2-Publications IGN 2022
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Titre : Towards a transportable Yb lattice clock at SYRTE Type de document : Article/Communication Auteurs : Wilfreddy Moreno, Auteur ; Fatima Rahmouni, Auteur ; Benjamin Pointard, Auteur ; Paul-Eric Pottie, Auteur ; Pacôme Delva, Auteur ; Jérôme Lodewyck, Auteur ; Rodolphe Letargat, Auteur ; J. Romero González, Auteur ; M.-F. Lalancette, Auteur ; Guillaume Lion , Auteur ; Isabelle Panet , Auteur ; Olivier Jamet , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2022 Projets : ROYMAGE / Letargat, Rodolphe Conférence : EFTF-IFCS 2022, Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium 24/04/2022 28/04/2022 Paris France Proceedings IEEE Note générale : bibliographie
This work has received support from Agence Nationale de la Recherche (ANR) with project ROYMAGE (ANR-20-CE47-0006), DIM SIRTEQ and Labex First-TF with project PATHYNAGE, Scientific Council of Observatoire de Paris with project LARYNGITE, and the European Metrology Program for Innovation and Research (EMPIR), with project 18SIB05 ROCIT.
présenté aussi sous "Towards a high flux transportable Ytterbium Optical lattice Clock" aux Houches School of Physics, Cold Atom Predoc School Quantum mixtures, 26 sept-7 oct 2022Langues : Français (fre) Descripteur : [Vedettes matières IGN] Métrologie
[Termes IGN] chronométrie
[Termes IGN] fréquence
[Termes IGN] horloge optique
[Termes IGN] horlogerieRésumé : (auteur) We describe the design of a transportable optical lattice clock based on neutral ytterbium at SYRTE, Observatoire de Paris. This instrument will be connected to the network of ultrastable fiber links REFIMEVE+ with the objective of contributing both to Earth sciences and to frequency metrology. Note de contenu : 2022 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium (EFTF/IFCS) Numéro de notice : C2022-034 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Autre URL associée : vers HAL Thématique : POSITIONNEMENT Nature : Communication nature-HAL : Poster-avec-CL DOI : 10.1109/EFTF/IFCS54560.2022.9850674 Date de publication en ligne : 15/08/2022 En ligne : https://doi.org/10.1109/EFTF/IFCS54560.2022.9850674 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101381
Titre : Products and services of the Urban THEIA Scientific Expertise Centre Type de document : Article/Communication Auteurs : Anne Puissant, Auteur ; Thibault Catry, Auteur ; Rémi Cresson, Auteur ; Nadine Dessay, Auteur ; Laurent Demagistri, Auteur ; Sébastien Gadal, Auteur ; Arnaud Le Bris , Auteur ; Kenji Ose, Auteur ; Benjamin Pillot, Auteur Editeur : Strasbourg : Université de Strasbourg Année de publication : 2022 Conférence : LPS 2022, ESA Living Planet Symposium 22/05/2022 27/05/2022 Bonn Allemagne programme sans actes Note générale : projet AIMCEE (Apport de l’Imagerie satellitaire Multi-Capteurs pour répondre aux Enjeux Environnementaux et sociétaux des socio-systèmes urbains) Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] données spatiotemporelles
[Termes IGN] image satelliteRésumé : (auteur) The THEIA data and services centre (www.theia-land.fr) is a consortium of 12 French public institutions involved in Earth observation and environmental sciences (CEA, CEREMA, CIRAD, CNES, IGN, INRA, CNRS, IRD, Irstea, Météo France, AgroParisTech, and ONERA). THEIA was initiated in 2012 with the objective of increasing the use of space data by the scientific community and the public actors. The first years allowed structuring the national science and user communities, pooling resources to facilitate access to data and processing capacities, federating various previously unrelated initiatives, and disseminating the French achievements nationally and internationally.
