References of "d'Oreye, Nicolas"
     in
Bookmark and Share    
Full Text
See detailDevelopment of an Interferometric Mass Processing Chain for Multitemporal Ground Deformation Measurements
Libert, Ludivine ULiege; De Rauw, Dominique ULiege; d'Oreye, Nicolas

Conference (2017, November 07)

The main goal of the RESIST project is to understand the mechanisms driving volcanic eruptions and landslides in the Kivu region, on the East African Rift. In order to model both volcanic and landslide ... [more ▼]

The main goal of the RESIST project is to understand the mechanisms driving volcanic eruptions and landslides in the Kivu region, on the East African Rift. In order to model both volcanic and landslide processes, it is necessary to measure ground deformations in the region accurately. For this purpose, both ground-based instruments (e.g. GPS network) and spaceborne data (e.g. optical and SAR images) are used. One aspect of the project focuses on Differential SAR Interferometry (DInSAR), which is a technique used to map ground deformations occurring between two SAR images acquired at different times. It is today a well-mastered technique that offers large spatial coverage with a typical temporal sampling of one to several days, depending on the chosen sensor. In the last years, multitemporal approaches based on DInSAR have been developed, like the Small BAseline Subset (SBAS) [1] and Multidimensional Small BAseline Subset (MSBAS) [2] techniques, or the Persistent Scatterers Interferometry (PSI) [3]. In the framework of RESIST, we use MSBAS to perform ground deformations monitoring along time. The Multidimensional Small BAseline Subset (MSBAS) technique produces 2-D time series of ground deformations by integrating data sets of SAR images acquired by different sensors, with different spatial and temporal sampling, resolutions, incidence angles, wavelengths, pass directions and other varying parameters. By combining at least two data sets with overlapping spatial and temporal coverage and an extended range of look angles, the evolution of deformations in the vertical and west-east directions can be computed by the MSBAS approach [2]. The MSBAS software feeds on a large amount of deformation maps, which are produce by DInSAR. Such an amount of data cannot be produced by hand and that is the reason why we developed an automatic interferometric processing chain meant to produce large amounts of products adequate for multitemporal methods like MSBAS. The interferometric processing is supported by the CSL InSAR Suite (CIS) software developed at Centre Spatial de Liège, which presents the advantages to be fully adaptable to the needs of the MSBAS technique and the thematic specificities. Indeed, numerous options (e.g. adaptive filtering, wide swath interferometry) have been added to the CIS software in the framework of the RESIST project. In a first time, we will briefly present the MSBAS approach and its advantages regarding the ground deformation measurements. In the second part of the presentation, we will introduce the mass processing chain step by step and its functionalities. Critical steps of the chain, like the chosen strategy for the interferometric pairs selection, the integration of Sentinel-1 data or the image interpolation approach, will be presented in more details. Finally, preliminary results of an MSBAS processing over the Bukavu area will be presented. REFERENCES: [1] Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E. (2002). A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, IEEE Trans. Geosci. Remote Sens., 40, 11, pp. 2375-2383. doi: 10.1109/TGRS.2002.803792. [2] Samsonov, S., and d’Oreye, N. (2012). Multidimensional time series analysis of ground deformation from multiple InSAR data sets applied to Virunga Volcanic Province, Geophysical Journal International, 191, 3, pp. 1095-1108. doi: 10.1111/j.1365-246X.2012.05669.x [3] Ferretti, A., Prati, C., and Rocca, F. (2001). Permanent scatterers in SAR interferometry, IEEE Trans. Geosci. Remote Sens., 39, 1, pp. 8-20. doi: 10.1109/36.898661. [less ▲]

Detailed reference viewed: 37 (1 ULiège)
Full Text
Peer Reviewed
See detailSplit-Band Interferometry-Assisted Phase Unwrapping for the Phase Ambiguities Correction
Libert, Ludivine ULiege; De Rauw, Dominique ULiege; d'Oreye, Nicolas et al

in Remote Sensing (2017), 9(9),

Split-Band Interferometry (SBInSAR) exploits the large range bandwidth of the new generation of synthetic aperture radar (SAR) sensors to process images at subrange bandwidth. Its application to an ... [more ▼]

