We are proud to share that Hemayatullah Ahmadi, recently co-authored a new research study. His work, titled “High-Resolution UAV-Based Fuzzy Logic Mapping of Iron Oxide Alteration for Porphyry Copper Exploration: A Case Study from the Kyzylkiya Copper Prospect in Eastern Kazakhstan,” advances the use of drone-acquired multispectral imagery combined with fuzzy logic modeling to enhance mineral exploration. You can read the full abstract and access the publication below.

Abstract

Detecting surface mineral indicators with high spatial precision remains a significant challenge in mineral exploration, particularly in remote or geologically complex regions such as Eastern Kazakhstan. This study addresses this challenge by integrating high-resolution multispectral imagery from Unmanned Aerial Vehicles (UAVs) to map iron oxide distributions, key indicators of ore mineralization such as copper porphyry at the Kyzylkiya mining site in Eastern Kazakhstan. The novelty of this study is the development of a statistical fuzzy logic model that integrates UAV-derived spectral indices, including the Normalized Difference Vegetation Index (NDVI) and targeted band ratios, to generate probabilistic maps of iron oxide presence at a fine spatial resolution of 5.29 cm. This approach enhances prediction accuracy by incorporating uncertainty and variability in spectral responses. The model’s output was validated through a multi-stage process involving independent multispectral datasets and ground-truth sampling, achieving an overall accuracy of 80%. The results reveal concentrated iron oxide anomalies in the northeast and northwest of the study area, underscoring the method’s effectiveness. This integrated UAV-fuzzy logic framework demonstrates a scalable and cost-effective solution for early-stage mineral exploration and can be adapted to similar geological settings globally.

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We are proud to share that Hemayatullah Ahmadi, a valued member of our team, recently had another research study published. His work, titled "Integrated Prospectivity Mapping for Copper Mineralization in the Koldar Massif, Kazakhstan," explores innovative methods for identifying copper-rich zones through a combination of satellite imagery and geophysical data. You can read the full abstract and access the publication below.

Abstract

This study developed a copper mineral prospectivity map for the Koldar massif, Kazakhstan, using an integrated approach combining geophysical and satellite methods. A strong spatialgenetic link was identified between faults and hydrothermal mineralization, with faults acting as key conduits for ore-bearing fluids. Lineament analysis and density mapping confirmed the high permeability of the Koldar massif, indicating its structural prospectivity. Hyperspectral and multispectral data (ASTER, PRISMA, WorldView-3) were applied for detailed mapping of hydrothermal alteration (phyllic, propylitic, argillic zones), which are critical for discovering porphyry copper deposits. In particular, WorldView-3 imagery facilitated the identification of new prospective zones. The transformation of magnetic and gravity data successfully delineated geological features and structural boundaries, confirming the fractured nature of the massif, a key structural factor for mineralization. The resulting map of prospective zones, created by normalizing and integrating four evidential layers (lineament density, PRISMA-derived hydrothermal alteration, magnetic, and gravity anomalies), is thoroughly validated, successfully outlining the known Aktogay, Aidarly, and Kyzylkiya deposits. Furthermore, new, previously underestimated prospective areas were identified. This work fills a significant knowledge gap concerning the Koldar massif, which had not been extensively studied using satellite methods previously. The key advantage of this research lies in its comprehensive approach and the successful application of high-quality hyperspectral imagery for mapping new prospective zones, offering a cost-effective and efficient alternative to traditional ground-based investigations.

Read the publication for free here: Integrated Prospectivity Mapping for Copper Mineralization in the Koldar Massif, Kazakhstan

We are proud to share that Hemayatullah Ahmadi, a valued member of our team, recently had a new research study published. His work, titled "Mapping potential zones of Lithium-bearing pegmatites using ASTER and Sentinel-2 remote sensing imagery in the Tagablor Pegmatite Field, Central Afghanistan". You can read the full abstract and access the publication below.

