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34 results on '"Martini, Audrey"'

1. Evaluation of drain, a deep-learning approach to rain retrieval from gpm passive microwave radiometer

Author

Viltard, Nicolas, Sambath, Vibolroth, Lepetit, Pierre, Martini, Audrey, Barthès, Laurent, and Mallet, Cécile

Subjects
Computer Science - Machine Learning
Abstract

Retrieval of rain from Passive Microwave radiometers data has been a challenge ever since the launch of the first Defense Meteorological Satellite Program in the late 70s. Enormous progress has been made since the launch of the Tropical Rainfall Measuring Mission (TRMM) in 1997 but until recently the data were processed pixel-by-pixel or taking a few neighboring pixels into account. Deep learning has obtained remarkable improvement in the computer vision field, and offers a whole new way to tackle the rain retrieval problem. The Global Precipitation Measurement (GPM) Core satellite carries similarly to TRMM, a passive microwave radiometer and a radar that share part of their swath. The brightness temperatures measured in the 37 and 89 GHz channels are used like the RGB components of a regular image while rain rate from Dual Frequency radar provides the surface rain. A U-net is then trained on these data to develop a retrieval algorithm: Deep-learning RAIN (DRAIN). With only four brightness temperatures as an input and no other a priori information, DRAIN is offering similar or slightly better performances than GPROF, the GPM official algorithm, in most situations. These performances are assumed to be due to the fact that DRAIN works on an image basis instead of the classical pixel-by-pixel basis.

Published
2023

2. ICE GENESIS: Synergetic Aircraft and Ground-Based Remote Sensing and In Situ Measurements of Snowfall Microphysical Properties

Author

Billault-Roux, Anne-Claire, Grazioli, Jacopo, Delanoë, Julien, Jorquera, Susana, Pauwels, Nicolas, Viltard, Nicolas, Martini, Audrey, Mariage, Vincent, Le Gac, Christophe, Caudoux, Christophe, Aubry, Clémantyne, Bertrand, Fabrice, Schwarzenboeck, Alfons, Jaffeux, Louis, Coutris, Pierre, Febvre, Guy, Pichon, Jean Marc, Dezitter, Fabien, Gehring, Josué, Untersee, Aude, Calas, Christophe, Figueras I Ventura, Jordi, Vie, Benoit, Peyrat, Adrien, Curat, Valentin, Rebouissoux, Simon, Berne, Alexis, Environmental Remote Sensing Laboratory [Lausanne], Ecole Polytechnique Fédérale de Lausanne (EPFL), SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Airbus Helicopters, Aeroport International de Marseille-Provence, Federal Office of Meteorology and Climatology MeteoSwiss, and Météo-France

Subjects
Snowfall, Atmospheric Science, Cloud microphysics, Precipitation, Radars/Radar observations, Remote sensing, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Icing
Abstract

An international field experiment took place in the Swiss Jura in January 2021 as a milestone of the European ICE GENESIS project (www.ice-genesis.eu/), which aims to better measure, understand, and model the ice/snow particle properties and mechanisms responsible for icing of rotor-craft and aircraft. The field campaign was designed to collect observations of clouds and snowfall at a prescribed range of temperatures (−10° to +2°C). The suite of in situ and remote sensing instruments included airborne probes and imagers on board a SAFIRE ATR-42 aircraft, able to sample liquid and ice particles from the micron to the millimeter size range, as well as icing sensors and cameras. Two 95 GHz Doppler cloud radars were installed on the SAFIRE ATR-42, while six Doppler weather radars operating at frequencies ranging from 10 to 95 GHz (and one lidar) were ground based. An operational polarimetric weather radar in nearby France (Montancy) complements the coverage. Finally, observations of standard meteorological variables as well as high-resolution pictures of falling snowflakes from a multiangle snowflake camera were collected at the ground level. The campaign showed its full potential during five (multihourly) flights where precipitation was monitored from cloud to ground. The originality of this campaign resides in the targeted specific temperature range for snowfall and in the synchronization between the ground-based remote sensing and the aircraft trajectories designed to maximize the collection of in situ observations within the column above the radar systems.

