| Thermal anomaly detection before strong Earthquakes regarding the fault zones distances and using MODIS thermal data |
| Paper ID : 1260-SMPR |
| Authors: |
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Arash Karimi *, Mohammad Reza Saradjian School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran |
| Abstract: |
| The recent scientific researches in the context of earthquake precursors reveals some processes connected to seismic activity including thermal anomaly before earthquakes which is a great help for making better decision regarding this disastrous phenomena and reducing its casualty to minimum. This paper represents a new method for generating the input data for different Thermal anomaly detection methods using the average land surface temperature in multiple distances from the corresponding fault during the forty days (i.e. 30 days before and 10 days after earthquake event). Six strong earthquakes (i.e. M >6) that has occurred in Iran have been investigated in this study. Results show that each anomaly detection method has slightly different lead times and the local time of anomalies, despite using the same data source of LST values but Results also show that these proposed input data produce less false alarms in each of the thermal anomaly detection methods compared to the ordinary inputs thus making this method much more accurate and stable Considering the easy accessibility of thermal data and their less complicated algorithms for processing, thermal anomaly is one with the most significant precursor for earthquake parameter estimation to be jointly used with other precursors. So it is recommended to use thermal anomaly as an initial process to limit the search for other precursors which need more complicated algorithms and data to process. |
| Keywords: |
| Earthquake, Earthquake Precursors Thermal Anomaly, LST, Active fault, MODIS Thermal Data Product |
| Status : Paper Accepted (Poster Presentation) |
