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Geology Disaster
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Multi-Source remotely sensed data applied to gold and nonferrous metals exploration in Xinjiang region
Techniques and Methodology
The eight types of remotely sensed data have been collected in the Northen Xinjiang including 5 types spaceborne data, Landsat TM, MSS, SPOT, NOAA AVHRR and MSS are efficient at searching and determining the emphasized study areas. TM is capable of identifying the alteration zone due to its high spectral resolution. Because of their high special resolution, SPOT HRV and colored infrared data become the major information sources for analysing the geometric feature of mineralized geological bodies. Radar data has prominent advantages in structure interpretation. As a kind of complement data, National landsat data play an important role, especially in area without other data cover.
In this study, platform includes both space borne and airborne, wavelength covers visible, infrared and microwave, the emphasized study areas were covered by all three kinds of wavelength. The image resolution varies from 2m to 100m which suits different demands of study. This is one of the key techniques of the program and is effective an economic. The second key technique is information extraction: start from understanding the imaging mechanism of mineralized geological body, analyse the anomalous image features, develop effective methods, extract mineralization information. The third one is to integrate remotely sensed data with geological geophysical and geochemical data. Through the comparison and integration of multi-source data the best analysis results are reached.
Figure 1 demonstrated the procedures and techniques of the study. On the basis of it, a series of methods of remote sensing for mineral exploration were established.
- Gold-bearing Information Extraction. TM data with plentiful spectral information have capability of identifying mineralization and alteration. Using medium infrared bands and visible bands to do ratio and colour composite image processing on TM data in the Eastern Altai found out the ferritization and gold mineralization; Using KL transformation found out gold mineralized epidotization, which are important contributions of TM of discover fracture zone type of gold deposit in this area. Applying HIS transformation to SPOT data in the western Altai, which is to transform from Red, Green and Blue space to Intensity, Hue and Saturation space and their reverse transformation, extracted quartz veins from middle-acidic intrusions, A lot of veins are gold bearing quartz vein type of gold deposit in this area.
- Integration of Multi-Source Remotely Sensing Data and Integration of Remotely Sensed Data with other Surveying Data. Visible and infrared data of TM and SPOT HRV were integrated with SAR data in study of gold deposit SAR data shows variation of relief; TM data stress the spectral features; SPOT HRV has high special resolution. Integration of SAR TM and SPOT
Data enhanced the geological information of gold mineralization. Mean while, in order to interpret the deep fault associated with Kesa copper deposit remotely sensed data has been integrated with aeromagnetic data and gravity data; image interpretation map has been in targeted with thematic geological map.
- Remote Sensing and Mathematical Geology. It was two types of analysing methods one is to build up mathematical prospective model using remotely sensed data and other surveying data. Another one is to analyse the trend surface of lineament density, which were interpreted from remotely sensed data. In a specified circumstance, lineament density usually strongly relate to gold mineralization. The high Lineament density areas interpreted from trend surface highly correlated to gold mineralization.3
- Geological Data Sets Analysis Supported by GIS-as One of Means for Mineral Exploration. Central Altai was Chosen as a test area. It was very contributive to our broad understanding of gold targets that using remotely sensed, geological, geophysical and geochemical data to extract gold mineralization features, set up DTM and analyse data comprehensively. Which were supported by ARC/INFO and GIST geographic information system software, respectively.
- Special Pattern Analyses of Lineaments. NOAA AVHRR is able to reveal more geological feature of deep subsurface comparing to other remotely sensed data in the study area. It was inferred from special pattern analysis of lineament that the pattern is the inner characteristics of regional structures. The spacial pattern corresponds to sturcture zones of different geological events. Coincides with regional features of graivity field and relates to mineral deposits inherently. Therefore, it has leading function for mineral exploration study.
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