The THEIA Land Data and Services Centre (www.theia-land.fr) is a consortium of 12 French public institutions involved in Earth observation and environmental sciences (CEA, CEREMA, CIRAD, CNES, IGN, INRAE, CNRS, IRD, Irstea, Météo France, AgroParisTech, and ONERA). THEIA has been initiated with the objective of increasing the use of space data by the scientific community and the public actors. The Scientific Expertise Centers (SEC) cluster research groups on various thematic domains. The "Urban” SEC gathers experts in multi-sensor urban remote sensing. Researchers of this group have structured their works around the development of algorithms useful for urban remote sensing using optical and SAR sensors to propose “urban products” at three different spatial scales: (1) the urban footprint, (2) the urban fabrics and (3) the urban objects. The objective of this poster is to present recent (>2019) advances of the URBAN SEC at these three scales. For the first two, the proposed methods are adapted to the geographic context of urban cities (West Cities, South Cities first and North Cities). For each spatial scale, the objective is to propose validated scientific products already available or in the near-term through the THEIA Land Service and Data Infrastructure.
At the macro-scale (urban footprint), an unsupervised automated approach is currently under development at Espace-DEV - Montpellier, and funded by a CNES project (TOSCA DELICIOSA). This method is derived from the FOTO algorithm originally developed to differentiate vegetation textures in HR and VHR satellite images (Couteron et al. 2006, Lang et al., 2019). It has been optimized and packaged into the FOTOTEX Python Open-Source library. The method is very well suited for areas with no or few urban settlement data or with quickly growing informal settlements. No training dataset is required, and the urban footprint can be identified from only one satellite image as long as it is not covered by clouds. For Western Cities where training datasets are available, the Urba-Opt processing chain based on an automatic and object-oriented approach has been deployed on HPC infrastructure and produce annually (since 2018) an urban settlement product which is available through the A2S dissemination infrastructure and on the Urban SEC of Theia land data and service Infrastructure. An ongoing research between LIVE and Espace Dev Labs focused on the interest to use the FOTOTEX result as training data in the Urba-Opt processing chain to propose an updated product of urban settlement for South cities.
At the scales of urban fabrics, products are under research activities The LIVE lab. In the context of an ongoing PhD thesis (ANR TIMES) and Tosca project (CNES 2019-2022) Sentinel-2 single-date images are used to assess two semantic segmentation networks (U-Net) that we combined using feature fusion between a from scratch network and a pre-trained network on ImageNet. Three spectral or textural indices have been added to the both networks in order to improve the classification results. The results showed a performance gain for the fusion methods. The research activities are ongoing in order to test the S1 imagery and temporal series for training in a deep architecture.
The IGN-LaSTIG - Univ. Paris Est has focused on the use of Sentinel-2 and VHR mono-temporal SPOT products to retrieve land cover information related to urban density. First, images undergo a U-net based semantic segmentation at urban object level to retrieve ‘topographic’ classes (buildings, roads, vegetation, …). Generalized information about urban fabrics is then derived out of these land cover maps thanks to another CNN architecture. Both a building density measure and a simplified Urban Atlas like land cover map are calculated. The UMR ESPACE has focused on the machine learning modeling of the evolution of urban territories of Arctic (Yakutsk) and North-Eastern Europe (Baltic States and Kaliningrad) cities since the post-Soviet period at two scales: those of the built-up area with high spatial resolution SPOT 6/7 images, and of the urban structures based on the use of Landsat 5 TM, Landsat 8 OLI, and Sentinel 2 MSI images. Environmental (urban vegetation), economic (agricultural transformation), and morphometric indexes have been developed to characterize the processes of urban restructuring (densification, renovation) and expansion of post-Soviet cities. A comparative analysis of the machine learning algorithms used was done on the South-East Baltic cities to evaluate their performance.
