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Information extraction and integration in mineral exploration.

机译:矿物勘探中的信息提取和集成。

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摘要

Geologic information extraction and integration are the main goals of this study. Tools are designed to aid in exploration for common mineral deposits by intelligently and efficiently processing spatial geological data.;Gabor filters, comprising Gaussian-attenuated sinusoidal weight vectors, are used for textural discrimination. A highly non-linear logic operator was designed for "valley", "ridge", edge, and intersection extraction from multispectral images to cover most of the possible local lineament types. A zonation detector (a non-linear logic operator) indicates the presence or absence of lithologic zonation, the number and the types of zones using a series of automatically expanding moving windows. The ultimate window size represents the zonation size.;Two different types of raster-based expert systems help optimize pixel-by-pixel knowledge extraction and representation over the spatial information and throughout the different raster feature layers. First a 2-D expert system is used for classification, ranking, recognition and searching for important pattern associations in the feature space. Second, a multilayer adaptive raster-based expert system allows the processing of multiple geologic features, and operates over each pattern in the feature layers.;The fuzzy integral method of evidence fusion is used to integrate information from a variety of mineral exploration sources. This nonlinearly combines objective mineral occurrence evidence, in the form of a fuzzy membership function, with subjective evaluation of the worth of the sources with respect to the decision.;An application of these methods to the Tombstone mineral district in southern Arizona demonstrates its ability to pick out circular features from TM imagery, Gabor transforms and lineament patterns, as well as identify favorable zonation for new mineral occurrence. The final product at this time is a probability map to guide the exploration geologist.
机译:地质信息的提取和整合是本研究的主要目标。这些工具旨在通过智能,高效地处理空间地质数据来辅助勘探常见的矿床。Gabor过滤器包括高斯衰减的正弦加权矢量,用于构造判别。设计了一种高度非线性的逻辑运算符,用于从多光谱图像中提取“谷”,“山脊”,边缘和交点,以覆盖大多数可能的局部折线类型。分区检测器(非线性逻辑运算符)使用一系列自动扩展的移动窗口来指示岩性分区的存在与否,区域的数量和类型。最终的窗口大小表示分区大小。两种不同类型的基于栅格的专家系统可帮助优化空间信息以及整个不同栅格要素层的逐像素知识提取和表示。首先,使用二维专家系统对特征空间中的重要模式关联进行分类,排名,识别和搜索。其次,基于多层自适应栅格的专家系统允许处理多个地质特征,并在特征层中的每个模式上进行操作。;证据融合的模糊积分方法用于整合来自各种矿物勘探来源的信息。这将模糊的隶属函数形式的客观矿物发生证据与主观评估有关决策的来源价值进行非线性组合。这些方法在亚利桑那州南部墓碑矿产区的应用证明了其有能力从TM影像,Gabor变换和线条样式中选取圆形特征,并为新矿物的出现确定有利的分区。这时的最终产品是一个指导勘探地质学家的概率图。

著录项

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Geology.;Computer Science.;Engineering Mining.
  • 学位 Ph.D.
  • 年度 1992
  • 页码 219 p.
  • 总页数 219
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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