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The identification of altered rock in vegetation-covered area using hyperspectral remote sensing

Imaging spectroscopic technique has been used for the mineral and rock geological mapping and alteration information extraction successfully with many reasonable results, but it is mainly used in arid and semi-arid land with sparse vegetation covering. In the case of the dense vegetation covering, the outcrop of the altered rocks is small and distributes sparsely, the altered rocks is difficult to be identified directly. The target detection technique using imaging spectroscopic data should be introduced to the extraction of small geological targets under dense vegetation covering area. In the paper, we take Ding-Ma gold deposit as the study area which located in Zhenan country, Shanxi province, China. Some target detection algorithms which are appropriate to the small geological target detection are introduced based on the study of the principle of the algorithms. At last, the small altered rock targets under the covering of vegetation in forest are detected and discriminated using imaging spectroscopy data with the methods of spectral angle map(SAM), Orthogonal Subspace Projection(OSP), Constrained Energy Minimization(CEM), Adaptive Coherence/Cosine Estimator(ACE), Adaptive Matched Filter(AMF), Elliptically Contoured Distributions(ECD). The detection results are reasonable and indicate the ability of target detection algorithms for geological target detection in the forest area.