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本文以红外细分波段新疆铁木尔特航带为例,依据不同地质体各自的光谱特征,运用主成分分析、多种信息复合等技术与综合分析方法,使该地段的矿化特征提取收到了良好效果。 本航带的矿化特征信息在图像处理结果中表现为黄色异常色调。它反映了当地多金属成矿带中二氧化硅含量低、全铁含量较高的岩矿矿化特征。团块状黄色异常色调表示出地表出露的铁帽、磁铁矿化和矽卡岩化的分布状况。野外验证表明,黄色调的分布地域与实地的地表矿化范围相吻合。 遥感特征信息提取的综合分析方法包括信息基本特征分析、图像处理、后验分析和机理解释等四个相互联系的步骤。研究表明,只有经过综合分析,才能揭示出特征信息的内在规律性,使特征信息具有较好的实用价值。
Taking the infrared sub-band Tymmuart Belt as an example, based on the spectral features of different geologic bodies, the authors use the principal component analysis, multiple information composite techniques and comprehensive analysis methods to extract the mineralization characteristics of this area To good effect. The mineralization characteristic information of this navigation band appears as anomalous yellow color in the image processing result. It reflects the local mineralization of polymetallic metallogenic belt with low silica content and high total iron content. Unbalanced yellow anomalies indicate the distribution of exposed iron caps, magnetite and skarnization on the surface. Field verification shows that the distribution of the yellow tone is consistent with the surface mineralization range of the field. The comprehensive analysis method of remote sensing feature information extraction includes four interrelated steps of information basic feature analysis, image processing, posteriori analysis and mechanism interpretation. The research shows that only through the comprehensive analysis can reveal the intrinsic regularity of feature information, so that the feature information has good practical value.