Japan Geoscience Union Meeting 2014

Presentation information

Poster

Symbol M (Multidisciplinary and Interdisciplinary) » M-IS Intersection

[M-IS29_29PO1] Electromagnetic phenomena associated with seismic and volcanic activities

Tue. Apr 29, 2014 6:15 PM - 7:30 PM Poster (3F)

Convener:*Kodama Tetsuya(Earth Observation Research Center, Space Applications Mission Directorate, Japan Space Exploration Agency), Jun Izutsu(College of Engineering, Chubu University), Yasuhide Hobara Yasuhide(Graduate School of Information and Engineering Department of Communication Engineering and Informatics, The University of Electro-Communications), Toshiyasu Nagao(Earthquake Prediction Research Center, Tokai University)

6:15 PM - 7:30 PM

[MIS29-P05] Detection of thermal anomaly associated with Earthquake from MODIS data

*Rika TSUTSUMI1 (1.Chiba University)

Keywords:MODIS, Earthquake, L'Aquila, thermal anomaly

It is a critical issue to mitigate of disasters including earthquake. And it is required to develop of technique to monitor and predict major earthquakes. Therefore, the purpose of this study is to develop an adequate algorithm to detect LST (Land Surface Temperature) anomalies related to earthquakes using MODIS (Moderate Resolution Imaging Spectroradiometer) infrared sensor onboard Terra/Arqua satellite. We investigate spatial-time changes in LST in the statistical way. In order to detect only hotspots related to earthquakes without faints, the developed algorithm investigates the difference temperature behavior between a target point and spatial average, and we get spatial difference of brightness temperature(delta-T). In order to evaluate the temporal singularity of delta-T, we calculate the following equation.R=(delta-T(x,y,t)-ave(x,y))/sigma(x,y)where ave(x,y) is multi year plus minus 15 days moving average. And sigma(x,y) is multi year plus minus 15 days moving standard deviation. We detect LST anomaly 8 days before L'Aquila earthquake. And it continued for several hours. This result represents that it has potential for monitoring/predicting major earthquakes to develop algorithms to detect thermal anomalies using MODIS data.