single-dr.php

JDR Vol.12 No.3 pp. 526-535
(2017)
doi: 10.20965/jdr.2017.p0526

Paper:

Views over last 60 days: 933

Synthetic Aperture Radar Interferometry for Disaster Monitoring of Harbor Facilities

Ryo Natsuaki*1,†, Takuma Anahara*1, Tsuyoshi Kotoura*2, Yuudai Iwatsuka*3, Naoya Tomii*4, Hiroyuki Katayama*3, and Takeshi Nishihata*2

*1Earth Observation Research Center, Japan Aerospace Exploration Agency
2-1-1 Sengen, Tsukuba, Ibaraki 305-8508, Japan

†Corresponding author

*2Institute of Technology, Penta-Ocean Construction Co., Ltd., Tochigi, Japan

*3Nagoya Branch, Penta-Ocean Construction Co., Ltd., Aichi, Japan

*4Satellite Applications and Operations Center, Japan Aerospace Exploration Agency, Tokyo, Japan

Received:
August 31, 2016
Accepted:
February 26, 2017
Online released:
May 29, 2017
Published:
June 1, 2017
Creative Commons License
Keywords:
synthetic aperture radar, interferometry, disaster monitoring, ALOS-2, PALSAR-2
Abstract

In this paper, we present experimental results of the disaster monitoring of harbor facilities using spaceborne synthetic aperture radar interferometry (InSAR). The Advanced Land Observing Satellite-2 (ALOS-2 or DAICHI-2), operated by the Japan Aerospace Exploration Agency (JAXA), carries the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2). PALSAR-2 can observe disaster areas day and night, in any weather, at a resolution of approximately 3 m. ALOS-2 PALSAR-2 has been used to measure large-scale ground deformation e.g., after earthquakes and volcanic eruptions. However, its robustness for smaller targets, such as harbor facilities, has not yet been substantiated. Here, we measured the uplift of a breakwater model made of concrete armor units, and confirmed the sensor accuracy to be better than 2 cm standard deviation. We also analyzed the damage to the Nagata and Suma ports in Kobe city, Hyogo prefecture, Japan hit by the 11th Typhoon in 2014, and detected the damaged area using interferometric coherence analysis.

