Enhanced Gold Prospectivity Mapping in Mauritania: A Case Study by Farmonaut (2020-2025)

Executive Summary

Farmonaut, a leader in satellite-based agricultural and geospatial analytics, has successfully completed a groundbreaking remote sensing project for a gold mining client in Mauritania. Covering a 95-square-kilometer Area of Interest (AOI) from 2020 to 2025, this study leverages advanced multispectral and temporal satellite analysis to identify high-potential gold exploration targets. By integrating cutting-edge methodologies such as Gold Potential Index (GPI) modeling, spectral analysis, and anomaly characterization, Farmonaut delivered a prioritized list of exploration targets, significantly reducing the cost and risk associated with traditional fieldwork. This case study explores the objectives, methodologies, results, and implications of this project, showcasing Farmonaut’s expertise in remote sensing for mineral exploration.

Project Objective

The primary goal was to utilize satellite remote sensing to systematically identify, characterize, and rank high-potential gold exploration targets within the AOI. By mapping hydrothermal alteration zones and applying a robust GPI model, Farmonaut aimed to guide cost-effective and efficient field investigations, optimizing the client’s gold exploration strategy in Mauritania’s mineral-rich West African Craton.

Introduction

Project Background and Objectives

Gold exploration is a high-stakes, capital-intensive process, particularly in remote regions like Mauritania. Traditional methods, reliant on extensive ground surveys, are time-consuming and costly, often yielding uncertain results. Farmonaut’s innovative approach harnesses satellite remote sensing to provide a non-invasive, scalable solution for mineral exploration. By analyzing multispectral satellite data, this project identifies spectral signatures of minerals associated with gold deposits, such as phyllic, argillic, propylitic, and iron oxide alterations. These pathfinder minerals help pinpoint hydrothermal alteration zones, narrowing the search for economically viable gold deposits.

The objectives of the study were:

1. Process and analyze a four-year time-series of satellite imagery (2020–2025) to map mineral alteration assemblages.
2. Develop a multi-component Gold Potential Index (GPI) integrating seasonal and temporal data for enhanced reliability.
3. Identify and rank high-potential gold exploration targets to guide field investigations.
4. Deliver actionable prospectivity maps and coordinates for prioritized anomalies.

This approach aligns with industry trends toward data-driven exploration, leveraging remote sensing to optimize resource allocation and minimize environmental impact.

Study Area (Area of Interest – AOI)

The study focused on a 95-square-kilometer AOI in Mauritania, located within the mineral-rich West African Craton. Known for significant gold endowments, this region features arid to semi-arid conditions with sparse vegetation, ideal for remote sensing analysis. The AOI’s geological setting, characterized by structural controls like faults and shear zones, makes it a prime target for gold mineralization. Farmonaut’s analysis capitalized on these conditions to map surface geology and mineral signatures effectively.

Data Sources

The project utilized a combination of high-quality satellite and topographic datasets:

• Satellite Imagery: Landsat 8 OLI and Landsat 9 OLI-2, using Collection 2, Level-2 Surface Reflectance products. These datasets, with 30-meter spatial resolution, are radiometrically calibrated and atmospherically corrected, enabling precise spectral analysis. Imagery spanned January 1, 2020, to June 30, 2025, ensuring robust temporal coverage.
• Digital Elevation Model (DEM): The Shuttle Radar Topography Mission (SRTM) Global 1 arc-second dataset provided 30-meter resolution topographic data. Elevation and slope metrics were used to filter anomalies and exclude unsuitable terrain.

These datasets enabled Farmonaut to build a comprehensive analytical framework for gold prospectivity mapping.

Methodology

Farmonaut employed a five-stage methodology to deliver high-confidence gold exploration targets, combining advanced remote sensing techniques with rigorous data processing. This approach ensured repeatability, scalability, and accuracy in identifying mineralized zones.

Data Pre-Processing

The analysis began with the acquisition of 182 cloud-free Landsat 8/9 images from 2020 to 2025. These images were processed to generate seasonal, annual, and overall composites using median pixel values. Composites were created for dry (November–May) and wet (June–October) seasons to capture temporal trends and minimize noise from seasonal variations, such as vegetation or soil moisture changes.

Spectral Analysis

Spectral analysis targeted hydrothermal alteration minerals associated with gold deposits. Farmonaut calculated key indices to enhance mineralogical signatures:

• Phyllic Alteration: Associated with muscovite and sericite, indicating potential gold-bearing systems.
• Argillic Alteration: Linked to clay minerals, a common pathfinder for epithermal gold deposits.
• Propylitic Alteration: Indicative of chlorite and epidote, often peripheral to gold systems.
• Iron Oxide Alteration: Highlights hematite and goethite, key indicators of mineralization.
• Silicification: Identifies silica-rich zones, often associated with gold-bearing veins.

These indices were derived from multispectral bands, leveraging Landsat’s sensitivity to mineral signatures.

