3. 2D Quantitative Prediction Method of Mineral Resources

This chapter delves into the systematic principles and methodologies for 2D prediction and evaluation of mineral resources using GIS platforms. It begins with data collection and preprocessing, which involves gathering geological, geophysical, geochemical, remote sensing geological, and mineral data. The chapter then focuses on establishing prospecting models, quantifying and transforming digital models, and analyzing metallogenic geological conditions. Key methodologies include the analysis and extraction of metallogenic geological conditions, as well as the implementation of positional, quantitative assessment, and fixed-probability prediction. The chapter also discusses the establishment of a GIS Data Database, addressing challenges related to data integration, scale harmonization, and positional methods. It highlights the use of big data technology for enhanced data services and the application of mathematical models like Weights of Evidence for synthesizing multivariate geological prospecting information. The chapter concludes with a comprehensive analysis of metallogenic information and the division of prediction units, providing a robust framework for accurate mineral resource prediction and evaluation.