Split-Band Interferometry (SBInSAR) exploits the large range bandwidth of the new generation of synthetic aperture radar (SAR) sensors to process images at subrange bandwidth. Its application to an interferometric pair leads to several lower resolution interferograms of the same scene with slightly shifted central frequencies. When SBInSAR is applied to frequency-persistent scatterers, the linear trend of the phase through the stack of interferograms can be used to perform absolute and spatially independent phase unwrapping. While the height computation has been the main concern of studies on SBInSAR so far, we propose instead to use it to assist conventional phase unwrapping. During phase unwrapping, phase ambiguities are introduced when parts of the interferogram are separately unwrapped. The proposed method reduces the phase ambiguities so that the phase can be connected between separately unwrapped regions. The approach is tested on a pair of TerraSAR-X spotlight images of Copahue volcano, Argentina. In this framework, we propose two new criteria for the frequency-persistent scatterers detection, based respectively on the standard deviation of the slope of the linear regression and on the phase variance stability, and we compare them to the multifrequency phase error. Both new criteria appear to be more suited to our approach than the multifrequency phase error. We validate the SBInSAR-assisted phase unwrapping method by artificially splitting a continuous phase region into disconnected subzones. Despite the decorrelation and the steep topography affecting the volcanic test region, the expected phase ambiguities are successfully recovered whatever the chosen criterion to detect the frequency-persistent scatterers. Comparing the aspect ratio of the distributions of the computed phase ambiguities, the analysis shows that the phase variance stability is the most efficient criterion to select stable targets and the slope standard deviation gives satisfactory results. [less ▲]

Detailed reference viewed: 26 (3 ULiège)
Full Text
See detailThe Split-Band Interferometry Approach to Determine the Phase Unwrapping Offset
Libert, Ludivine ULiege; De Rauw, Dominique ULiege; d'Oreye, Nicolas et al

Poster (2017, June)

This poster presents an approach based on the Split-Band Interferometry to solve the ambiguities introduced during the phase unwrapping of separate regions.

Detailed reference viewed: 24 (5 ULiège)
Full Text
See detailThe RESIST Project: a Study of Geohazards in the Kivu Basin Region using ground- and space borne Techniques
Libert, Ludivine ULiege; d'Oreye, Nicolas; Kervyn, François et al

Poster (2015, September)

Presentation of the goals and means of the RESIST project

Detailed reference viewed: 13 (0 ULiège)
Full Text
See detailSplit-Band Interferometric SAR Processing Using TanDEM-X Data
De Rauw, Dominique ULiege; Kervyn, François; d'Oreye, Nicolas et al

in ESA SP-731 (2015, March)

Most recent SAR sensors use wide band signals to achieve metric range resolution. One can also take advantage of wide band to split it into sub-bands and generate several lower-resolution images, centered ... [more ▼]

Most recent SAR sensors use wide band signals to achieve metric range resolution. One can also take advantage of wide band to split it into sub-bands and generate several lower-resolution images, centered on slightly different frequencies, from a single acquisition. This process, named Multi Chromatic Analysis (MCA) corresponds to performing a spectral analysis of SAR images. Split-Band SAR interferometry (SBInSAR) is based on spectral analysis performed on each image of an InSAR pair, yielding a stack of sub-band interferograms. Scatterers keeping a coherent behaviour in each sub-band interferogram show a phase that varies linearly with the carrier frequency, the slope being proportional to the absolute optical path difference. This potentially solves the problems of phase unwrapping on a pixel-per-pixel basis. In this paper, we present an SBInSAR processor and its application using TanDEM-X data over the Nyiragongo volcano. [less ▲]

Detailed reference viewed: 271 (16 ULiège)
Full Text
Peer Reviewed
See detailSource parameters of the 2008 Bukavu-Cyangugu earthquake estimated from InSAR and teleseismic data
d'Oreye, Nicolas; Gonzalez, P.; Shuler, A. et al

in Geophysical Journal International (2011)

Detailed reference viewed: 28 (5 ULiège)
Full Text
Peer Reviewed
See detailThe 2007 rifting event in Northern Tanzania studied by C and L-band interferometry
Oyen, Anneleen; Wauthier, Christelle ULiege; d'Oreye, Nicolas et al

in ECGS Blue Books (2010)

Detailed reference viewed: 35 (1 ULiège)
Full Text
Peer Reviewed
See detailModeling of InSAR displacements related with the January 2002 eruption of Nyiragongo volcano
Wauthier, Christelle ULiege; Cayol, Valérie; Kervyn, François et al

in ECGS Blue Books (2010)

Detailed reference viewed: 117 (1 ULiège)