P-Band InSAR for Geohazard Detection over Forested Terrains: Preliminary Results
Abstract
:1. Introduction
2. Data and Methodology
2.1. Airborne P-Band SAR Acquisition and Processing
2.2. Spaceborne L-Band SAR Acquisition and Processing
3. Results
3.1. Identified Geohazards from P-Band InSAR
3.2. Coherence Comparison of P-Band and L-Band InSAR
3.3. Comparison of P-Band and L-Band SAR on Geohazard Detection
4. Discussion
4.1. Impacts of Radar Frequency Bands
4.2. Effects of Radar Look Direction
4.3. Resolution and Pixel Spacing of SAR Imagery
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
- Lu, Z.; Dzurisin, D.; Jung, H.S.; Zhang, J.X.; Zhang, Y.H. Radar image and data fusion for natural hazards characterization. Int. J. Image Data Fusion 2010, 1, 217–242. [Google Scholar] [CrossRef]
- Crosetto, M.; Solari, L.; Mróz, M.; Balasis-Levinsen, J.; Casagli, N.; Frei, M.; Oyen, A.; Moldestad, D.A.; Bateson, L.; Guerrieri, L.; et al. The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service. Remote Sens. 2020, 12, 2043. [Google Scholar] [CrossRef]
- Biggs, J.; Wright, T.J. How satellite InSAR has grown from opportunistic science to routine monitoring over the last decade. Nat. Commun. 2020, 11, 1–4. [Google Scholar] [CrossRef] [PubMed]
- Rosen, P.A.; Hensley, S.; Zebker, H.A.; Webb, F.H.; Fielding, E.J. Surface deformation and coherence measurements of Kilauea Volcano, Hawaii, from SIR-C radar interferometry. J. Geophys. Res. Planets 1996, 101, 23109–23125. [Google Scholar] [CrossRef]
- Simard, M.; Hensley, S.; Lavalle, M.; Dubayah, R.; Pinto, N.; Hofton, M. An empirical assessment of temporal decorrelation using the uninhabited aerial vehicle synthetic aperture radar over forested landscapes. Remote Sens. 2012, 4, 975–986. [Google Scholar] [CrossRef] [Green Version]
- Santos, J.R.; Freitas, C.C.; Araujo, L.S.; Dutra, L.V.; Mura, J.C.; Gama, F.F.; Soler, L.S.; Sant’Anna, J.S. Airborne P-band SAR applied to the aboveground biomass studies in the Brazilian tropical rainforest. Remote Sens. Environ. 2003, 87, 482–493. [Google Scholar] [CrossRef]
- Sadeghi, M.; Tabatabaeenejad, A.; Tuller, M.; Moghaddam, M.; Jones, S.B. Advancing NASA’s AirMOSS P-Band Radar Root Zone Soil Moisture Retrieval Algorithm via Incorporation of Richards’ Equation. Remote Sens. 2017, 9, 17. [Google Scholar] [CrossRef] [Green Version]
- Chapin, E.; Chau, A.; Chen, J.; Heavey, B.; Hensley, S.; Lou, Y.; Machuzak, R.; Moghaddam, M. AirMOSS: An airborne P-band SAR to measure root-zone soil moisture. In Proceedings of the 2012 IEEE Radar Conference, Atlanta, GA, USA, 7–11 May 2012; pp. 0693–0698. [Google Scholar]
- USGS (U.S. Geological Survey). National Elevation Datasets–1/3 Arc-Second DEM. 2021. Available online: http://usgs.gov/NationalMap/data (accessed on 10 October 2021).
