Shahrestani, Shahed, Sanislav, Ioan, and Fereydooni, Hosein (2025) Rotation-based outlier detection for geochemical anomaly identification in stream sediment multivariate data. Earth Science Informatics, 18 (296).

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Abstract

This research explores the use of the rotation-based outlier detection (ROD) method for identifying geochemical anomalies in a multivariate stream sediment dataset from Iran, targeting porphyry and vein-type Cu mineralization. Geochemical datasets often present challenges for outlier detection methods like local outlier factor (LOF) and k-nearest neighbor (KNN), which rely on distance or density metrics and require parameter tuning (e.g., neighborhood size k). High-dimensional feature spaces further complicate their application. ROD, in contrast, offers a parameter-free, rotation-based approach that effectively analyzes geometric relationships between samples in subspaces, mitigating the curse of dimensionality. This makes ROD particularly suited to high-dimensional geochemical datasets, where complex relationships between elements (due to lithology or mineralization) are critical for identifying anomalies. This study compares ROD with LOF and KNN using two subsets of geochemical variables (Ag, As, Au, Bi, Co, Cr, Cu, Mo, Ni, Pb, Sb, Zn; and Ag, As, Au, Cu, Mo, Sb) and evaluates its performance based on the receiver operating characteristic (ROC) analysis and the number of known mineral occurrences detected in anomaly class. ROD outperforms LOF and KNN, capturing 78% (14 out of 18) of known Cu-bearing mineral occurrences. Moreover, ROD shows better conformity between 10% of highest outlier scores and Cu-mineralization sites. Rotation cost function in ROD, evaluated using the median absolute deviation (MAD), enhances its ability to detect outliers by focusing on orientation rather than distance, and by reducing noise misclassification. In addition, the parameter-free design of ROD and improved handling of high-dimensional data makes it a promising tool for geochemical exploration, as it captures unique mineralization-related signals that might be missed by traditional methods.

Item ID:	84772
Item Type:	Article (Research - C1)
ISSN:	1865-0481
Copyright Information:	© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Date Deposited:	28 Feb 2025 00:34
FoR Codes:	37 EARTH SCIENCES > 3703 Geochemistry > 370301 Exploration geochemistry @ 50% 37 EARTH SCIENCES > 3704 Geoinformatics > 370402 Earth and space science informatics @ 30% 37 EARTH SCIENCES > 3705 Geology > 370508 Resource geoscience @ 20%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280107 Expanding knowledge in the earth sciences @ 100%
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