1. Jul. 29, 2011IGARSS 2011 1 [3118] RELATION BETWEEN ROCK FAILURE MICROWAVE SIGNALS DETECTED BY AMSR-E AND A DISTRIBUTION OF RUPTURES GENERATED BY SEISMIC ACTIVITY Takashi Maeda Japan Aerospace Exploration Agency, Earth Observation Research Center Tadashi Takano Nihon University

2. IGARSS 20112 Jul. 29, 2011 Contents Introduction Methodology Latest Analysis Results Conclusion

3. IGARSS 20113 Jul. 29, 2011 Detection of microwave signals generated by rock failures in a laboratory Simulation of detection capability of rock failure microwave signals using a satellite-borne microwave sensor Detection of microwave signals generated by rock failures in a field test Algorithm development for a satellite-borne microwave sensor to detect rock failure microwave signals and case studies for some earthquakes (1) Maki, K. and T. Takano et al., J. of the Seismological Society of Japan, 2006. (3) Takano, T. and T. Maeda, IEEE Geoscience and Remote Sensing Letters, 2009. (4) Maeda, T. and T. Takano, IEEE Trans. on Geoscience and Remote Sensing, 2008. (5) Maeda, T. and T. Takano, IEEE Trans. on Geoscience and Remote Sensing, 2010. (2) Takano, T. and T. Maeda et al., IEEJ Trans. FM, 2009. Today’s topic

4. IGARSS 20114 Jul. 29, 2011 Contents Introduction Methodology Latest Analysis Results Conclusion

5. IGARSS 20115 Jul. 29, 2011 Methodology (1) What area do we analyze? Synthetic Aperture Radar (e.g. ALOS/PALSAR) Earth’s surface SAR can detect an area where the land surface was deformed by seismic activity. However, due to its poor time resolution, it cannot determine by what the land surface was deformed, preslips, a main shock or aftershocks.

6. IGARSS 20116 Jul. 29, 2011 Methodology (1) What area do we analyze? Earth’s surface Rock failures In such an area, rock failures are likely to occur extremely near the land surface. Microwave signals generated by these rock failures should be emitted into free space without attenuation in the ground.

7. IGARSS 20117 Jul. 29, 2011 Methodology (1) What area do we analyze? Earth’s surface Additionally, once cracks appear in the ground, rock failure microwave signals in the ground, which are caused by aftershocks, should be more easily emitted into free space because cracks act as waveguides. Accordingly, we focus on an area where severe land surface deformations were detected by InSAR rather than an epicenter.

8. IGARSS 20118 Jul. 29, 2011 Methodology (2) Microwave radiometer AMSR-E It measures microwave signal power (P R ) [W] from the atmosphere and the Earth’s surface as a brightness temperature (T B ) [K]. The relationship between P R and T B is T B = P R / (k B). * k: Boltzmann constant, B: Receiver’s bandwidth [Hz]

9. IGARSS 20119 Jul. 29, 2011 Methodology (3) Which frequency do we analyze? Frequency characteristic of emitted microwave signal depends on objectives. 300 MHz2 GHz22 GHz Frequency characteristic of rock failure microwave signals: 23.8 GHz6.9 GHz10.65 GHz18.7 GHz ・・・ Strong attenuation by water vapor in the atmosphere Too poor spatial resolution and interference by human activity (e.g. wireless communication) We analyze brightness temperatures of vertically and horizontally polarized signals at 18.7 GHz (T 18V and T 18H ) in order to detect rock failure microwave signals.

10. IGARSS 201110 Jul. 29, 2011 Methodology (4) How do we analyze T 18V and T 18H ? When we define a 1 deg x 1deg rectangular area in latitude and longitude as a target area, AMSR-E observes there almost every night since June 2002. Local and simultaneous increase of T 18V and T 18H sometimes appears. From experimental results, response for rock failure signal is also likely to have the similar feature. T 18V T 18H

11. IGARSS 201111 Jul. 29, 2011 0.05 o Methodology (5) How do we analyze T 18V and T 18H ? Accordingly, we investigated (1) where (2) when (3) how often during the entire observation period local and simultaneous increases of T 18V and T 18H appeared in the target area. 10,201 pixels x 4 directions = 40,804 combinations 101 pixels (1 pixel = 0.01 o ) 101 pixels Target area For 40,804 combinations, we investigated time variation of S 18 during the entire observation period.

12. IGARSS 201112 Jul. 29, 2011 Methodology (6) How many combinations’ S 18 became abnormally large on each day? 9 3/31/2010 Time variation of S 18 for a certain combination: CDF in gamma distribution: We regard S 18 as a gamma-distributed variable because it is always larger than 0. Here, we defined S 18 which meets CDF(0, S 18 ) ≥ 0.9974 as an `abnormally large’ value. 0.9974 is corresponding to CDF(, ) in a normal distribution.

13. IGARSS 201113 Jul. 29, 2011 Methodology (6’) Pre-processing: screening of combinations 9 3/31/2010 Time variation of S 18 for a certain combination: In which combinations did S 18 become largest during 1 month centered on the main shock day when we focus only on the similar period in each year? Main shock ― Actually, after screening only combinations which meets this condition, we investigated how many combinations’ S 18 became `abnormally large’ on each day.

14. IGARSS 201114 Jul. 29, 2011 Contents Introduction Methodology Latest Analysis Results Conclusion

15. IGARSS 201115 Jul. 29, 2011 Main shock (2/27/10) Santiago Concepcion Epicenter Target area Analysis Results (1) – 2010 Chile EQ How many combinations’ S 18 became `abnormally large’ on each day? 8 years

16. IGARSS 201116 Jul. 29, 2011 Analysis Results (2) – 2010 Chile EQ 2/20/10 Main shock (2/27/10) S 18 values became `abnormally large’ in the largest portion of the target area on 2/20/10 (7 days before the EQ).

17. IGARSS 201117 Jul. 29, 2011 Analysis Results (3) – 2010 Chile EQ δ 18 = S 18max / S 18mean ; In the area with the high δ 18 values, S 18 values hardly became `abnormally large’. This means the detected phenomenon was extremely rare during the entire observation period. The area where the land surface was severely deformed coincides with that where S 18 values became `abnormally large’.

18. IGARSS 201118 Jul. 29, 2011 Contents Introduction Methodology Latest Analysis Results Conclusion

19. IGARSS 201119 Jul. 29, 2011 Conclusion We analyzed the data of AMSR-E to detect rock failure signals associated with an earthquake.  We focused on an area where the land surface severely deformed rather than an epicenter.  We investigated how large was the potion of the target area where S 18 became `abnormally large’ on each day during the observation period. In this presentation, we illustrated the analysis results for the 2010 Chile Earthquake.  We detected the portion began to enlarge before a main shock, became largest around the main shock, and shrank with the termination of aftershock activity (as we detected the similar phenomena for other earthquakes).  When S 18 values became `abnormally large’ in the largest portion of the target area, the portion coincided with the area with severe land surface deformations.

20. IGARSS 201120 Jul. 29, 2011 Thank you for your attention!