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

Synthetic Aperture Radar (e.g. ALOS/PALSAR) Methodology (1) • What area do we analyze? 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. IGARSS 2011

Rock failures Methodology (1) • What area do we analyze? 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. Earth’s surface IGARSS 2011

Methodology (1) • What area do we analyze? 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. Earth’s surface IGARSS 2011

Methodology (2) • Microwave radiometer AMSR-E It measures microwave signal power (PR) [W] from the atmosphere and the Earth’s surface as a brightness temperature (TB) [K]. The relationship between PR and TB is TB = PR / (k B). *k: Boltzmann constant, B: Receiver’s bandwidth [Hz] IGARSS 2011

・・・ 6.9 GHz 10.65 GHz 18.7 GHz 23.8 GHz Methodology (3) • Which frequency do we analyze? Frequency characteristic of emitted microwave signal depends on objectives. Frequency characteristic of rock failure microwave signals: 300 MHz 2 GHz 22 GHz Too poor spatial resolution and interference by human activity (e.g. wireless communication) Strong attenuation by water vapor in the atmosphere We analyze brightness temperatures of vertically and horizontally polarized signals at 18.7 GHz (T18V and T18H) in order to detect rock failure microwave signals. IGARSS 2011

Methodology (4) • How do we analyze T18V and T18H? 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. T18V T18H Local and simultaneous increase of T18V and T18H sometimes appears. From experimental results, response for rock failure signal is also likely to have the similar feature. IGARSS 2011

101 pixels (1 pixel = 0.01o) 0.05o 101 pixels Target area Methodology (5) • How do we analyze T18V and T18H? Accordingly, we investigated (1) where (2) when (3) how often during the entire observation period local and simultaneous increases of T18V and T18H appeared in the target area. 10,201 pixels x 4 directions = 40,804 combinations For 40,804 combinations, we investigated time variation of S18 during the entire observation period. IGARSS 2011

3/31/2010 9 We regard S18 as a gamma-distributed variable because it is always larger than 0. Here, we defined S18 which meets CDF(0, S18) ≥ 0.9974as an `abnormally large’ value. 0.9974 is corresponding to CDF( , ) in a normal distribution. CDF in gamma distribution: Methodology (6) • How many combinations’ S18 became abnormally large on each day? Time variation of S18 for a certain combination: IGARSS 2011

3/31/2010 9 Main shock In which combinations did S18 become largest during 1 month centered on the main shock day when we focus only on the similar period in each year? Methodology (6’) • Pre-processing: screening of combinations Time variation of S18 for a certain combination: ― Actually, after screening only combinations which meets this condition, we investigated how many combinations’ S18 became `abnormally large’ on each day. IGARSS 2011

Santiago Main shock (2/27/10) Epicenter Concepcion Target area Analysis Results (1) – 2010 Chile EQ How many combinations’ S18 became `abnormally large’ on each day? 8 years IGARSS 2011

Analysis Results (2) – 2010 Chile EQ Main shock (2/27/10) 2/20/10 S18 values became `abnormally large’ in the largest portion of the target area on 2/20/10 (7 days before the EQ). IGARSS 2011

Analysis Results (3) – 2010 Chile EQ The area where the land surface was severely deformed coincides with that where S18 values became `abnormally large’. δ18 = S18max / S18mean ; In the area with the high δ18 values, S18 values hardly became `abnormally large’. This means the detected phenomenon was extremely rare during the entire observation period. IGARSS 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 S18 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 S18 values became `abnormally large’ in the largest portion of the target area, the portion coincided with the area with severe land surface deformations. IGARSS 2011

Thank you for your attention! IGARSS 2011

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