| Title | Natural and anthropogenic ground deformation monitored using high spatio-temporal resolution MSBAS time series method |
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| Author | Samsonov, S ;
d'Oreye, N; Smets, B |
| Source | Proceedings, MultiTemp 2013: 7th International Workshop on the Analysis of Multi-temporal Remote Sensing Images; by IEEE; 6866021, 2013 p. 1-3, https://doi.org/10.1109/Multi-Temp.2013.6866021 |
| Image |  |
| Year | 2013 |
| Alt Series | Earth Sciences Sector, Contribution Series 20130118 |
| Publisher | IEEE |
| Meeting | MultiTemp 2013: 7th International Workshop on the Analysis of Multi-temporal Remote Sensing Images;; Banff; CA; June 25-27, 2013 |
| Document | book |
| Lang. | English |
| Media | on-line; digital |
| File format | pdf |
| Area | Lac Kivu; Saarbrücken; Congo, the Democratic Republic of the; France; Germany; Luxembourg |
| Lat/Long WENS | 29.0000 29.5000 -13.0000 -17.0000 |
| Lat/Long WENS | 7.0000 8.0000 55.0000 54.7500 |
| Subjects | geophysics; analytical methods; geophysical surveys; radar methods |
| Program | Remote Sensing Science |
| Released | 2013 06 01 |
| Abstract | Multidimensional Small Baseline Subset (MSBAS), methodology is used for integration of multiple InSAR data sets for computation of two or three dimensional time series of deformation. The method is
applied to monitor ground deformation with high spatio-temporal resolution. The MSBAS approach allows 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 method has four main advantages: (i) it achieves combined temporal coverage over an extended period of time when data from many different sensors with different temporal coverages are available; (ii)
temporal resolution of produced time series increases since it includes the combined sampling from all data sets, which helps to observe signal in more details and also to improve the quality of post-processing (i.e. filtering); (iii) two or three
components of ground deformation vector are computed, which helps in interpretation of observed ground deformation and further modeling and inversion; (iv) various sources of noise (i.e. tropospheric, ionospheric, topographic, orbital, thermal, etc.)
are averaged out during the processing improving a signal-to-noise ratio. Performing double difference between time series of carefully chosen pixels allows reducing noise from common sources such as atmosphere and eliminating the influence of the
reference area taken for the time series. For demonstration purposes we apply MSBAS methodology for mapping volcanic ground deformation in Virunga Volcanic Province in Congo and mining deformation along the French-German border. |
| Summary | (Plain Language Summary, not published)
Ground deformation (e.g. subsidence, uplift) produced by natural (earthquakes, volcanic eruptions) and anthropogenic (bridge and building collapses)
disasters is one of the largest sources of casualties and damage to infrastructure around the world. The most cost-efficient tool for monitoring natural and anthropogenic hazards over large regions is space-borne Synthetic Aperture Radar (SAR) and
Canada operates the most advanced SAR satellite in the world - RADARSAT-2. To further improve processing methodologies that are used for monitoring ground deformation here we investigated land uplift in Naples region of Italy that currently is
undergoing active ground deformation due to volcanic inflation. The space-based technique successfully identified seismic-related uplift and subsidence in the study region, along with related seasonal variability. |
| GEOSCAN ID | 292743 |
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