At the scale of urban object (3), a map of building with their functions is proposed by the TETIS laboratory. The study targets the retrieval of buildings footprint using deep convolutional neural networks for semantic segmentation, from Spot-6/7 images (1,5m spacing), on the entire France mainland. A single model has been trained and validated from 1.2k Spot-6/7 scenes and 20M images patches. The LIVE Lab has focused on the detection of urban changes from tri-stereoscopic Pléiades imagery through 2017 to 2020. A processing chain based on a Random Forest classifiers (ImCLASS) has been tested and the impact of the height attribute to detect changes has been evaluated to characterize changes into three thematic classes of changes.Numéro de notice : C2022-016 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Poster nature-HAL : Poster-avec-CL DOI : sans En ligne : https://express.converia.de/frontend/index.php?page_id=22745&additions_conferenc [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100842 Documents numériques
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Titre : ATONTE: towards a new methodology for seed ontology development from texts and experts Type de document : Article/Communication Auteurs : Helen Mair Rawsthorne , Auteur ; Nathalie Abadie , Auteur ; Eric Kergosien, Auteur ; Cécile Duchêne , Auteur ; Eric Saux, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2022 Projets : 1-Pas de projet / Letargat, Rodolphe Conférence : EKAW 2022, 23rd international conference on knowledge engineering and knowledge management 26/09/2022 29/09/2022 Bozen-Bolzano Italie Proceedings Springer Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] connaissance thématique
[Termes IGN] corpus
[Termes IGN] ontologie
[Termes IGN] réseau sémantiqueRésumé : (auteur) ATONTE (ATlantis methodology for ONtology development from Texts and Experts) is a methodology for the manual development of low-level seed ontologies. The modelling process is based on a combination of knowledge from non-fiction text corpora such as manuals, information guides or sets of instructions, and the knowledge of domain experts. This article presents the five key steps of the ATONTE process. Seed ontologies created with ATONTE can be used to develop and populate knowledge graphs for use in specific applications within given technical domains. Numéro de notice : C2022-010 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : texte de soumission Thématique : GEOMATIQUE Nature : Poster nature-HAL : Poster-avec-CL DOI : sans En ligne : https://hal.science/hal-03794323v1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102120 A square-grid sampling support to reconcile systematicity and adaptivity in the periodic spatial survey of natural resources / Olivier Bouriaud (2022)
Titre : A square-grid sampling support to reconcile systematicity and adaptivity in the periodic spatial survey of natural resources Type de document : Article/Communication Auteurs : Olivier Bouriaud , Auteur ; François Morneau , Auteur ; Jean-Daniel Bontemps , Auteur Editeur : Research Square Année de publication : 2022 Projets : ARBRE / AgroParisTech (2007 -) Présentation : 24 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] échantillonnage
[Termes IGN] grille d'échantillonnage
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] placette d'échantillonnage
[Termes IGN] population
[Termes IGN] surveillance forestière
[Termes IGN] variation temporelle
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Spatially balanced sampling is the most efficient design for surveying continuous or spatial populations across space. The spatial sampling of large-scale surveys is mostly based on grids, whose properties drive, and potentially limit, the possibilities of building flexible samples. Conciliating spatial balance and flexibility remains difficult. In particular, periodicity causes high constraints to the sampling particularly when an increase in the frequency of the information delivery is sought. Sampling stratification of adaptive sampling intensity also conflicts the grid-based approach. We show that square grids have geometric homothetic properties that enable to answer these needs by supporting nested hierarchical subgrid sets. These properties can be exploited to cope with both spatial flexibility in the sampling effort and spatio-temporal coordination of samples. Whereas some surveys seemingly do exploit these properties practically across the world, no formal development has been made available