Published
2023

4. Unsupervised Domain Adaptation to Mitigate Out-of-Distribution Problem of Spatial Radiometer Images: Application to Quantitative Precipitation Estimation

Author

Sambath, Vibolroth, Dubois-Quilici, Natanael, Viltard, Nicolas, Martini, Audrey, and Mallet, Cecile

Abstract

A major issue limiting the successful deployment of deep-learning algorithms in geophysical applications is their inability to generalize to new contexts. Regarding the quantitative precipitation estimation (QPE) from the Global Precipitation Measurement (GPM) satellite constellation, the GPM microwave imager (GMI) contains enough co-located brightness temperatures (TBs) and rain rates data to train a deep-learning inverse model to retrieve precipitation intensity. However, the difference in instrumental configurations makes it impossible to directly apply this inverse operator to another space-borne radiometric imager. A domain adaptation is thus necessary to solve the domain shift problem encountered when applying the model trained on one satellite to another satellite. The present article tests a method to map the SSMI/S data to the GMI data. In the absence of sufficient paired images between the two satellites, we applied a Cycle Consistent Generative Adversarial Network (CycleGAN), which allows for an Unsupervised Domain Adaptation approach. Evaluating the quality of adapted images is a complex problem. This article employs two tactics: a brief evaluation of adapted radiometric images and a qualitative/quantitative evaluation of rain retrieval. Over several case studies, the results show that the domain adaptation step produces adapted SSMI/S images that retain the majority of the rain structure. Next, the rain detection score and intensity bias are then compared using 847 overpasses. The same analysis is carried out over mainland France by comparing the results with rainfall products supplied by Météo-France. In both comparisons, the adapted images allow the inverse operator to provide a better score in rain detection and intensity.

Published
2024
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8. Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach.

Author

Billault-Roux, Anne-Claire, Ghiggi, Gionata, Jaffeux, Louis, Martini, Audrey, Viltard, Nicolas, and Berne, Alexis

Subjects
RADAR, RADAR meteorology, ATMOSPHERIC sciences, MICROPHYSICS, DATA compression, DEEP learning, DOPPLER radar, RADIATIVE transfer
Abstract

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectra. We propose a novel approach to retrieve snowfall properties by combining the latter two techniques, while relaxing some assumptions on, e.g., beam alignment and non-turbulent atmosphere. The method relies on a two-step deep-learning framework inspired from data compression techniques: an encoder model maps a high-dimensional signal to a low-dimensional latent space, while the decoder reconstructs the original signal from this latent space. Here, Doppler spectrograms at two frequencies constitute the high-dimensional input, while the latent features are constrained to represent the snowfall properties of interest. The decoder network is first trained to emulate Doppler spectra from a set of microphysical variables, using simulations from the Passive and Active Microwave radiative TRAnsfer model (PAMTRA) as training data. In a second step, the encoder network learns the inverse mapping, from real measured dual-frequency spectrograms to the microphysical latent space; in doing so, it leverages with a convolutional structure the spatial consistency of the measurements to mitigate the ill-posedness of the problem. The method was implemented on X- and W-band data from the ICE GENESIS campaign that took place in the Swiss Jura Mountains in January 2021. An in-depth assessment of the retrieval accuracy was performed through comparisons with colocated aircraft in situ measurements collected during three precipitation events. The agreement is overall good and opens up possibilities for acute characterization of snowfall microphysics on larger datasets. A discussion of the sensitivity and limitations of the method is also conducted. The main contribution of this work is, on the one hand, the theoretical framework itself, which can be applied to other remote-sensing retrieval applications and is thus possibly of interest to a broad audience across atmospheric sciences. On the other hand, the seven retrieved microphysical descriptors provide relevant insights into snowfall processes. [ABSTRACT FROM AUTHOR]

Published
2023
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9. Dual-frequency spectral radar retrieval of snowfall microphysics: a physically constrained deep learning approach.

