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利用陆地卫星影象象元亮度值为变量,对广东大宝山矿区进行找矿信息统计预测探讨。取Landsat—2(1976.1.11《133—43》韶关幅)MSS_4、MSS_5、MSS_6、MSS_7、以及派生的MSS_5/MSS_4,MSS_6/MSS_4、MSS_7/MSS_4、MSS_6/MSS_5、MSS_7/MSS_5、MSS_7/MSS_6为变量。统计面积达251.64平方公里,划分为2520个单元,每个单元面积为316×316平方米。以铅锌多金属矿床为统计模型,通过对应分析获取与模型关系密切主变量,再将主变量逐一通过趋势面分析,从其残差分量中选出能显著反映模型单元之特征变量,并从其产生的信息中选出合理的信息异常单元14个,其中85.71％所处地质条件很好,对扩大该区本类矿床远景值得优先重视的区段。与地质物化探统计预测该区有利地段相吻合,说明本法对金属矿找矿预测是个有用的方法。
Using the satellite image brightness value of land satellite as a variable, this paper discusses the prospecting statistics of prospecting information in Dabaoshan mining area of Guangdong Province. Landsat-2 (1976.11.11 “133-43” Shaoguan amplitude) MSS_4, MSS_5, MSS_6, MSS_7, and derived MSS_5 / MSS_4, MSS_6 / MSS_4, MSS_7 / MSS_4, MSS_6 / MSS_5, MSS_7 / MSS_5, MSS_7 / MSS_6 For the variable. The statistical area of 251.64 square kilometers, divided into 2520 units, each unit area of 316 × 316 square meters. Taking the lead-zinc polymetallic deposit as the statistical model, the principal variables closely related to the model are obtained through correspondence analysis. Then, the principal variables are analyzed one by one through the trend surface, and the eigenvalues of the model elements are significantly selected from the residual components. In the information generated, 14 reasonable information anomalous units are selected, of which 85.71% are located in well geological conditions, which is of great importance for expanding the prospect of this type of deposit in this area. The geophysical and geophysical prospecting is in good agreement with the favorable area in this area, which shows that this method is a useful method for metallogenic prospecting prediction.