Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Geochemical Association Rules of Elements Mined using Clustered Events of Spatial Auto-correlation: A Case Study in the Chahanwusu River Area, Qinghai Province, China

Version 1 : Received: 20 January 2022 / Approved: 21 January 2022 / Online: 21 January 2022 (13:42:44 CET)

A peer-reviewed article of this Preprint also exists.

Zhang, B.; Jiang, Z.; Chen, Y.; Cheng, N.; Khan, U.; Deng, J. Geochemical Association Rules of Elements Mined Using Clustered Events of Spatial Autocorrelation: A Case Study in the Chahanwusu River Area, Qinghai Province, China. Appl. Sci. 2022, 12, 2247. Zhang, B.; Jiang, Z.; Chen, Y.; Cheng, N.; Khan, U.; Deng, J. Geochemical Association Rules of Elements Mined Using Clustered Events of Spatial Autocorrelation: A Case Study in the Chahanwusu River Area, Qinghai Province, China. Appl. Sci. 2022, 12, 2247.

Journal reference: Appl. Sci. 2022, 12, 2247
DOI: 10.3390/app12042247

Abstract

The spatial distribution of elements can be regarded as a numerical field of concentration values with a continuous spatial coverage. An active area of research is to discover geologically meaningful relationships among elements from their spatial distribution. To solve this problem, we propose an association rule mining method based on clustered events of spatial auto-correlation and applied it to the polymetallic deposits of the Chahanwusu River area, Qinghai Province, China. The elemental data for stream sediments were first clustered into HH (high-high), LL (low-low), HL (high-low), and LH (low-high) groups by using local Moran’s I clustering map (LMIC). Then the Apriori algorithm was used to mine the association rules among different elements in these clusters. More than 86% of the mined rule points are located within 1000 m of faults and near known ore occurrences, and occur in the upper reaches of the stream and catchment areas. In addition, we found that the Indosinian granodiorite is enriched in sulfophile elements, e.g., Zn, Ag and Cd, and the Variscan granite quartz diorite (P1γδο) coexists with Cu and associated elements. Therefore, the proposed algorithm is an effective method for mining co-existence patterns of elements and provides an insight into their enrichment mechanisms.

Keywords

Concentration field; Spatial auto-correlation; Association rules; Apriori algorithm; Element co-occurrence

Subject

EARTH SCIENCES, Geoinformatics

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