EFIDIR: Extraction et Fusion d'Informations pour la mesure de Déplacement par Imagerie Radar - ANR Masse de données et Connaissances project 2008-2011
- University Savoie Mont Blanc / LISTIC : Computer Science, Systems, Information and Knowledge Processing Laboratory.
- University of Rennes 1 / IETR : Rennes Institute of Electronics and Telecommunications.
- CNRS / GIPSA-Lab: Grenoble Image Parole Signal Automatique.
- CNRS / LTCI: Information Processing and Communication Laboratory, Télécom ParisTech.
- CNRS / LGIT: Laboratoire de Géophysique Interne et de Tectonophysique, Chambéry/Grenoble.
- CNRS / LG: Geology Laboratory, ENS Paris.
Emmanuel TROUVÉ, LISTIC, Université Savoie Mont Blanc University.
The data currently provided by SAR (Synthetic Aperture Radar) sensors on remote remote sensing satellites are particularly voluminous: typically 1 Gigabyte is needed to archive 1 interferometric pair of a 100kmx100km ERS scene, and at least 40 pairs are required for a time series. To fully and systematically exploit this massive amount of data, it is necessary to develop specific processing techniques to access geological, geomorphological and tectonic information. The availability of this vast amount of data, combined with the uncertainties surrounding the parameters of physical models (ground truth and/or acquisition systems), has led to the use of data mining and information fusion techniques.
The aim of the EFIDIR project is to develop an open archiving and processing platform adapted both to the specific features of SAR data and to the large time series used for displacement measurements. In the 90s, thanks to data acquired by the first generation of satellite SAR sensors (ERS-1, ERS-2, JERS, Radarsat-1), it was shown that, by judicious use of time series over a given site, it was possible to deduce, over large areas, displacements of the order of a fraction of a wavelength. In particular, on examples of urban subsidences, differential interferometry on gratings (using stable scatterers called PS: permanent scatterers) achieves millimetric accuracies on displacement, but requires large time series (at least 40 images). Today, new-generation SAR satellites are - or will be - placed in orbit: ENVISAT, ALOS, Radarsat-2, Terrasar-X and CSK. Most often combined with new modalities (such as polarimetry), these sensors deliver new data, which are even more voluminous in terms of storage space because they are better resolved. This opens the way to new applications, but will also require reformulation of the processing chains currently in use.
The need for a " Massede Donnéeset COnnaissance" project covering the entire information processing chain is explained, on the one hand, by the volume and nature of the data (raw "RAW data" or complex multi-varied "SLC data" images supplied by space agencies) and, on the other hand, by the various phenomena that disturb and bury the information sought: speckle, decorrelation, atmospheric disturbances, etc. To obtain thematic information from these multi-temporal interferometric and polarimetric data, a complex processing chain has to be implemented: To obtain thematic information from these multi-temporal interferometric and polarimetric data, a complex processing chain must be implemented (SAR synthesis, interferogram generation, PolSAR/Pol-InSAR decomposition, fringe unwinding, georeferencing, artifact correction, geophysical model inversion, etc.). At present, this chain only exists in partial form through closed and expensive commercial software, making it very difficult to adapt to new themes or new types of data (high-resolution, polarimetric, etc.) for which they were not initially designed. In this context of specific databases, the design, production and validation of specific codes to complement the processing elements available in open-source software are the aim of this project.
The proposed application is characteristic of the expectations of a user community, the "geophysicists", with regard to the "information processing" community, to design and make operational original approaches capable of overcoming current obstacles thanks to the exploitation of the mass of data and the taking into account of domain expertise. To this end, the project draws on databases linked to a number of original themes, such as :
- the low-amplitude (but wide-ranging) movements linked to the filling of large dams (Serre Ponçon lake, studied by the LG),
- glacier surface movements (LISTIC, GIPSA, LTCI), localized and of greater amplitude, for which, following the ACI Masse de Données MEGATOR (2004-2007), a vast and diverse database is available (ERS, ENVISAT), in the process of being supplied (ENVISAT, ALOS, E-SAR) or to be supplied (for satellites not yet launched: Radarsat-2, Terrasar-X),
- volcanic movements (Mexican "laboratory" volcanoes studied by LGIT). In all these cases, current processing chains have shown their limitations.
The project is divided into three sub-projects:
- SP1, which aims to develop complementary signal and image processing tools in line with the proposed themes. This will involve work on "coherent targets" and refocusing, as well as the introduction of tools dedicated to polarimetric data.
- SP2, which aims to integrate these tools into software platforms for tracing ground displacement parameters. It will focus on small displacements (mainly using "permanent targets") and large displacements (with particular emphasis on polarimetric data).
- SP3, the information fusion stage, which aims to enable the transition to geophysical quantities. This last phase will validate the complete processing chain on pilot thematic applications.
To achieve these objectives, this multi-disciplinary project brings together 4 ICST laboratories specializing in SAR image processing and information fusion, and 2 Earth sciences laboratories. This grouping guarantees the development and dissemination of methodological tools guided and validated by applications. These advances will make it possible to transform the mass of data from satellite radar imagery into displacement measurements, thereby enriching our knowledge of the geophysical phenomena observed.