Remote sensing techniques in active faults surveying. Case study: detecting active faulting zones NW of Damascus, Syria

In this paper, an effective method is presented to identify active faults from different sources of remote sensing images. First, it was compared the capability of some satellite sensors in active faults survey. Then, it was discussed a few digital image processing approaches used for information enhancement and feature extraction related to faults. Those methods include band ratio, PCA (Principal Components Analysis), Tasseled Cap Transformation, filtering and texture statistics, etc. Extensive experiments were implemented to validate the efficiency of those methods. Landsat MSS, TM and ETM Plus images of NW Damascus Province, Syria have been collected. DEM (Digital Elevation Model) data of 25m resolution and Spot resource satellite -Resource-2 images with pixel size of about 5m are also acquired in very important active faults regions. The experimental results show that remote sensing multi-spectral images have great potentials in large scale active faults investigation. It has also got satisfied results when deal with invisible faults those lying beneath the earth surface. It is known that many of the earthquakes that ever happened on our planet are located in active faults zones. Therefore, it is of most important to obtain detailed information on regional tectonic structures. The main approach of active faults survey at present is to use geological and geophysical methods, such as in-situ measuring, drilling and analysis of gravity and magnetic fields. However, because of the magnitude of the work, there are still many uncertainties that we cannot figure out by traditional approaches. Remote sensing has been brought forward for many years, and has applications in many hazard reduction domains, such as Earthquakes monitoring. Remote sensing technique has been thought as a good complementary tool to map active faults quickly at a large scale, because it can view a wide range of area at a time. Meanwhile, remote sensing images cover the spectrum from visible to Microwave wavelengths of electromagnetic wave, which provides much more useful information. However, there exist invisible faults underground, and those faults cannot be detected clearly from remote sensing images. In this paper, we will use remotely sensed data to identify active faults both at a la- rge spatial scale and small key study areas.