Volume Loss Assessment with MT-InSAR during Tunnel Construction in the City of Naples (Italy)
Abstract
:1. Introduction
2. Area of Interest and Dataset
3. Methodology
3.1. Empirical Method for Tunnel-Induced Vertical Displacements
3.2. Empirical Method for Tunnel-Induced Horizontal Displacements
3.3. Multi Temporal InSAR
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- 7 March 2018 to 2 July 2020 (i.e., from beginning of the analysis to prior to the first excavation);
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- 2 July 2020 to 23 March 2021 (i.e., from the beginning to the end of the first excavation);
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- 23 March 2021 to 7 September 2021 (i.e., from the end of the first excavation to the beginning of the second excavation);
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- 7 September 2021 to 29 January 2022 (i.e., from the beginning of the second excavation to the end of the analysis).
4. Results
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- The stability of the AoI is assessed;
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- The displacement maps right after the excavation of the first and second excavation are presented;
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- Predicted settlement profiles obtained using Equation (15) are compared to those retrieved from MT-InSAR to assess the reliability of the measurements;
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- Monitored data from MT-InSAR, which lie on cross sections orthogonal to the first excavated tunnel axis (the one further east in Figure 2b), are interpolated to gain information on VL and ix. The latter are then used to predict the settlement caused by the second excavation, taking into account the influence of the second excavation on the first one using the superimposition of the effects.
4.1. Assessment of the AoI before the Excavations
4.2. Displacements Maps after the Excavation Processes
4.3. Settlements’ Prediction and Comparison to Monitored Data
4.4. Volume Loss Assessment and Settlement Prediction for the Second Excavation
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
(1 + x·tan(ϑ)/z0)·VL·π·D2/4 − ∫tan(ϑ)/z0·VL·π·D2/4·dx =
VL·π·D2/4 + x·tan(ϑ)/z0·VL·π·D2/4 − x·tan(ϑ)/z0·VL·π·D2/4 =
VL·π·D2/4 = V∗L·π·D2/4 (Equation (A2)) → VL = V∗L.
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% of Monitored Scatters that Fall within the Expected Range | ||||||||
---|---|---|---|---|---|---|---|---|
A | B | C | D | E | F | G | H | I |
64% | 53% | 67% | 59% | 78% | 55% | 64% | 79% | 54% |
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Della Ragione, G.; Rocca, A.; Perissin, D.; Bilotta, E. Volume Loss Assessment with MT-InSAR during Tunnel Construction in the City of Naples (Italy). Remote Sens. 2023, 15, 2555. https://doi.org/10.3390/rs15102555
Della Ragione G, Rocca A, Perissin D, Bilotta E. Volume Loss Assessment with MT-InSAR during Tunnel Construction in the City of Naples (Italy). Remote Sensing. 2023; 15(10):2555. https://doi.org/10.3390/rs15102555
Chicago/Turabian StyleDella Ragione, Gianluigi, Alfredo Rocca, Daniele Perissin, and Emilio Bilotta. 2023. "Volume Loss Assessment with MT-InSAR during Tunnel Construction in the City of Naples (Italy)" Remote Sensing 15, no. 10: 2555. https://doi.org/10.3390/rs15102555
APA StyleDella Ragione, G., Rocca, A., Perissin, D., & Bilotta, E. (2023). Volume Loss Assessment with MT-InSAR during Tunnel Construction in the City of Naples (Italy). Remote Sensing, 15(10), 2555. https://doi.org/10.3390/rs15102555