عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Over the last two decades there have been numerous reports from different seismically active regions of the world that thermal infrared (TIR) anomalies can be identified around the epicentral areas before major earthquakes [e.g. (Tronin et al., 2002)]. The TIR anomalies reportedly appear as early as 14 to 7 days before the seismic events and affect areas as large as 1000s to 100,000s km2 in size. Our case study for detection of TIRs using NOAA -AVHRR data(Band 4) is an Ms = 5.1 earthquake that occurred on 14th October 2004 near Ravar in Kerman province located in Loot and Tabas deserts, southeast-central Iran. The area is part of the Golbaf-Sirj seismogenic zone. It includes major faults comprising regional geology of cenozoic granitic to intermediate igneous rocks in the north and east, but cretaceous shales, sandstone (Shemshak Formation) and limestone in the center and west. The epicentral region is surrounded by the Nayband fault to the east, the Lakarkuh fault in the center, and the Kuhbanan fault to the west. To find TIR anomalies we surveyed the night-time satellite data of the epicental area representing the period of 2 ½ years before the Ravar earthquake checking the background noise, cloud cover and other meteorological conditions to ensure stable, high quality data. Finally we selected 14 dates of which the first 8 cover 2 ½ years prior to the earthquake to establish a reference TIR background. The remaining 6 dates cover the period from 11 days to 2 days before the event. The last day before and the day of the earthquake were not included due to regional cloudiness. To optimize the information extracted from the available satellite data, three methodologies were designed. Since this is a post-event analysis, we have the advantage of knowing the location of the epicenter.
1- Square Array Method (SAM): We superimpose over the epicenter a series of squares with their edges increasing from 10, 20, 30, 40, 60, 80, 120, to 200. We integrate the TIR intensities over each of these squares.
2- Rectangle Array Model (RAM): We superimpose rectangles over the epicenter with their longest edges aligned along the trace of the N–S trending Lakar Kuh fault, up to a maximum length of 200 km and an aspect ratio of about 5. We integrate the TIR intensities over the area of each of these rectangles.
3- Geologic Square Array Method: we divided the largest square in SAM model into 9 equivalent squares to detect geologic effects spatially igneous rocks item on the appearance TIR anomalies. We integrate the TIR intensities over the area of each of these rectangles.
Results showed the NOAA (AVHRR) band 4 is suitable for detecting thermal anomalies before earthquakes. In this research the abnormal increase of TIR radiation around the epicentral region was detected using three slightly different methodologies, SAM, RAM and GSAM. The primary results indicate that the area emitting enhanced TIR radiation was aligned along the Lakarkuh fault, which ruptured during the event. The results further indicate that the TIR anomaly reached its highest intensity six nights before the Ravar earthquake. Also the GSAM model extracted small differences in the TIR intensity emitted from igneous rocks and sand or gravel surfaces of which the maximum anomaly was allocated to igneous ones. Finally this study has shown that, given near-ideal weather conditions and a barren desert land surface, a TIR anomaly can be clearly identified for a relatively modest seismic event such as the M5.1 Ravar earthquake using NOAA (AVHRR) data.