Author

Billault-Roux, Anne-Claire, Ghiggi, Gionata, Jaffeux, Louis, Martini, Audrey, Viltard, Nicolas, and Berne, Alexis

Subjects
MICROPHYSICS, DEEP learning, RADAR meteorology, RADAR, ATMOSPHERIC sciences, DATA compression
Abstract

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular through two techniques: the use of multi-frequency radar measurements and the analysis of radar Doppler spectra. We propose a novel approach to retrieve snowfall properties by combining both techniques, while relaxing some assumptions on e.g. beam matching and non-turbulent atmosphere. The method relies on a two-step deep-learning framework inspired from data compression techniques: an encoder model maps a high-dimensional signal to a lower-dimensional "latent" space, while the decoder reconstructs the original signal from this latent space. Here, Doppler spectrograms at two frequencies constitute the high-dimensional input, while the latent features are constrained to represent the snowfall properties of interest. The decoder network is first trained to emulate Doppler spectra from a set of microphysical variables, using simulations from the radiative transfer model PAMTRA as training data. In a second step, the encoder network learns the inverse mapping, from real measured dual-frequency spectrograms to the microphysical latent space; doing so, it leverages the spatial consistency of the measurements to mitigate the problem's ill-posedness. The method was implemented on X- and W-band data from the ICE GENESIS campaign that took place in the Swiss Jura in January 2021. An in-depth assessment of the retrieval's accuracy was performed through comparisons with colocated aircraft in-situ measurements collected during 3 precipitation events. The agreement is overall good and opens up possibilities for acute characterization of snowfall microphysics on larger datasets. A discussion of the method's sensitivity and limitations is also conducted. The main contribution of this work is on the one hand the theoretical framework itself, which can be applied to other remote sensing retrieval applications and is thus possibly of interest to a broad audience across atmospheric sciences. On the other hand, the retrieved seven microphysical descriptors provide relevant insights into snowfall processes. [ABSTRACT FROM AUTHOR]

Published
2022
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10. Statistical database from existing data sets to assess the performances of a dynamics and microphysics studies-oriented mission: DYCECT

Author

Viltard, Nicolas, Martini, Audrey, Delanoë, Julien, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), and Viltard, Nicolas

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract

International audience; A breakthrough for energy and water budgets would be to retrieve the horizontal and vertical transport terms. We propose here to study the feasibility of a mission that would carry a scanning polarimetric Doppler radar: DYCECT (DYnamique et Cycle de l'Eau dans la Convection Tropicale). The purpose of the mission would not only to be able to measure rain but also to retrieve instantaneous wind fields and statistics of dynamical properties in convection and to retrieve the microphysical properties of precipitating ice. In this study we used the existing data sets (TRMM-PR, CloudSat, GPM-DPR) to build a statistical database allowing us to characterize the cloud types and properties as seen by the future instrument. We can thus define more precisely the effective added value of the latter. We evaluated the occurrence and statistical properties of the rain systems that will be observed, depending on the radar characteristics. The poor temporal sampling of DYCECT (1 to 2 overpasses per day) will force us to work on averaged dynamical properties. It is thus necessary to check how long it takes to converge towards such values because this might impact the minimum required duration of the mission. Datasets already available (TRMM, GPM-Core, Cloudsat) will allow us to characterize the occurrence of the systems according to size, height of the detected clouds, average ice/water content, etc., which will impact the detection capabilities of the future instrument.

Published
2019

12. Développements radar au LATMOS pour l'études des propriétés microphysiques des nuages et des précipitations

Author

Viltard, Nicolas, Le Gac, Christophe, Martini, Audrey, Lemaître, Yvon, Pauwels, Nicolas, Delanoë, Julien, Lesage, Guillaume, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), and Viltard, Nicolas

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, microphysique glacée, bande X, précipitations, bande W, nuages, radar
Abstract

International audience; Ce document donne une brève introduction des activités de recherche sur la microphysique des nuages et des précipitations effectuées au LATMOS. Si de très nombreuses études ont été menées par le passé sur les propriétés des distributions dimensionnelles de tailles de gouttes, des questions restent ouvertes sur les caractéristiques des particules glacées dans les différents types de nuages et l'impact que ceux-ci peuvent avoir sur le bilan hydrique et de bilan radiatif. Au LATMOS, nous concevons, développons, déployons et exploitons des radars en bande X et W afin de d'améliorer notre connaissance des liens entre dynamique et microphysique dans les systèmes précipitants.