- Lee, J.; Strovers, B.; Lin, V. C-20A/GIII precision autopilot development in support of NASA’s UAVSAR program. In Proceedings of the NASA Science Technology Conference 2007, Greenbelt, MD, USA, 25 June 2007. [Google Scholar]
- Hensley, S.; Michel, T.; Simard, M.; Jones, C.; Muellerschoen, R.; Le, C.; Zebker, H.; Chapman, B. Residual motion estimation for UAVSAR: Implications of an electronically scanned array. In Proceedings of the 2009 IEEE Radar Conference, Pasadena, CA, USA, 4–8 May 2009; pp. 1–5. [Google Scholar]
- Farr, T.G.; Rosen, P.A.; Caro, E.; Crippen, R.; Duren, R.; Hensley, S.; Kobrick, M.; Paller, M.; Rodriguez, E.; Roth, L.; et al. The shuttle radar topography mission. Rev. Geophys. 2007, 45. [Google Scholar] [CrossRef] [Green Version]
- Goldstein, R.M.; Zebker, H.A.; Werner, C.L. Satellite radar interferometry: Two-dimensional phase unwrapping. Radio Sci. 1998, 23, 713–720. [Google Scholar] [CrossRef] [Green Version]
- Werner, C.; Wegmüller, U.; Strozzi, T.; Wiesmann, A. Gamma SAR and interferometric processing software. In Proceedings of the ERS-Envisat Symposium 2000, Gothenburg, Sweden, 16–20 October 2000. [Google Scholar]
- Jones, E.S.; Mirus, B.B.; Schmitt, R.G.; Baum, R.L.; Burns, W.J.; Crawford, M.; Godt, J.W.; Kirschbaum, D.B.; Lancaster, J.T.; Lindsey, K.O.; et al. Summary Metadata—Landslide Inventories across the United States; U.S. Geological Survey Data Release; U.S. Geological Survey: Reston, VA, USA, 2019. [Google Scholar] [CrossRef]
- Xu, Y.; Schulz, W.H.; Lu, Z.; Kim, J.; Baxstrom, K. Geologic controls of slow-moving landslides near the US West Coast. Landslides 2021, 18, 3353–3365. [Google Scholar] [CrossRef]
- Highland, L.; Bobrowsky, P.T. The Landslide Handbook: A Guide to Understanding Landslides; U.S. Geological Survey Circular 1325: Reston, VA, USA, 2008; 129p. Available online: https://pubs.usgs.gov/circ/1325/ (accessed on 11 November 2021).
- Rosen, P.A.; Hensley, S.; Joughin, I.R.; Li, F.K.; Madsen, S.N.; Rodriguez, E.; Goldstein, R.M. Synthetic aperture radar interferometry. Proc. IEEE 2000, 88, 333–382. [Google Scholar] [CrossRef]
- Rodriguez, E.; Martin, J.M. Theory and design of interferometric synthetic aperture radars. IEE Proc. F Radar Signal Process. 1992, 139, 147–159. [Google Scholar] [CrossRef]
- Jordan, E.C.; Balmain, K.G. Electromagnetic Waves and Radiating Systems, 2nd ed.; Prentice-Hall Inc.: New York, NY, USA, 1968. [Google Scholar]
- Xu, Y.; George, D.L.; Kim, J.; Lu, Z.; Riley, M.; Griffin, T.; de la Fuente, J. Landslide monitoring and runout hazard assessment by integrating multi-source remote sensing and numerical models: An application to the Gold Basin landslide complex, northern Washington. Landslides 2021, 18, 1131–1141. [Google Scholar] [CrossRef]
- Aslan, G.; Foumelis, M.; Raucoules, D.; De Michele, M.; Bernardie, S.; Cakir, Z. Landslide Mapping and Monitoring Using Persistent Scatterer Interferometry (PSI) Technique in the French Alps. Remote Sens. 2020, 12, 1305. [Google Scholar] [CrossRef] [Green Version]
Target Region | Band | Wavelength (cm) | Radar Look Direction | Headng (°) | Look Angle (°) | SLC Pixel Size (Rg × Az, m) | Multi-Looked Pixel Size (Rg × Az, m) | SAR Acquisition Dates | |
---|---|---|---|---|---|---|---|---|---|
Gold Beach | P | 69.72 | Left | 2.9 | 43.1 | 1.7 × 0.6 | 5.0 × 7.2 | Dec 2020 | May 2021 |
L | 24.26 | right | −169.7 | 36.3 | 4.3 × 3.8 | 4.3 × 7.6 | May 2020 | May 2021 | |
Somes Bar | P | 69.72 | left | −4.8 | 48.0 | 1.7 × 0.6 | 5.0 × 7.2 | Dec 2020 | May 2021 |
L | 24.26 | right | −169.2 | 31.4 | 4.3 × 3.2 | 4.3 × 6.4 | Apr 2020 | Apr 2021 | |
Happy Camp | P | 69.72 | left | −160.0 | 48.6 | 1.7 × 0.6 | 5.0 × 7.2 | Dec 2020 | May 2021 |
L | 24.26 | right | −169.2 | 31.4 | 4.3 × 3.2 | 4.3 × 6.4 | Apr 2020 | Apr 2021 |
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Xu, Y.; Lu, Z.; Kim, J.-W. P-Band InSAR for Geohazard Detection over Forested Terrains: Preliminary Results. Remote Sens. 2021, 13, 4575. https://doi.org/10.3390/rs13224575
Xu Y, Lu Z, Kim J-W. P-Band InSAR for Geohazard Detection over Forested Terrains: Preliminary Results. Remote Sensing. 2021; 13(22):4575. https://doi.org/10.3390/rs13224575
Chicago/Turabian StyleXu, Yuankun, Zhong Lu, and Jin-Woo Kim. 2021. "P-Band InSAR for Geohazard Detection over Forested Terrains: Preliminary Results" Remote Sensing 13, no. 22: 4575. https://doi.org/10.3390/rs13224575