Thermal anomaly detection for 2014 Jinggu earthquake using remote sensing data

Thermal anomaly appears to be a significant precursor of some strong earthquakes. In this study, time series of daily MODIS Land Surface Temperature (LST) product are processed and analyzed to detect possible anomalies prior the Jinggu earthquake (7 October 2014, Yunnan Province). In order to reduce the seasonal or annual effects from the LST variations, also to avoid the rainy and cloudy weather in this area, a background data of 10-day LST are derived using averaging MOD11A2 products from 2001 to 2013. Then the 10-day LST data from August 2014 to December 2014 were differenced using the above background. RX anomaly detection algorithm was applied to detect the anomalies. Abnormal LST increase before the earthquake is quite obvious from the differential images, indicating that this method is useful in such area with high mountains and cloudy weather. The study indicates that LST change detection is somewhat effective in this area for earthquake precursor study.