Published
2019

13. DYCECT-WIVERN: mesurer les vitesses Doppler pour restituer le vent 3D dans la convection

Author

Viltard, Nicolas, Martini, Audrey, Lemaître, Yvon, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), and Cardon, Catherine

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

International audience; La mission DYCECT a été proposée à la prospective du CNES en 2014. Elle a pour ambition d’effectuer une mesure de la vitesse Doppler associée au déplacement des hydrométéores dans la convection avec un balayage permettant d’accéder au champ 3D de vent. Ce champ ouvrirait ensuite la porte à la réalisation de bilan d’eau et d’énergie en prenant en compte les termes de transports horizontaux et verticaux. La présentation fera un état des lieux des activités en question dans la communauté française et au niveau de l’Europe.

Published
2018

14. GT Précipitation (SIRTA)

Author

Banson, Sandra, Baray, Jean-Luc, Barthès, Laurent, Bastin, Sophie, Chazottes, Aymeric, Delanoë, Julien, Dilmi, Djallel, Dupont, Jean-Charles, Gires, Auguste, Hallali, Ruben, Jahangir, Emad, Lemaître, Yvon, Martini, Audrey, Mallet, Cécile, Molinié, Gilles, Parent Du Châtelet, Jacques, Paz, Igor, Schertzer, D, Tchiguirinskaia, Ioulia, Van Baelen, Joël, Viltard, Nicolas, Laboratoire de Météorologie Physique - Clermont Auvergne (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Hydrologie, Météorologie et Complexité (HM&Co), École des Ponts ParisTech (ENPC), Centre de Géosciences (GEOSCIENCES), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Centre national de recherches météorologiques (CNRM), Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Mines Paris - PSL (École nationale supérieure des mines de Paris), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), MINES ParisTech - École nationale supérieure des mines de Paris, Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology
Abstract

International audience; Le rôle du GT est de coordonner les activités d'observation et d'étude des précipitations qui exploiteront l’infrastructure et les moyens mis en œuvre sur le SIRTA, de s’insérer dans action de structuration au niveau national des activités en radar météorologie, d'être en relation avec la structuration des moyens d’observations atmosphériques français (SOERE ATMOS, IR-ATMO / ACTRIS-FR ), dêtre une des briques du réseau d’observations national (plateformes d’observations existantes en France)

Published
2017

15. Post-GPM rain retrieval and 3-D wind retrieval: the DYCECT mission

Author

Lemaître, Yvon, Martini, Audrey, Viltard, Nicolas, Arago Higueras, Nadia, Delanoë, Julien, Le Gac, Christophe, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Viltard, Nicolas

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract

International audience; Abstract: GPM-core (Global Precipitation Mission) was launched in the spring 2014 and the post-GPM era is already in the decision/design phase. This is why it is time to investigate future possible missions to be launched. We propose here to study the feasibility of a mission that would carry a scanning polarimetric Doppler radar: DYCECT. This mission would not only be able to measure rain but also to build instantaneous wind fields and statistics of dynamics in convection and to retrieve the microphysical properties of precipitating ice.Indeed, the critical variables that have not been measured so far by satellite-borne instruments are the three components of the wind field in the convection. Scanning radars with Doppler capability could allow us to retrieve dynamic information along with the rain estimates. This dynamic information would not only be a breakthrough in terms of our knowledge of convective properties (specifically over deep ocean) but also, dynamics can be a help to improve retrieval of rain because of the strong connection between the latter and microphysics.In 2018, the EarthCare ESA-JAXA mission will see the first Doppler cloud radar (nadir pointing). In parallel ESA’s ADM-AEOLUS with a Doppler lidar will provide some hints about the global dynamics. DYCECT will come to complement these missions, benefiting of these first results and going one step further.

