Geo-information identification for exploring non-stationary relationships between volcanic sedimentary Fe mineralization and controlling factors in an area with overburden in eastern Tianshan region, China

GIS-based spatial analysis has been a common practice in mineral exploration, by which mineral potentials can be delineated to support following sequences of exploration. Mineral potential mapping is generally composed of geo-information extraction and integration. Geological anomalies frequently indicate mineralization. Volcanic sedimentary Fe deposits in eastern Tianshan mineral district, China provide an example of such an indication. However, mineral exploration in this area has been impeded by the desert coverage and geo-anomalies indicative to the presence of mineralization are often weak and may not be efficiently identified by traditional exploring methods. Furthermore, geological guidance regarding to spatially non-stationary relationships between Fe mineralization and its controlling factors were not sufficiently concerned in former studies, which limited the application of proper statistics in mineral exploration. In this dissertation, geochemical distributions associated with controlling factors of the Fe mineralization are characterized by various GIS-based spatial analysis methods. The singularity index mapping technique is attempted to separate geochemical anomalies from background, especially in the desert covered areas. Principal component analysis is further used in integrating the geochemical anomalies to identify geo-information of geological bodies or geological activities associated with Fe mineralization. In order to delineate mineral potentials, spatially weighted principal component analysis with more geological guidance is tried to integrate these identified controlling factors. At the end, as the first time been introduced to mineral exploration, a geographically weighted regression method is currently attempted investigate spatially non-stationary interrelationships presented across the space. Based on the results, superimposition of these controlling factors can be qualitatively and quantitatively summarized that provides a constructive geo-information to Fe mineral exploration in this area. From the practices in this dissertation, GIS-based mineral exploration will not only be efficient in mapping mineral potentials but also be supportive to strategies making of following mineral exploration. All of these experiences can be suggested to future mineral exploration in the other regions.