Utilizing Remote Sensing and Satellite-Based Bouguer Gravity Data to Predict Potential Sites of Hydrothermal Minerals and Gold Deposits in Central Saudi Arabia

Faculty Science Year: 2023
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Minerals MDPI Volume:
Keywords : Utilizing Remote Sensing , Satellite-Based Bouguer Gravity Data    
Abstract:
This article aims to aid in exploring and forecasting hydrothermal minerals and gold deposits in Central Saudi Arabia (SA), with a focus on structural contexts. Remote sensing (RS) and satellite-based Bouguer gravity (SBG) data were integrated in order to create a mineral prediction map for the researched location. Data from the Landsat Operational Land Imager (OLI) and Shuttle Radar Topography Mission (SRTM) were transformed and enhanced using a variety of approaches. The delineation of hydrothermal alteration zones (HAZs) and highlighting of structural discontinuities in the OLI data were made possible using band ratios and oriented principal component analysis (PCA). Additionally, the underlying structural features were successfully exposed by processing the SBG using a variety of edge detection techniques, like the analytical signal (AS), total horizontal derivative (THD), tilt angle (TA), horizontal tilt angle (TDX), theta map (TM), horizontal derivative of the tilt derivative (HD_TDR), horizontal gradient of the tilt angle (HGTA), tilt angle of the analytical signal (TAAS), and soft sign function (SF). As a result, more prominent lineaments were found in the NW–SE, NNW–SSE, NE–SW, and NNE–SSW directions than in the N–S and E– W directions. The GIS incorporated surface/subsurface geological structure density maps with zones of hydrothermal alteration. It was found that the lineaments derived from the analysis of the RS and SBG data were more in line with the HAZs, which demonstrated the common connection between alteration zones and deep lineaments. The findings revealed a mineral prediction map with extremely low to extremely high probabilities. Overall, combining RS and SBG data effectively identified probable mineralization sites associated with hydrothermal processes and made it easier to create this study’s final predictive mineralization map.
   
     
 
       

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