Study On The Mineralizing Alteration Information Extraction Based On The Multispectral Data And The Hyper Spectral Data

Mineralization anomalies, which include ore-forming or ore-controlling factors and mineralization indications, are widely used as significant information in target optimization and exploration deployment. The characteristic spectrum produced by the interaction between the electromagnetic wave and surface rock is the theory basis of the mineralizing alteration information extraction by remote sensing. With the development of the remote sensing imaging and the digital image processing technology, the remote sensing combined with the multisource geology is widely used in the geological survey.The area of Hongqi Mountain in the Ejinaqi ,Inner Mongolia, low vegetation cover, is abundant in mineral resources, but the work of mineral survey is still at a lower level which make the traditional methods of prospecting are useless. In the study., the multispectral data of ASTER (Advanced Space - borne Thermal Emission and Reflection) and the hyper spectral data of China's Constellation of Small Satellites for Environment and Disaster Monitoring and Forecasting are used to extract the information of the alteration of rocks and minerals. The main achievements are summarized as follows:1.The Realization of Atmospheric Correction is based on the FLAASH(Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes). The research showed that the atmospheric influences of the satellite images could be eliminated well and accurate surface albedo can be got after FLAASH atmospheric correction.2.The HIS transform and wavlet transform are used for the information fusion to get hyperspectral and high-resolution image. The results shows that HIS transform is more suitable for the study.3.The extraction with ASTER data is Based on the method of the crosta, the combination model with selected eigenvectors of PCA is effectively done to extract the alteration information of the iron mineralization, kaolinization+ sericitization and chloritization. The result is validated by the known mineralization spots. This study shows that ASTER data has better capability for recognition of clay mineral.It also proves the feasibility of this method used for mineral resources searching by remote sensing at such region.4.The alteration information extracted with ASTER data is matching with the spatial distribution of wall-rock hornfelization.5.The extraction of iron mineralization with hyper spectral data of the Satellites for Environment and Disaster Monitoring and Forecasting, processed by"Hourglass"procedure, is matching the result of the extraction with ASTER data shows the feasibility of the method.