كليدواژه :
تداخل سنجي راداري , جابجايي , گسل كوهبنان , زلزله داهوئيه , تصاوير ماهواره Envisat
چكيده لاتين :
The use of satellite imagery processing to fault lines extraction and faults identification is very common (Yassaghi, 2006: 35; Mehrabi et al. 2016: 45). However, the use of radar imagery in the field of faults is an emerging phenomenon, and so far, less work has been done. The radar images, in addition to measuring the intensity of the signal, also have phase information, therefore, that can be used in fault studies and earthquakes with using phase information and interferometry technique (Wright et al. 1999: 213; Simons et al. 2002: 145; Qu et al. 2017: 78). The subject of this study is to Measurement of surface displacement caused by the 2004 Dahuieh (Zarand) earthquake in Kerman province and identification of the operating fault using the radar interferometry method.
Materials and Methods
Initially, the focal mechanisms of earthquake information in 2004 were obtained from the site of the International Institute of Earthquake Engineering and seismology (IIEES). Then, two ASAR radar images of ENVISAT satellite were ordered from the ESA, one related to before the earthquake, and one related to after the earthquake event. The image that is related to before the earthquake is called the master image and the image associated with it later is a slave image. Also, a topographic map of 25000/1 was used to provide a digital elevation model (DEM). The processes and interferometric techniques were made using the Envi software via the Sarscape 4.3 plugin.
Results & Discussion
Two ASAR radar images, due to the fact that one was taken before the earthquake and one after the earthquake, can show the changes and effects of the earthquake on the surface as a phase of displacement. As shown in Fig. 4, in the image of the interferometric map that created at the earthquake surface center, numbers of fringes were created. Since the used satellite (Envisat) works in the C band, and each fringe obtained is 2.2 λ equal to 8.2 centimeters, the amount of displacement in the direction of the satellite's view is given by counting the number of fringes. Depending on how the color cycles are observed, the displacement rate also varies, so that if the cycle is yellow-blue-red, moving away from the radar and if the cycle is yellow-red-blue, the shift to the radar has occurred. As shown in Fig. 3, the northern and southern fringes both collide and disappear in both eastern and western parts, Just like the two poles of a magnetic field, if we connect these two poles with a single line, the upper part of the line has an uplift and its lower part has fallen, and almost the same line can be assumed as the fault of the earthquake. Before the interferometric map can provide a surface displacement, with the Goldstein filters must eliminate possible errors, such as the speckle and noise error. Since interferometric phase information is on the 2π scale, there is an ambiguous problem in calculating the correct number of phase currents, so that the interval to the phase observations must be added to obtain the distances. Eventually, the map of displacement created by performing and applying the filter and solving the ambiguity of the phase (Fig. 5). As shown in this figure, the difference in displacement exactly is started from the point of the earthquake surface. The north of this point has a high elevation, and the lower part is drooping. An area of 100 square kilometers has risen with maximum values of 34 cm. An area about 150 square kilometers in the southern part of surface focal has dropped by 24 cm. In Figure 6, the position of the aftershocks occurred one year after the earthquake was also included in the area. As seen, the post-shaking distribution follows the specified fault line. If the stone layers of the area are also examined (Fig. 7), evidence of the breakdown and displacement of these layers is observed exactly along the known fault line.
Conclution
An earthquake of seismic moment magnitude (Mw) 6.4 occurred in eastern Zarand city in Kerman province on February 22th, 2005. At first, the Kuhbanan fault was considered to be the cause of this earthquake. However, further studies of (Nemati and Gheitanchi, 2011: 3) show that One of the secondary faults that caused this earthquake. In this research, we decided to use radar images to investigate and model the changes and displacements occurring on Earth's surface due to this earthquake, and identify the caused fault. On the basis of ascending data, InSAR analysis reveals due to intensity of earthquake in the northern part of surface focal an area of 100 square kilometers has risen with maximum values of 34 cm. Also, an area about 150 square kilometers in the southern part of surface focal has dropped by 24 cm. Based on the results, the causative fault of the earthquake is the east-west fault with a reverse component and a length of 20 km.