in the survey sampling literature across fields of applications. Here we therefore define and demonstrate these properties, and show how they can be used to produce nested hierarchical grids compatible with multiple periodicity values of interest to natural monitoring, and with adapting sampling intensity across space and time. We also provide an original extension of this framework, intended to tune the sampling effort gradually while preserving spatial systematicity. We use the French National Forest Inventory survey to illustrate these properties and their use in a large-scale repeated inventory. We show the flexibility and diversity of sampling schemes that can be initiated with square grids and the limits of their use. Numéro de notice : P2022-004 Affiliation des auteurs : LIF (2020- ) Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : Préprint DOI : 10.21203/rs.3.rs-1745991/v1 Date de publication en ligne : 08/07/2022 En ligne : https://doi.org/10.21203/rs.3.rs-1745991/v1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101265
Titre : GENESIS: Co-location of Geodetic Techniques in Space Type de document : Article/Communication Auteurs : Pacôme Delva, Auteur ; Zuheir Altamimi , Auteur ; Alejandro Blazquez, Auteur ; Mathis Blossfeld, Auteur ; Johannes Böhm , Auteur ; Pascal Bonnefond, Auteur ; et al., Auteur ; Laurent Métivier , Auteur Editeur : Ithaca [New York - Etats-Unis] : ArXiv - Université Cornell Année de publication : 2022 Projets : 1-Pas de projet / AgroParisTech (2007 -) Note générale : bibliographie
auteurs : Pacome Delva, Zuheir Altamimi, Alejandro Blazquez, Mathis Blossfeld, Johannes Böhm, Pascal Bonnefond, Jean-Paul Boy, Sean Bruinsma, Grzegorz Bury, Miltiadis Chatzinikos, Alexandre Couhert, Clement Courde, Rolf Dach, Veronique Dehant, Simone Dell’Agnello, Gunnar Elgered, Werner Enderle, Pierre Exertier, Susanne Glaser, Rudiger Haas, Wen Huang, Urs Hugentobler17, Adrian J¨aggi11, Ozgur Karatekin12, Frank G. Lemoine18, Christophe Le Poncin-Lafitte, Susanne Lunz, Benjamin Mannel, Flavien Mercier, Laurent Metivier, Benoıt Meyssignac, Jurgen Muller, Axel Nothnage, Felix Perosanz, Roelof Rietbroek, Markus Rothacher, Hakan Sert, Krzysztof Sosnica, Paride Testani, Javier Ventura-Traveset, Gilles
Wautelet, and Radoslaw ZajdeLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] co-positionnement
[Termes IGN] état de l'art
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] mission spatiale
[Termes IGN] station de mesureRésumé : (auteur) Improving and homogenizing time and space reference systems on Earth and, more directly, realizing the Terrestrial Reference Frame (TRF) with an accuracy of 1mm and a long-term stability of 0.1mm/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, 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 for predicting natural hazards. The TRF accuracy to be achieved represents the consensus of various authorities which has enunciated geodesy requirements for Earth sciences.
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, proposed as 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 white paper is to review the state-of-the-art and explain the benefits of the GENESIS mission in Earth sciences, navigation sciences and metrology.Numéro de notice : P2022-007 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Preprint nature-HAL : Préprint DOI : 10.48550/arXiv.2209.15298 Date de publication en ligne : 30/09/2022 En ligne : https://doi.org/10.48550/arXiv.2209.15298 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101792 FLAIR: French Land cover from Aerial ImageRy - Challenge FLAIR #1: semantic segmentation and domain adaptation / Anatol Garioud (2022)PermalinkPrecipitation frequency in MED and EURO-CORDEX ensembles from 0.44° to convective permitting resolution: Impact of model resolution and convection representation / Minh Ha-Truong (2022)PermalinkGaining insight into the allometric scaling of trees by utilizing 3d reconstructed tree models - a SimpleForest study / Jan Hackenberg (2022)PermalinkPermalinkBuyTheDips : PathLoss for improved topology-preserving deep learning-based image segmentation / Minh On Vu Ngoc (2022)PermalinkHigh-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach / Martin Schwartz (2022)PermalinkPermalinkCultural Heritage and Climate Change: New challenges and perspectives for research / Christopher Ballard (2022)PermalinkPermalinkLe mémento inventaire forestier, édition 2021 / Institut national de l'information géographique et forestière (2012 -) (2022)Permalink