Abstract
As direct prospecting data, geochemical data play an important role in modelling prospect potential. Geochemical element assemblage anomalies are usually reflected by the correlation between elements. Correlation coefficients are computed from the values of two elements, which reflect only the correlation at a global level. Thus, the spatial details of the correlation structure are ignored. In fact, an element combination anomaly often exists in geological backgrounds, such as on a fault zone or within a lithological unit. This anomaly may cause some combination of anomalies that are submerged inside the overall area and thus cannot be effectively extracted. To address this problem, we propose a local correlation coefficient based on spatial neighbourhoods to reflect the global distribution of elements. In this method, the sampling area is first divided into a set of uniform grid cells. A moving window with a size of 3×3 is defined with an integer of 3 to represent the sampling unit. The local correlation in each unit is expressed by the Pearson correlation coefficient. The whole area is scanned by the moving window, which produces a correlation coefficient matrix, and the result is portrayed with a thermal diagram. The local correlation approach was tested on two selected geochemical soil survey sites in Xiao Mountain, Henan Province. The results show that the areas of high correlation are mainly distributed in the fault zone or the known mineral spots. Therefore, the local correlation method is effective in extracting geochemical element combination anomalies.
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This research was supported by the National Natural Science Foundation of China (Nos. 41272359, 210100069). We thank the No. 1 Institute of Geological and Mineral resources survey of Henan for its data support. We also thank Prof. Ren-guang Zuo and Prof. Yongqing Chen for their comments and suggestions. The final publication is available at Springer via https://doi.org/10.1007/s12583-021-1444-9.
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Yu, X., Wang, S., Wang, H. et al. Detection of Geochemical Element Assemblage Anomalies Using a Local Correlation Approach. J. Earth Sci. 32, 408–414 (2021). https://doi.org/10.1007/s12583-021-1444-9
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DOI: https://doi.org/10.1007/s12583-021-1444-9