Abstract

The demand for critical minerals is increasing swiftly as they are essential components for clean energy technologies. Nowadays, lithium (Li) is considered critical due to its wider use in various battery chemistries and the rapid growth of the electric vehicle industry. Pegmatites are considered one of the main sources of lithium worldwide. The pegmatite belt in Afghanistan, known for its enormous resources of critical metals, has recently emerged as an important region for lithium exploration. Multispectral remote sensing imagery is the only technique with large spatial coverage to map lithium-bearing pegmatites on a regional scale. In this study, ASTER and Sentinel 2MSI multispectral remote sensing imagery was used to map lithium-bearing pegmatites in the Tagablor pegmatite field in central Afghanistan. Various spectral mapping methods such as False Color Composite (FCC), Band Ratio (BR) and Spectral Angle Mapper (SAM) as well as supervised classification algorithms, i.e. Support Vector Machine (SVM), Minimum Distance (MD) and Maximum Likelihood (ML), were used to discriminate between altered minerals and lithologies as well as to identify areas with high potential for lithium-bearing pegmatites. Of the classification algorithms tested, SVM showed the highest efficiency in separating pegmatite bodies from their host rocks when applied to Sentinel 2 MSI data. The current study identified six promising pegmatite zones in the Tagablor pegmatite field, five of which were newly discovered and proposed for a comprehensive field campaign. In this study, an overall accuracy of 89 % was achieved in the detection of pegmatites and their surrounding formations, highlighting the potential of multispectral remote sensing for lithium exploration at a regional scale in arid and semi-arid regions. Further geochronological, geochemical and mineralogical investigations are recommended to better understand the age and mineralization potential of these pegmatites in the Tagablor pegmatite field, central Afghanistan. This study highlights the significant potential of multispectral remote sensing in mapping potential zones of critical minerals to enhance the sustainable utilization of minerals for green energy technologies in the future.

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Read the article for free here: Mapping potential zones of Lithium-bearing pegmatites using ASTER and Sentinel-2 remote sensing imagery in the Tagablor Pegmatite Field, Central Afghanistan - ScienceDirect

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Geospatial surveying combines advanced technologies such as drone-based mapping, lidar, photogrammetry, laser scanning, ground penetrating radar, and magnetic surveys to gather, analyze, and interpret precise geographical and spatial data. This innovative approach provides detailed insights into the earth’s surface and subsurface, enabling smarter decision-making throughout the lifecycle of mining and exploration projects.

We are proud to share that Hemayatullah Ahmadi, a valued member of our team, recently had a new research study published. His work, titled "Mapping Alteration Minerals Associated with Aktogay Porphyry Copper Mineralization in Eastern Kazakhstan Using Landsat-8 and ASTER Satellite Sensors," explores the use of satellite data to identify key geological features linked to copper mineralization. You can read the full abstract and access the publication below.

Abstract

Mineral resources, particularly copper, are crucial for the sustained economic growth of developing countries like Kazakhstan. Over the past four decades, the diversity and importance of critical minerals for high technology and environmental applications have increased dramatically. Today, copper is a critical metal due to its importance in electrification. Porphyry deposits are important sources of copper and other critical metals. Conventional exploration methods for mapping alteration zones as indicators of high-potential zones in porphyry deposits are often associated with increased cost, time and environmental concerns. Remote sensing imagery is a cutting-edge technology for the exploration of minerals at low cost and in short timeframes and without environmental damage. Kazakhstan hosts several large porphyry copper deposits, such as Aktogay, Aidarly, Bozshakol and Koksai, and has great potential for the discovery of new resources. However, the potential of these porphyry deposits has not yet been fully discovered using remote sensing technology. In this study, a remote sensing-based mineral exploration approach was developed to delineate hydrothermal alteration zones associated with Aktogay porphyry copper mineralization in eastern Kazakhstan using Landsat-8 and ASTER satellite sensors. A comprehensive suite of image processing techniques was used to analyze the two remote sensing datasets, including specialized band ratios (BRs), principal component analysis (PCA) and the Crosta method. The remote sensing results were validated against field data, including the spatial distribution of geological lineaments and petrographic analysis of the collected rock samples of alteration zones and ore mineralization. The results show that the ASTER data, especially when analyzed with specialized BRs and the Crosta method, effectively identified the main hydrothermal alteration zones, including potassic, propylitic, argillic and iron oxide zones, as indicators of potential zones of ore mineralization. The spatial orientation of these alteration zones with high lineament density supports their association with underlying mineralized zones and the spatial location of high-potential zones. This study highlights the high applicability of the remote sensing-based mineral exploration approach compared to traditional techniques and provides a rapid, cost-effective tool for early-stage exploration of porphyry copper systems in Kazakhstan. The results provide a solid framework for future detailed geological, geochemical and geophysical studies aimed at resource development of the Aktogay porphyry copper mineralization in eastern Kazakhstan. The results of this study underpin the effectiveness of remote sensing data for mineral exploration in geologically complex regions where limited geological information is available and provide a scalable approach for other developing countries worldwide.

