SPATIAL CLUSTER AND OUTLIER IDENTIFICATION OF GEOCHEMICAL ASSOCIATION OF ELEMENTS: A CASE STUDY IN JUIRUI COPPER MINING AREA

Indexed In

Volume 153 / 2016

Authors:

Thanh NGUYEN TİEN, Tuyen VU DANH, Hung TRİNH LE HUNG, Hang NGUYEN THİ LE HANG

Keywords:

Spatial Outliers, Spatial Clusters, Spatial Variability, Local Moran Statistic, Geochemistry

Abstract:

Spatial clusters and spatial outliers play an important role in the study of the spatial distribution patterns of geochemical data. They characterize the fundamental properties of mineralization processes, the spatial distribution of mineral deposits, and ore element concentrations in mineral districts. In this study, a new method for the study of spatial distribution patterns of multivariate data is proposed based on a combination of robust Mahalanobis distance and local Moran’s Ii. In order to construct the spatial matrix, the Moran’s I spatial correlogram was first used to determine the range. The robust Mahalanobis distances were then computed for an association of elements. Finally, local Moran’s Ii statistics was used to measure the degree of spatial association and discover the spatial distribution patterns of associations of Cu, Au, Mo, Ag, Pb, Zn, As, and Sb elements including spatial clusters and spatial outliers. Spatial patterns were analyzed at six different spatial scales (2km, 4 km, 6 km, 8 km, 10 km and 12 km) for both the raw data and Box-Cox transformed data. The results show that identified spatial cluster and spatial outlier areas using local Moran’s Ii and the robust Mahalanobis accord the objective reality and have a good conformity with known deposits in the study area.

DOI:

http://dx.doi.org/10.19076/mta.61513