| Title | Multidimensional time-series analysis of ground deformation from multiple InSAR data sets applied to Virunga Volcanic Province |
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| Author | Samsonov, S ;
d'Oreye, N |
| Source | Geophysical Journal International vol. 191, no. 3, 2012 p. 1095-1108, https://doi.org/10.1111/j.1365-246X.2012.05669.x  Open Access |
| Image |  |
| Year | 2012 |
| Alt Series | Earth Sciences Sector, Contribution Series 20110351 |
| Publisher | Oxford University Press (OUP) |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Area | North Kivu; Congo, the Democratic Republic of the |
| Lat/Long WENS | 29.0833 29.3333 -1.2500 -1.5000 |
| Subjects | geophysics; remote sensing; satellite geodesy; geodesy; satellite imagery; radar imagery; Virunga Volcanic Province; InSAR |
| Illustrations | location maps; plots; graphs; tables |
| Program | Remote Sensing Science |
| Released | 2012 12 01 |
| Abstract | (Summary)
A novel, multidimensional small baseline subset (MSBAS) methodology is presented for integration of multiple interferometric synthetic aperture radar (InSAR) data sets for
computation of 2- or 3-D time-series of deformation. The proposed approach allows the combination of all possible air-borne and space-borne SAR data acquired with different acquisition parameters, temporal and spatial sampling and resolution,
wave-band and polarization. The produced time-series have improved temporal resolution and can be enhanced by applying either regularization or temporal filtering to remove high-frequency noise. We apply this methodology to map 2003–2010 ground
deformation of the Virunga Volcanic Province (VVP), North Kivu, Democratic Republic of Congo. The horizontal and vertical time-series of ground displacement clearly identify lava compaction areas, long-term deformation of Mt Nyamuragira and 2004,
2006 and 2010 pre- and coeruptive deformation. Providing that enough SAR data is available, the method opens new opportunities for detecting ground motion in the VVP and elsewhere. |
| GEOSCAN ID | 289865 |
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