Image Fusion and Evaluation of Geological Disaster Based on Remote Sensing

Abstract

The investigation of geological disaster in our article locates in southern Australia, which is characterized by wide range, high relief, inaccessibility and other unfavorable factors. Multi-spectral ETM+ and SPOT 5 pan images were selected as the remote sensing data source, and Brovey transform (BT), intensity-hue-saturation (IHS), principal component analysis (PCA), high-pass filtering (HPF) and modified Gram-Schmidt (MGS) methods were used for image fusion. A comparison has been conducted between the resultant fusion images to assess the image quality both in subjective and objective evaluation. The results show that, the MGS method is the optimal image fusion method for geological disaster interpretation, and can provide abundant textural and spectral information in interpreting such geological disasters as landslide, rock fall and debris flow.