Published
2015

16. Rain retrieval using the SAPHIR water vapor sounder on Megha-Tropiques

Author

Martini, Audrey, Viltard, Nicolas, Sivira, Ramses, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Viltard, Nicolas

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract

International audience; Megha-Tropiques is an Indo-French satellite launched in 2011 to study the water and energy cycle in the tropical belt. The satellite carries on board three passive instruments: MADRAS, an microwave imager, SAPHIR a microwave water vapor sounder, and ScaraB a broadband VIRS to compute TOA radiative budget. Unfortunately, MADRAS worked nominally only for about 14 month before failing. This was a dramatic loss for the rain retrieval objectives of the Megha-Tropiques mission. As an alternative solution an algorithm was developed to retrieve rain from SAPHIR using a combination of the 183 GHz channels. The latter are nominally designed to retrieve water vapor profiles but are also sensitive to scattering by ice. Bennartz and Bauer (2005) showed some preliminary results on the scattering regimes of such sounding instruments. We pushed further on and showed that the sounding properties remain true even in the scattering regime. By co-locating SAPHIR and three space-borne radars: CPR on CloudSat, PR on TRMM and DPR on GPM, we were able to test extensively the information content of the microwave brightness temperatures in scattering regime using the RTTOV-scatt radiative transfer model. This allows us to gather information on the vertical structure of the precipitating ice on the upper part of the cloud. The vertical structure of ice is in turn related to the properties of the convection: deep or shallow and intense or weak. Using these last properties, a rain retrieval algorithm was designed. The presentation will detail how the algorithm works, evaluate its performances and compare the results with the retrieval from MADRAS over the fourteen-month when the two instruments were functioning together.

Published
2015

17. Characterization of the microphysics of ice in tropical convection

Author

Martini, Audrey, Viltard, Nicolas, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), American Meteorological Society, and Cardon, Catherine

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU.STU.ME] Sciences of the Universe [physics]/Earth Sciences/Meteorology, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

International audience; Megha-Tropiques is a joint satellite between France and India to study the water and energy cycle in the Tropics. The satellite is part of GPM and provides an exceptional sampling of the 23° S-23° N region because of the low inclination of its orbit (20°) combined with the large swath (1700 km) of its main instrument MADRAS. The latter is a 9-channel passive microwave radiometer dedicated mainly to precipitation retrieval. Bauer et al (2005) showed that the most critical source of uncertainties in the precipitation retrieval over land comes from the ice microphysics characteristics. In the framework of the Megha-Tropiques mission we tried to improve the parameterization of precipitating ice in the radiative transfer model.Datasets from two field experiments (Niamey 2010 and Gan 2011) will be used here. These campaigns were specifically designed to improve our knowledge of the ice categories found in the tropical convection. A combination of ground-based (X and S-band) and airborne (W-band) radars was used in conjunction with in-situ probes for microphysics. We will show some comparisons of Particles IDentification (PID) made from the various polarimetric radars in continental Africa and Indian Ocean with the images from these probes. The main idea here is to combine polarimetric radar data and microphysics in-situ measurements, both acquired during the two campaigns to demonstrate the coherence between PID (Particles IDentificator) classification and the microphysical characterization of the ice particles. This analysis will serve as a base to support the construction of a more “climatological” characterization of the ice depending on the convective features: life cycle, environment, season, etc… This climatology will then be compared with the brightness temperature at 89 GHz and 157 GHz of MADRAS.

Published
2014

18. Use of MADRAS on Megha-Tropiques to study Hurricane Sandy and Typhoon Bophat Evolution

Author

Viltard, Nicolas, Martini, Audrey, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), American Meteorological Society, and Cardon, Catherine

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

International audience; Megha-Tropiques is a French-Indian satellite dedicated to tropical convection. The low-inclination of (20°) its orbit and the large swath of its main instrument MADRAS allows us to sample the rain systems in series of overpasses separated by 1h30 time lags. Coupled with other similar sensors like TMI on TRMM, AMSR2 on GCOM-W or SSMI and SSMIS on NOAA satellites, we are able to get a good sampling of the temporal evolution of those systems in terms of rain structures and intensities. Hurricanes are particularly interesting because their characteristic life time is a few days and their general motion is relatively slow. Furthermore, the characteristic scale and structure of their precipitation field gives a lot of information about their evolution and those fields are compatible with the spatial resolution of the spaceborne instruments even if the smallest details cannot be captured.MADRAS produced only 15 month of data from October 2011 to January 2013; During its life time it captured a number of hurricanes and typhoons in the various basins. We will focus here on the evolution of two storms that were nicely sampled by MADRAS. First, Hurricane Sandy in October 2011 was observed in its first few days about 16 times from its the tropical storm stage in the Gulf of Mexico and until it moved out of the Caribbean regions as a mature hurricane after crossing through the Island of Cuba. Similarly, typhoon Bophat was sampled while it formed and intensified in the Warm Pool and until it made its landfall in the Philippines.We will show in the presentation how, through examination of the brightness temperatures at 89 and 157 GHz and the rain retrieval algorithm known as BRAIN, we can understand the evolution of each of the storms and how critical satellite with low-inclinations orbits are critical for hurricane forecasts and studies.

