Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry
Abstract
:1. Introduction
1.1. Study Area
2. Materials and Methods
2.1. Open Source Toolboxes
2.2. Data and Processing
2.2.1. Copernicus Sentinel-1 Data
2.2.2. SNAP-StaMPS PSI Processing
- Slave preparation. In this step, the Sentinel-1 Single Look Complex (SLC) data are sorted by acquisition date while checking if SLC assembly (concatenation procedure) is necessary, depending on whether the defined AOI is covered by more than one scene per acquisition date.
- Slave splitting. To enable processing in batch mode, the SNAP Graph Processing Tool (GPT) is used, which runs already-defined processing chains (graphs in xml format). For this step, the TOPSAR-Splitting and Apply Orbit operators are called, to update the annotated orbit information with more precise ones according to their availability (restituted or precise). These orbits are automatically downloaded by SNAP. The corresponding graph is illustrated in Figure 2, part A.
- Coregistration and interferogram computation. This is the most computationally demanding step, as it performs the coregistration of the TOPSAR data (Back-geocoding with Enhanced Spectral Diversity [26] refinement) and produces the interferograms with the Flat-Earth and topographic phase contributions removed. Optionally, a finer subset can be applied over an AOI, as defined in the project configuration file. If no information is provided by the user, the full burst interferograms are generated. The outputs of this step are two debursted stacks of master-slave Single Look Complex (SLC) files and the master-slave interferogram. Supplementary data files required by StaMPS are also generated, including elevation band and orthorectified latitude and longitude coordinates as independent products. The graph employed for this step is shown in Figure 2, part B.
- Stamps export. This is the final step of the single master DInSAR processing, which converts previous processing results into binary raster files compatible with StaMPS readers. Graph shown in Figure 2, part C.
2.2.3. Post-Processing
3. Results
3.1. Critical Urban Infrastructures: Global Road Network
3.2. Subsidence along the Tiber River
3.3. Fiumicino Airport and Ostia Coastal Region
3.4. Other Cases of Strong Displacement Patterns
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Satellite | First Image | Last Image | Orbit Pass | Track | N Acquisitions |
---|---|---|---|---|---|
S1A | 2015/03/24 | 2018/04/13 | Descending | 22 | 82 |
S1A | 2015/03/30 | 2018/04/19 | Ascending | 117 | 87 |
Track | Acquisition Date | Mean Inc. Angle (rad/degrees) | Sub-Swath | Polarization | Initial Burst | Last Burst |
---|---|---|---|---|---|---|
D022 | 2015/05/23 | 0.75/42.97 | IW3 | VV | 5 | 8 |
A117 | 2015/08/09 | 0.67/38.39 | IW2 | VV | 5 | 7 |
Orbit | No Merging LOS/Vertical | 20 m LOS/Vertical | 40 m LOS/Vertical |
---|---|---|---|
Ascending (A117) | 1065328/947386 | 486188/418481 | 264024/211999 |
Descending (D022) | 1342924/1061976 | 580578/439738 | 311615/217237 |
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Delgado Blasco, J.M.; Foumelis, M.; Stewart, C.; Hooper, A. Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry. Remote Sens. 2019, 11, 129. https://doi.org/10.3390/rs11020129
Delgado Blasco JM, Foumelis M, Stewart C, Hooper A. Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry. Remote Sensing. 2019; 11(2):129. https://doi.org/10.3390/rs11020129
Chicago/Turabian StyleDelgado Blasco, José Manuel, Michael Foumelis, Chris Stewart, and Andrew Hooper. 2019. "Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry" Remote Sensing 11, no. 2: 129. https://doi.org/10.3390/rs11020129