Gold Potential Index (GPI) Modeling

Farmonaut developed a multi-component GPI to integrate spectral indices and temporal stability. Seasonal GPIs were created using weighted overlays of alteration indices, with dry season data weighted at 60% and wet season at 40% to account for environmental variability. A Temporal Stability metric, based on the Coefficient of Variation, prioritized persistent signals, filtering out transient features like seasonal vegetation or soil moisture. The final GPI combined seasonal data and temporal stability to produce a robust prospectivity score.

Target Identification

High-potential targets were identified by flagging anomalies exceeding the 80th percentile on the GPI map. These anomalies were refined using terrain and land cover masks, including:

• NDVI (Normalized Difference Vegetation Index): To exclude vegetated areas.
• NDWI (Normalized Difference Water Index): To eliminate water bodies.
• Slope and Elevation: To filter out topographically unsuitable areas, such as steep slopes or low-lying regions.

This process ensured that only geologically plausible anomalies were prioritized.

Anomaly Characterization

Raster anomalies were converted into polygons and ranked using a custom scoring system. The score integrated:

• Alteration Intensity: Average GPI value within the anomaly.
• Physical Size: Area of the anomaly in hectares.
• Temporal Stability: Consistency of the signal across seasons and years.
• Seasonal Contrast: Clarity of the signal between wet and dry seasons.

This multi-criteria approach produced a prioritized list of high-confidence exploration targets, optimized for field validation.

Results

Farmonaut’s methodology delivered clear, actionable results, including prospectivity maps and a ranked table of gold anomalies, empowering the client to focus exploration efforts effectively.

Prospectivity Maps

The study produced two key visual outputs:

• Final Gold Anomaly Map: This map displays prioritized anomaly polygons overlaid on a true-color satellite composite of the AOI. These polygons represent the most promising targets, having passed spectral, temporal, and terrain-based filters. The map provides a clear spatial context for field planning.
• Combined Gold Potential Index (GPI) Heatmap: This heatmap illustrates prospectivity scores across the AOI, with “hotter” colors (red, orange) indicating higher potential and “cooler” colors (blue, green) lower potential. The heatmap highlights regional geological trends, aiding in the interpretation of anomaly distribution.

Table of Coordinates of Major Gold Anomalies

The study identified 12 high-priority anomalies, each characterized by size, GPI score, and geographic coordinates. These targets were ranked based on the custom scoring system, ensuring that exploration efforts focus on the most promising sites. The table provides precise coordinates for field teams to locate and validate anomalies efficiently.

Discussion

Interpretation of Results

The distribution of anomalies within the AOI suggests a strong structural control on gold mineralization, likely associated with regional faults or shear zones. These geological features are common conduits for gold-bearing hydrothermal fluids, increasing the confidence in the identified targets. The alignment of anomalies with known geological structures in the West African Craton further validates the results, positioning the client for successful follow-up exploration.

The GPI heatmap revealed regional trends, with high-potential zones concentrated in areas with favorable geology. The use of temporal stability metrics ensured that only persistent, geologically significant signals were prioritized, reducing false positives caused by seasonal or environmental noise.

Strengths of the Methodology

Farmonaut’s methodology offers several advantages over traditional exploration approaches:

• Temporal Analysis: By analyzing a multi-year time-series and comparing wet and dry season composites, the model filters out transient features like vegetation or soil moisture. The Temporal Stability metric ensures that only geologically relevant signals are prioritized, enhancing target reliability.
• Enhanced Prioritization Score: The custom scoring system integrates alteration intensity, anomaly size, temporal stability, and seasonal contrast. This holistic approach produces a commercially actionable ranking, allowing the client to focus on targets with the optimal combination of characteristics.
• Cost-Effectiveness: Remote sensing reduces the need for extensive fieldwork, saving time and resources while covering large areas efficiently.
• Scalability: The methodology can be applied to other regions or minerals, making it a versatile tool for mineral exploration globally.

These innovations position Farmonaut as a leader in satellite-based mineral exploration, delivering high-value insights with minimal environmental impact.

GEOJSON of Significant Gold Potential Locations

Farmonaut provided a GEOJSON file containing the coordinates and attributes of significant gold potential locations. This file enables seamless integration with GIS platforms, allowing the client to visualize and analyze anomalies in their preferred software. The GEOJSON format ensures compatibility and ease of use for field planning and validation.

Conclusion

Farmonaut’s gold prospectivity mapping project in Mauritania demonstrates the power of satellite remote sensing in modern mineral exploration. By leveraging multispectral and temporal analysis, Farmonaut identified and prioritized high-potential gold exploration targets, delivering actionable insights to the client. The methodology’s reliance on robust data processing, advanced GPI modeling, and multi-criteria ranking ensures high-confidence results, reducing the risks and costs of traditional exploration. This case study underscores Farmonaut’s expertise in geospatial analytics and its ability to drive innovation in the mining industry.

For more information on Farmonaut’s remote sensing solutions, visit farmonaut.com.