地球化学的空间自相关异常信息提取方法

发布时间：2018-04-22 01:09

本文选题：地球化学异常 + 局部空间自相关　；参考：《测绘科学》2017年08期

【摘要】：针对地球化学数据存在的空间分布相关性特征,该文提出了一种基于空间自相关统计的地球化学异常提取方法。以内蒙古浩布高矿床外围的土壤地球化学数据为例,通过对Sn、Cu元素地球化学数据在不同空间间隔上的全局自相关计算,测算其空间聚集的程度,选取聚集程度最高时的间隔距离作为局部空间自相关的参数,通过局部Moran’s I值研究元素的空间分布特征,分析空间聚类和异常值,从而提取地球化学异常。结果表明,局部空间自相关分析可以揭示Sn、Cu地球化学数据的空间分布特征,能够更好地提取地球化学弱缓异常,说明空间自相关是一种有效的地球化学异常识别方法。
[Abstract]:In view of the spatial distribution correlation characteristics of geochemical data, a method of geochemical anomaly extraction based on spatial autocorrelation statistics is proposed in this paper. Taking the soil geochemistry data from the periphery of the Haobugao deposit in Inner Mongolia as an example, the degree of spatial accumulation is calculated by calculating the global autocorrelation of the geochemistry data of Snnn Cu in different spatial intervals. The interval distance of the highest degree of aggregation is chosen as the autocorrelation parameter of local space. The spatial distribution characteristics of elements are studied by the local Moran's I value and the spatial clustering and outliers are analyzed to extract geochemical anomalies. The results show that the local spatial autocorrelation analysis can reveal the spatial distribution characteristics of Sn-Cu geochemical data, and can better extract the weak and slow geochemical anomalies, which indicates that spatial autocorrelation is an effective method for identifying geochemical anomalies.
【作者单位】：合肥工业大学资源与环境工程学院;
【基金】：中国地质调查局地质调查工作项目(12120115033801) 中央高校基本科研业务费专项(2013HGQC0024)
【分类号】：P632

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