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In this paper, an effective method is presented to identify active faults from different sources of remote sensing images. First, we compared the capability of some satellite sensors in active faults survey. Then, we 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. We collected Landsat MSS, TM and ETM Plus images of Shandong Province, northern China. DEM (Digital Elevation Model) data of 25 m resolution and Chinese resource satellite-Resource-2 images with pixel size of about 5 m 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. We also get satisfied results when deal with invisible faults those lying beneath the earth surface.