P3 co-funded by CNES but also by BQR-OCA.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] coin réflecteur
[Termes IGN] constellation Sentinel
[Termes IGN] Global Geodetic Observing System
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] observatoire astronomiqueRésumé : (auteur) We present the procedure we followed to design an artificial corner reflector (CR) at the Calern site of Côte d’Azur Observatory (France). Although still few in number, such reflectors are an integral part of the Global Geodetic Observing System (GGOS) infrastructure. They can be used as a stable radar target in SAR images to connect local InSAR deformation maps to the global Terrestrial Reference Frame and for SAR absolute determination. During a test phase, the orientation of the CR was changed in order to be aligned toward all possible orbits of Sentinel-1A/1B satellites. On the different SAR images, the CR exhibits a high backscattering signal, and provides a Signal-to-Clutter Ratio larger than 26 dB. Since December 2018, the CR is specifically oriented toward the relative orbit 88. It is clearly detected as a PS in our InSAR analyses and as expected, the standard deviation of displacement measured on the CR is lower than on surrounding PS. A first local survey was performed to locate precisely this CR with respect to the existing geodetic instruments and annual campaigns have been carried out since then to insure its stability over time. Numéro de notice : A2022-337 Affiliation des auteurs : ENSG+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2022.04.050 Date de publication en ligne : 29/04/2022 En ligne : https://doi.org/10.1016/j.asr.2022.04.050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100694
in Advances in space research > vol 70 n° 2 (15 July 2022) . - pp 360 - 370[article]PermalinkPermalinkPermalinkEfficient variance component estimation for large-scale least-squares problems in satellite geodesy / Yufeng Nie in Journal of geodesy, vol 96 n° 2 (February 2022)
PermalinkOn-orbit BDS signals and transmit antenna gain analysis for a geostationary satellite / Meng Wang in Advances in space research, vol 69 n° 7 (April 2022)
PermalinkPreparation of the VENµS satellite data over Israel for the input into the GRASP data treatment algorithm / Maeve Blarel (2022)
PermalinkPermalinkIonospheric corrections tailored to the Galileo High Accuracy Service / Adria Rovira-Garcia in Journal of geodesy, vol 95 n° 12 (December 2021)
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