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Read the article for free here: https://www.mdpi.com/3216948

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Hemayatullah Ahmadi's paper, “Automated detection of granitic complexes in NW Parwan, NE Afghanistan using Sentinel-2B/MSI and ASTER data,” explores advanced geospatial techniques and machine learning to map granite formations in northeastern Afghanistan. The study identified two granitic complexes with 75% accuracy, providing valuable insights for resource exploration of rare earth elements, aluminum, and tungsten.

Abstract

Granites are widely distributed, phaneritic igneous rocks renowned for their high compressive strength and durability, making them a premier choice for dimension stone applications. This study aims to detect and map granitic complexes using geospatial data and spectral algorithms within the arid and semi-arid environment of northwestern Parwan Province, northeastern Afghanistan. Also, to establish an effective and optimized supervised classification approach specifically tailored for identifying granitic complexes in similar terrains. This study utilizes FCC imagery to highlight lithology and employs various machine learning algorithms, including ML, MD, SVM, and SAM, for mapping granitic complexes within the study area. Training and test data were collected from field observations, Google Earth imagery, and geological maps. Our analysis identified two primary granitic complexes within the study area, measuring approximately 19 km × 13 km2 and 7 km × 3 km2, respectively. Ground truth data validation yielded an accuracy of 75%, indicating a positive correlation between the predicted and observed distributions. This enhanced understanding of granite distribution can serve as a valuable guide for future exploration endeavors targeting metallic and non-metallic resources, including aluminum, iron, manganese, rare earth elements, tungsten, etc.

Access the article for free here.

We are thrilled to announce that one of our esteemed employees, Hemayatullah Ahmadi, has recently had a groundbreaking paper published in the prestigious journal Geosciences. The paper, titled "Assessing the Impacts of Landuse-Landcover (LULC) Dynamics on Groundwater Depletion in Kabul, Afghanistan’s Capital (2000–2022): A Geospatial Technology-Driven Investigation," explores the critical issue of groundwater depletion through a detailed geospatial analysis.

Abstract

Land use/land cover (LULC) changes significantly impact spatiotemporal groundwater levels, posing a challenge for sustainable water resource management. This study investigates the long-term (2000–2022) influence of LULC dynamics, particularly urbanization, on groundwater depletion in Kabul, Afghanistan, using geospatial techniques. A time series of Landsat imagery (Landsat 5, 7 ETM+, and 8 OLI/TIRS) was employed to generate LULC maps for five key years (2000, 2005, 2010, 2015, and 2022) using a supervised classification algorithm based on Support Vector Machines (SVMs). Our analysis revealed a significant expansion of urban areas (70%) across Kabul City between 2000 and 2022, particularly concentrated in Districts 5, 6, 7, 11, 12, 13, 15, 17, and 22. Urbanization likely contributes to groundwater depletion through increased population growth, reduced infiltration of precipitation, and potential overexploitation of groundwater resources. The CA-Markov model further predicts continued expansion in built-up areas over the next two decades (2030s and 2040s), potentially leading to water scarcity, land subsidence, and environmental degradation in Kabul City. The periodic assessment of urbanization dynamics and prediction of future trends are considered the novelty of this study. The accuracy of the generated LULC maps was assessed for each year (2000, 2005, 2010, 2015, and 2022), achieving overall accuracy values of 95%, 93.8%, 85%, 95.6%, and 93%, respectively. These findings provide a valuable foundation for the development of sustainable management strategies for Kabul’s surface water and groundwater resources, while also guiding future research efforts.

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You can access the full paper through the following links:

• Read Online for Free
• PDF

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