Comparison of Exploratory Data Analysis (EDA) and Median Absolute Deviation (MAD) in order to identify geochemical anomaly and mineralization potential areas (Case Study: Hanza district, southern of Urrmia–Dokhtar metallogenic belt)
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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Summary
In this study, two methods of Exploratory Data Analysis (EDA) and Median Absolute Deviation (MAD) are used for determining the threshold. In the EDA technique, outlier values are considered as anomalies and eII is high. In type I error (eI), samples with background values are accepted as anomaly; and in type II error (eII), samples with anomalous values are accepted as background. In fact, EDA method is inefficient for identifying anomalies with low contrast. This paper introduces MAD method to reduce eII for thresholds estimation.
Introduction
Today EDA method is commonly used for threshold calculation and anomalies separation. In the EDA method, determination of threshold performs based on selection of fixed classes in box plot and is defined as Q3+1.5×(Q3-Q1). The third (Q3) and the first (Q1) quartiles are considered as 75% and 25% frequency, respectively. In the MAD method, estimation of thresholds performs based on median and median absolute deviation (MAD) and is defined as Q2+2×(MAD).
Methodology and Approaches
In order to compare EDA and MAD methods, the dot histogram was used and position of threshold of the two methods was displayed on the histogram. In the study area, there are six known PCDs. In order to compare the ability of EDA and MAD methods in identifying PCDs, copper and molybdenum maps were prepared by the two methods. Remote sensing data was used to demonstrate the importance of the anomaly regions that were identified by MAD. Key minerals of argillic and phyllic alterations were identified by valid remote sensing techniques based on the spectral characteristics. These techniques include False-color composite (FCC) and band ratio (BR) based on Relative Band Depth (RBD).
Results and Conclusions
The threshold of EDA is located in the end tail of dot histogram therefore by this method, just outlier values are identified as anomaly. The threshold of MAD method has a desirable position on the dot histogram. According to the investigation of copper and molybdenum maps, only three PCDs were identified by EDA while by MAD, all PCDs were identified. Also by MAD, eight new anomalous areas were detected. Satellite images processing has shown extensive distribution of hydrothermal alteration associated with porphyry systems in the eight new anomalous areas. These new anomalous areas have not been recognized by EDA and this method is inefficient for identifying geochemical anomalies. The MAD method is more suitable for identifying geochemical anomalous areas. this method detected 11 more areas (three PCDs and 8 new anomaly) than EDA method.
Language:
Persian
Published:
Journal of Aalytical and Numerical Methods in Mining Engineering, Volume:9 Issue: 18, 2019
Pages:
89 to 101
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