Published
2014

19. Algorithm Validation in the Megha-Tropiques Framework: An Attempt to Improve the Microphysic Parameterization in a Radiative Transfer Model

Author

Martini, Audrey, Viltard, Nicolas, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Cardon, Catherine

Subjects
[SDU.STU.ME] Sciences of the Universe [physics]/Earth Sciences/Meteorology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Physics::Atmospheric and Oceanic Physics
Abstract

In the framework of the Megha Tropiques Mission, we focus on the rain retrieval from MADRAS and other conical-scanning passive microwave imagers. The retrieval algorithm used here is a Bayesian-based algorithm known as BRAIN (Bayesian Rain retrieval Algorithm Including Neural network), which is described in the paper by Viltard et al. (2006). The retrieved rain rate is obtained through the use of a reference database built from a Radiative Transfer Model (RTM) simulation. In order to improve the simulation of the brightness temperatures, it is necessary to provide the RTM with an accurate parameterization of the ice particles. In this context, a study is in progress to evaluate if polarimetric radar hydrometeor retrievals are useful to distinguish the various ice species in precipitating systems and if it is possible to correlate these with the observed brightness temperatures. The goal of the study is to develop a series of parameterization corresponding to various meteorological situations to be used in the RTM . Datasets from the NCAR dual-wavelength S- and Ka-band radar (S-PolKa) collected during the Dynamics of the MJO (DYNAMO) field campaign that occurred in the Indian Ocean in 2011-2012 were compared with brightness temperatures from TRMM-TMI and MADRAS. Using the SPOLKA data, a PID (Particles IDentificator) classification is built using a fuzzy logic approach. To combine this information with the TMI and MADRAS brightness temperature we co-locate the polarimetric radar data inside the TMI radiometer pixel. A piewedge representation is chosen to show the proportion in the satellite pixel of the various species identified by the SPOLKA radar and associated with the PID.

Published
2013

20. Upper Tropospheric humidity from Megha-Tropiques : A humidity-convection study

Author

Viltard, Nicolas, Brogniez, Hélène, Martini, Audrey, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Cardon, Catherine

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDE.MCG] Environmental Sciences/Global Changes, [SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDE.MCG]Environmental Sciences/Global Changes, [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

Upper tropospheric humidity (UTH) and rainfall estimates are produced operationally from Megha-Tropiques observations since its launch on October 12th, 2012. With its low inclination (20°) orbit, this indo-french satellite offers a frequent revisit of the tropical belt giving 3 to 5 passes every day. This configuration provides an interesting sampling of the convective systems during their life that allows studies of their evolution, from their precipitation core to their close environment. The UTH is computed for the 3 upper channels of SAPHIR (±0.2 GHz, ±1.1 GHZ and ± 2.8 GHz) following a well established method applied to water vapor channels (6.3μm: e.g. Soden and Bretherton, 1993; 183 GHz: e.g. Spencer and Braswell, 1997) which gives an idea of the vertical distribution of the relative humidity in the upper part of the troposphere. The CINDY/DYNAMO international campaign that took place over the equatorial Indian Ocean from the 1st October 2011 to the 31 March 2012 aimed to study the conditions for the development of active convection in the context of the MJO (Madden-Julian Osillation). Thanks to a large deployment of ground instruments (SPol-Ka polarimetric radar, Smart-R radar, radiosoundings) and airborne measurements (SAPHIR-Falcon 20, NOAA-P3) it is possible to describe quite thoroughly the whole state of the atmosphere while the Megha-Tropiques satellite (mainly SAPHIR and MADRAS instruments) overpasses. This offers an ideal opportunity to study the relationship between convection and its moist environment. A few case studies are selected from the CINDY/DYNAMO observations and explored with the Megha-Tropiques estimations of rainfall and UTH: a simple eulerian approach is used over the area of activity of the cloudy systems and the distribution of UTH is analyzed and associated to the rainfall rate which is a good signature of the intensity of convection

