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.
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.
Hemayatullah Ahmadi’s study demonstrates how Landsat-8 and ASTER satellite data can be used to effectively map alteration minerals linked to porphyry copper deposits in Eastern Kazakhstan, supporting more efficient mineral exploration.
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.
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.
Read the article for free here: https://www.mdpi.com/3216948
Hemayatullah Ahmadi’s study uses advanced geospatial data and machine learning to accurately map granitic complexes in northeastern Afghanistan, offering valuable insights for future resource exploration.
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.
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.
Wood Rodgers employee Hemayatullah Ahmadi recently had a paper published in Geosciences. Read it 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.
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.
You can access the full paper through the following links:
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