Cite this article as:
R. Natsuaki, T. Anahara, T. Kotoura, Y. Iwatsuka, N. Tomii, H. Katayama, and T. Nishihata, “Synthetic Aperture Radar Interferometry for Disaster Monitoring of Harbor Facilities,” J. Disaster Res., Vol.12, No.3, pp. 526-535, 2017.
Data files:
References
  1. [1] W. M. Boerner, “Recent advances in extra-wide-band polarimetry, interferometry and polarimetric interferometry in synthetic aperture remote sensing and its applications,” Radar, Sonar Navigation, IEE Proc. Vol.150, No.3, pp. 113-124, 2003.
  2. [2] W.Liu, F. Yamazaki, B. Adriano, E. Mas, and S. Koshimura, “Development of Building Height Data in Peru from High-Resolution SAR Imagery,” J. of Disaster Research, Vol.9, No.6, pp. 1042-1049, doi: 10.20965/jdr.2014.p1042, 2014.
  3. [3] W. Liu, F. Yamazaki, and T. Sasagawa, “Monitoring of the Recovery Process of the Fukushima Daiichi Nuclear Power Plant from VHR SAR Images,” J. of Disaster Research, Vol.11, No.2, pp. 236-245 doi: 10.20965/jdr.2016.p0236, 2016.
  4. [4] P. Nakmuenwai, F. Yamazaki, and W. Liu, “Multi-Temporal Correlation Method for Damage Assessment of Buildings from High-Resolution SAR Images of the 2013 Typhoon Haiyan,” J. of Disaster Research, Vol.11, No.3, pp. 577-592, doi: 10.20965/jdr.2016.p0577, 2016.
  5. [5] Kankaku Y. et al., 2014, “PALSAR-2 Launch and Early Orbit Status” Proc. of IEEE Geoscience and Remote Sensing Symposium 2014, pp. 3410-3412, 2014.
  6. [6] M. Shimada and Y. Osawa, “ALOS-2 science program and high resolution SAR applications,” In Procs. of SPIE 8528: November 9 2012. pp. 852812, doi:10.1117/12.979379, 2012.
  7. [7] R. Natsuaki, H. Nagai, T. Motohka, M. Ohki, M. Watanabe, R.B. Thapa, T. Tadono, M. Shimada, and Shinichi Suzuki, “SAR interferometry using ALOS-2 PALSAR-2 data for the Mw 7.8 Gorkha Nepal earthquake,” Earth, Planets and Space, Vol.68-15, pp. 1-13, doi: 10.1186/s40623-016-0394-4, 2016.
  8. [8] C. Jimenez, N. Moggiano, E. Mas, B. Adriano, S. Koshimura, Y. Fujii, and H. Yanagisawa, “Seismic Source of 1746 Callao Earthquake from Tsunami Numerical Modeling,” J. of Disaster Research, Vol.8, No.2, pp. 266-273 doi: 10.20965/jdr.2013.p0266, 2013.
  9. [9] A. Hooper, F. Sigmundsson, and F. Prata, “Remote sensing of volcanic hazards and their precursors,” Procs. of the IEEE, Vol.100, No.10, pp. 2908-2930, 2012.
  10. [10] A. Ferretti, C Prati, and F. Rocca, “Permanent Scatterers in SAR Interferometry,” IEEE Trans. on Geoscience and Remote Sensing, Vol.39, No.1, pp. 8-20, 2001.
  11. [11] R. Natsuaki, T. Anahara, T. Kotoura, Y. Iiwatsuka, N. Tomii, H. Katayama, and T. Nishihata, “Preliminary Experiment for Disaster Monitoring In Harbor using Synthetic Aperture Radar Interferometry,” J. of Japan Society of Civil Engineers, Ser. B3, Vol.72, No.2, 2016 (in print).
  12. [12] M. Matsuoka and M. Estrada, “Development of Earthquake-Induced Building Damage Estimation Model Based on ALOS/PALSAR Observing the 2007 Peru Earthquake,” J. of Disaster Research, Vol.8 No.2 pp. 346-355, doi: 10.20965/jdr.2013.p0346, 2013.
  13. [13] B. Adriano, E. Mas, S. Koshimura, M. Estrada, and C. Jimenez, “Scenarios of Earthquake and Tsunami Damage Probability in Callao Region, Peru Using Tsunami Fragility Functions,” J. of Disaster Research, Vol.9 No.6 pp. 968-975, doi: 10.20965/jdr.2014.p0968, 2014.
  14. [14] S. Plank “Rapid Damage Assessment by Means of Multi-Temporal SAR – A Comprehensive Review and Outlook to Sentinel-1,” Remote Sensing, Vol.6, pp. 4870-4906, doi: 10.3390/rs6064870, 2014.
  15. [15] I. G. Cumming and F. H. C. Wong, “Digital processing of Synthetic Aperture Radar data: algorithms and implementation,” Artech House, 685 Canton Street, Norwood, MA 02062 USA, 2005.
  16. [16] D. C. Ghiglia and M. D. Pritt, “Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software,” John Wiley & Sons, Inc., 1998.
  17. [17] F. Mayer, N. Bamler, R. Jakowski, and T. Fritz, “The potential of low-frequency SAR systems for mapping ionospheric TEC distributions, “IEEE Geoscience and Remote Sensing Letters, Vol.3, No.4, pp. 560-564, 2006.
  18. [18] G. Gomba, A. Parizzi, F. De Zan, M. Eineder, and R, Bamler, “Toward operational compensation of ionospheric effects in SAR interferograms: the split-spectrum method,” IEEE Trans. on Geoscience and Remote Sensing, Vol.54, No.3, pp. 1446-1461, doi:10.1109/TGRS.2015.2481079, 2015.
  19. [19] H. S. Jung and W. J. Lee “An improvement of ionospheric phase correction by multiple-aperture interferometry,” IEEE Trans. on Geoscience and Remote Sensing, Vol.53, No.9, pp. 4952-4960, 2015.
  20. [20] M. P. Doin, C. Lasserre, G. Peltzer, O. Cavalié, and C. Doubre “Corrections of stratified tropospheric delays in SAR interferometry: validation with global atmospheric models,” J. of Applied Geophysics Vol.69, pp. 35-50, doi:10.1016/j.jappgeo.2009.03.010, 2009.
  21. [21] D. P. S. Bekaert, R. J. Walters, T. J. Wright, A. J. Hooper, and D. J. Parker, “Statistical comparison of InSAR tropospheric correction techniques,” Remote Sensing En-vironment, Vol.170, pp. 40-47, doi:10.1016/j.rse.2015.08.035, 2015.
  22. [22] R. Touzi, A. Lopes, J. Bruniquel, and P. W. Vachon, “Coherence estimation for SAR imagery,” IEEE Trans. on Geoscience and Remote Sensing, Vol.37, No.1, pp. 135-149, doi: 10.1109/36.739146, 1999.
  23. [23] R. Abdelfattah and J-M. Nicolas, “Interferometric SAR Coherence Magnitude Estimation Using Second Kind Statistics,” IEEE Trans. on Geoscience and Remote Sensing, Vol.44, No.2, pp. 1942-1953, 2003.J. Clerk Maxwell, “A Treatise on Electricity and Magnetism,” 3rd ed., Vol.2. Oxford: Clarendon, pp. 68-73, 1892.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 19, 2023