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Multi - source geospatial data mining methods and applications

Author: CuiYing
Tutor: HeBinBin
School: University of Electronic Science and Technology
Course: Cartography and Geographic Information Engineering
Keywords: geological spatial data mining uncertainty metallogenic association rules evidence theory regional mineral resources potential prediction
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 84
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Abstract


Nowadays earth observing technology develop rapidly, but processing software for remote sensing and GIS spatial data still has shortcomings. Contradictions between the massive spatial data and the acquisition of useful knowledge result in‘an explosion of spatial data, but lack of knowledge’. However, spatial data mining technology can solve the problems above, which has become the leading research direction of space information field in recent years. Currently, spatial data mining mainly focused on algorithm, but lack of application and practice for professional fields. Potential prediction of regional mineral resources is the most promising in the applications of spatial data mining. In present, mineral resource is short, and exploration cost and the exploration difficulty also increase intensely. It is particularly important and urgent to make full use of the massive geological spatial data to mine prospecting information with uncertainty in the deep-level. Establishing a rapid, efficient, intelligent prediction method of mineral resource potential could reduce the cost of mineral exploration and improve the efficiency and accuracy of mineral prediction further.For the demand of regional mineral resources potential forecasting, spatial data mining method and the uncertainty of geological spatial data will be integrated closely, and the multi-source geology spatial data mining methods were studied in the paper. A geological spatial data mining prototype system was designed and realized. Finally, this paper conducted detailed demonstration with the typical metallogenic belt in western China - Qinghai Kunlun metallogenic belt. The main work and achievements including:(1) Based on the analysis processes and analysis methods of spatial data mining, integrating the characteristics of geological spatial data and demand of mineral resources potential forecast applications, a multi-source geospatial data mining theory and technology framework was built.(2) On the base of Apriori algorithm and the cloud model, a method of mining association rules in mineral resource potential prediction, especially for the regional metallogenic prediction, was established. Confidence, support, lift, coverage, leverage, interesting and the number of conditions were used in the uncertainty evaluation of rules. Based on above all, a comprehensive evaluation was built and the spatial knowledge also was visualized.(3) The traditional spatial data mining methods are lack of capacity for the uncertainty expression. In the paper, evidence theory was used in multi-source geospatial data mining and the uncertainty expression.(4) A multi-source geospatial data mining prototype system was designed and realized based on the geological spatial data mining methods. This system provides software analysis tools for regional mineral resource potential prediction.(5) Finally, the multi-source geospatial data mining prototype system was used in the typical metallogenic belt in western China - Qinghai Kunlun metallogenic belt. The system was used in the region iron ore, copper lead zinc polymetallic ore and gold ore resources potential predict. The results could provide effective, accurate reference and decision-making information for mineral resources exploration in the region.

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