Published
2013

21. Characterization of the microphysics of ice in tropical convection for rain retrieval algorithms

Author

Martini, Audrey, Viltard, Nicolas, Gosset, Marielle E., Cazenave, P., Toledo Machado, Luiz Augusto, SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Instituto Nacional de Pesquisas Espaciais (INPE), Ministério da Ciência, Tecnologia e Inovação, Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDE.MCG]Environmental Sciences/Global Changes
Abstract

Megha-Tropiques is a joint satellite between France and India to study the water and energy cycle in the Tropics. The satellite is part of GPM and will provide a exceptional sampling of the 23° S-23° N region because of the low inclination of the orbit (20°) combined with the large swath (1700 km) of its main instrument MADRAS. MADRAS is a 9-channel passive microwave radiometer dedicated mainly to precipitation retrieval. Bauer et al (2005) showed that the most critical source of uncertainties in the precipitation retrieval over land comes from the ice microphysics characteristics. In the framework of the Megha-Tropiques mission we tried to improve the parameterization of precipitating ice in the radiative transfer model. Datasets from three field experiments (Niamey 2010, Gan 2011 and CHUVA) will be used here. Niamey 2010 and Gan 2011 were specifically designed to study these ice particles. A combination of ground-based (X and S-band) and airborne (W-band) radars were used in conjunction with in-situ microphysics. CHUVA, is more generally dedicated to study the rain regimes over various regions of Brazil, sees the deployment of a ground-based polarimetric X-band radar. We will show some comparisons of Particles IDentification (PID) made from the various polarimetric radars in continental Africa, Indian Ocean and continental Brazil respectively. Building some statistics, we will try to show how the life cycle of the system and the various environments impact on the ice microphysics characteristics and consequently will be taken into account in the rain retrieval algorithm for MADRAS on Megha-Tropiques.

Published
2012

23. Télédétection des couverts neigeux en milieu alpin à partir de données Radar Multi-polarisées et Polarimétriques

Author

Dedieu, Jean-Pierre, Martini, Audrey, Pottier, Eric, Ferro-Famil, Laurent, Niang, A., Durand, Yves, Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Dipartimento di Scienze Zootecniche, Università degli Studi di Firenze [Firenze], Institut d'Electronique et de Télécommunications de Rennes (IETR), Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Institut d'Électronique et des Technologies du numéRique (IETR), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Firenze = University of Florence (UniFI), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and Nantes Université (NU)-Université de Rennes 1 (UR1)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDE.MCG]Environmental Sciences/Global Changes, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2006

24. Snow extent mapping in Alpine areas using polarimetric SAR data

Author

Martini, Audrey, Dedieu, Jean-Pierre, Ferro-Famil, Laurent, Bernier, Monique, Pottier, Eric, Institut d'Electronique et de Télécommunications de Rennes (IETR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Scientifique [Québec] (INRS), Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-SUPELEC-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), and Nantes Université (NU)-Université de Rennes 1 (UR1)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDE.MCG]Environmental Sciences/Global Changes, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; This paper proposes one original technique to map the snow extent in the French Alps from SAR measurements using SIR-C fully polarimetric winter/summer data sets at L and C-bands. The method relies on a multi-frequency two-step approach. Basic natural media types, like surface and forest, are first discriminated over the scene under observation from a polarimetric analysis of summer measurements at L-band. Secondly, the presence of snow is then detected separately over each media type using the H-A-a polarimetric decomposition theorem. An original PCVE (polarimetric contrast variation enhancement) procedure provides optimal emission/reception polarisation states that maximise the C-band winter to summer response of snow-covered areas. The results are compared to Landsat optical images acquired simultaneously.

