A Remote Sensing-Based Application of Bayesian Networks for Epithermal Gold Potential Mapping in Ahar-Arasbaran Area, NW Iran

Abbas Maghsoudi,Hamid Reza Ramazi,Ghahraman Sohrabi,Amin Beiranvand Pour,Seyed Mohammad Bolouki

doi:10.3390/rs12010105

Abstract

Mapping hydrothermal alteration minerals using multispectral remote sensing satellite imagery provides vital information for the exploration of porphyry and epithermal ore mineralizations. The Ahar-Arasbaran region, NW Iran, contains a variety of porphyry, skarn and epithermal ore deposits. Gold mineralization occurs in the form of epithermal veins and veinlets, which is associated with hydrothermal alteration zones. Thus, the identification of hydrothermal alteration zones is one of the key indicators for targeting new prospective zones of epithermal gold mineralization in the Ahar-Arasbaran region. In this study, Landsat Enhanced Thematic Mapper+ (Landsat-7 ETM+), Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing datasets were processed to detect hydrothermal alteration zones associated with epithermal gold mineralization in the Ahar-Arasbaran region. Band ratio techniques and principal component analysis (PCA) were applied on Landsat-7 ETM+ and Landsat-8 data to map hydrothermal alteration zones. Advanced argillic, argillic-phyllic, propylitic and hydrous silica alteration zones were detected and discriminated by implementing band ratio, relative absorption band depth (RBD) and selective PCA to ASTER data. Subsequently, the Bayesian network classifier was used to synthesize the thematic layers of hydrothermal alteration zones. A mineral potential map was generated by the Bayesian network classifier, which shows several new prospective zones of epithermal gold mineralization in the Ahar-Arasbaran region. Besides, comprehensive field surveying and laboratory analysis were conducted to verify the remote sensing results and mineral potential map produced by the Bayesian network classifier. A good rate of agreement with field and laboratory data is achieved for remote sensing results and consequential mineral potential map. It is recommended that the Bayesian network classifier can be broadly used as a valuable model for fusing multi-sensor remote sensing results to generate mineral potential map for reconnaissance stages of epithermal gold exploration in the Ahar-Arasbaran region and other analogous metallogenic provinces around the world.

Highlights

Hydrothermal alteration minerals such as iron oxide/hydroxides, Al-OH, Fe,Mg-OH, S-O, Si-OH and carbonate minerals show indicative spectral absorption signatures in the visible near-infrared (VNIR) and the shortwave infrared (SWIR) regions [1,2,3,4,5]
The mineral potential map produced in this study using multi-sensor remote sensing imagery and Bayesian network model is viable and can be broadly applicable for epithermal gold exploration in the Ahar-Arasbaran region. This investigation was accomplished to produce a mineral potential map for prospecting epithermal gold mineralization in the Ahar-Arasbaran region, NW Iran using multi-sensor remote sensing satellite imagery (e.g., Landsat-7 ETM+, Landsat-8 and ASTER) and the Bayesian network model
Iron oxide/hydroxide zones, hydroxyl-bearing minerals and carbonates zones, advanced argillic, argillic-phyllic, propylitic and silicified alteration zones were mapped in the Ahar-Arasbaran region using band ratio, relative absorption band depth (RBD) and selective principal component analysis (PCA) image processing techniques

Summary

Introduction

Hydrothermal alteration minerals such as iron oxide/hydroxides, Al-OH, Fe,Mg-OH, S-O, Si-OH and carbonate minerals show indicative spectral absorption signatures in the visible near-infrared (VNIR) and the shortwave infrared (SWIR) regions [1,2,3,4,5]. The VNIR spectral bands of Landsat-7 ETM+ were utilized to map iron oxides/hydroxide minerals (gossan), while, SWIR spectral bands were used to detect hydroxyl-bearing minerals and carbonates [21,22,23,24]. Band ratio of 5/7 is sensitive to hydroxyl-bearing minerals and carbonates because of reflectance features in band 5 (1.55–1.75 μm) and strong absorption in band 7 (2.09–2.35 μm) [23,25,26,27]. Equivalent bands of Landsat-8, bands 2 and 4 responsive to iron oxides/hydroxides and bands 6 and 7 sensitive to hydroxyl-bearing minerals and carbonates, were extensively used for hydrothermal alteration mineral mapping in metallogenic provinces [12,16,18,19,28]. Discrimination of particular alteration zones and minerals (i.e., argillic, phyllic propylitic zones and muscovite, chlorite and kaolinite) using Landsat-7 ETM+ and Landsat-8 VNIR and SWIR spectral bands is challenging due to position, number and the broad extent of the bands [28,29]

Results

Discussion

Conclusion