Published
2006

25. Dry Snow discrimination in a high mountainous environment (French Alps) using multi-frequency and multi-temporal polarimetric SAR data

Author

Martini, Audrey, Dedieu, Jean-Pierre, Ferro-Famil, Laurent, Pottier, Eric, Environnements, Dynamiques et Territoires de la Montagne (EDYTEM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut d'Electronique et de Télécommunications de Rennes (IETR), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Environnements, Dynamiques et Territoires de Montagne (EDYTEM), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDE.MCG]Environmental Sciences/Global Changes, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2006

26. Télédétection d'un couvert neigeux en milieux alpins à partir de données SAR polarimétriques multi-fréquentielles et multi-temporelles

Author

Martini, Audrey, Institut d'Electronique et de Télécommunications de Rennes (IETR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Université Rennes 1, Eric POTTIER(eric.pottier@univ-rennes1.fr), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)

Subjects
modélisation électromagnétique incohérente, Télédétection, multi-temporal and multi-frequency procedure, snow cover, radar polarimetry, couvert neigeux, Remote sensing, cartographie, mapping, traitement multi-temporel et multi-fréquentiel, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, incoherent scattering model, polarimétrie radar
Abstract

This work introduces multi-frequency and multi-temporal snow cover analysis methods in alpine region using polarimetric parameters.From a digital elevation model, a polarimetric study is developed to relate the altitude to a specific snow cover behaviour.Theses methods are applied onto SIR-C SAR polarimetric data acquired over the alpine Risoul and Izoard sites.; Le suivi de la neige sèche a une place importante dans la télédétection, en raison du grand intérêt des applications en hydrologie, climatologie ou de la prévision d'avalanche. Ce travail présente des méthodes d'analyse multi-fréquentielles et multi-temporelles du couvert neigeux en milieux alpins à partir de données SAR polarimétriques.A l'aide d'un modèle numérique de terrain, une étude polarimétrique altitudinale du couvert neigeux est développée, permettant d'associer une attitude à un comportement polarimétrique spécifique.Ces méthodes sont appliquées sur des données SAR polarimétriques SIR-C des sites alpins de Risoul et Izoard.

Published
2005

27. Inferring snow parameters using C-band data from ENVISAT/ASAR alternating polarization in alpine environment

Author

Niang, M., Martini, Audrey, Dedieu, Jean-Pierre, Paquet, E., Bernier, Monique, Ferro-Famil, Laurent, Pottier, Eric, Durand, Yves, Guyomarc'H, G., Merindol, L., Sergent, C., Institut d'Electronique et de Télécommunications de Rennes (IETR), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Institut d'Électronique et des Technologies du numéRique (IETR), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2005

28. Snow Extent Mapping in Alpine Areas using different SAR Polarimetric Configurations

Author

Martini, Audrey, Dedieu, Jean-Pierre, Ferro-Famil, Laurent, Niang, M., Durand, Yves, Paquet, E., Bernier, Monique, Pottier, Eric, Institut d'Electronique et de Télécommunications de Rennes (IETR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and Nantes Université (NU)-Université de Rennes 1 (UR1)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2005

29. Mapping Dry Snow in Mountain Regions from Fully Polarimetric SAR Data

Author

Martini, Audrey, Dedieu, Jean-Pierre, Ferro-Famil, Laurent, Pottier, Eric, Institut d'Electronique et de Télécommunications de Rennes (IETR), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Institut d'Électronique et des Technologies du numéRique (IETR), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2005

30. A polarimetric contrast variation enhancement method to discriminate dry snow in alpine areas

Author

Ferro-Famil, Laurent, Pottier, Eric, Martini, Audrey, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institut d'Electronique et de Télécommunications de Rennes (IETR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), and Université de Nantes (UN)-Université de Rennes 1 (UR1)

Published
2004

31. Two novel surface model based inversion algorithms using mulit-frequency polSAR data

Author

Martini, Audrey, Ferro-Famil, Laurent, Pottier, Eric, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and Nantes Université (NU)-Université de Rennes 1 (UR1)

Subjects
ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2004

32. Snow extent discrimination in alpine areas from polarimetric and multi-frequency SAR data

Author

Martini, Audrey, Ferro-Famil, Laurent, Pottier, Eric, Institut d'Electronique et de Télécommunications de Rennes (IETR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and Université de Nantes (UN)-Université de Rennes 1 (UR1)

Subjects
ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2004

34. Modélisation polarimétrique de la diffusion par un volume naturel

Author

Martini, Audrey, Ferro-Famil, Laurent, Pottier, Eric, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and Nantes Université (NU)-Université de Rennes 1 (UR1)

Subjects
ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2002

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