Environment
Mohammad Hadi Salehzadeh; Hadi Farhadian; Saeed Yousefi; Mohammad Dehju
Abstract
This study aims to assess the environmental impacts of coal mining in the Eastern Alborz region, focusing on coal mines from 2013 to 2021, using remote sensing techniques. Landsat 8 satellite images were digitized based on key environmental indices, including NDVI, NDWI, NDSI, and NDBI, and subsequent ...
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This study aims to assess the environmental impacts of coal mining in the Eastern Alborz region, focusing on coal mines from 2013 to 2021, using remote sensing techniques. Landsat 8 satellite images were digitized based on key environmental indices, including NDVI, NDWI, NDSI, and NDBI, and subsequent statistical analyses and evaluations were conducted for the study areas. To distinguish the effects of mining from those of climate change, the results were compared with a reference area located within a natural resource block (baseline area), and the outcomes were thoroughly analyzed. The findings indicate that the combined impacts of mining and climate change have caused significant environmental degradation in the region. In particular, vegetation cover has experienced a sharp decline in recent years, while soil erosion has increased at a slower rate. Projections of mining impacts on vegetation and soil were made by calculating the average NDVI and NDSI indices for 2030 and 2050 in the studied areas. These projections suggest that NDVI is expected to decrease by 0.25 by 2030 and by 0.72 by 2050, indicating further vegetation loss in the coming decades. In contrast, analysis of the NDWI index reveals no clear trend in soil moisture changes over the study period. Given the climatic conditions of the selected areas, it is essential to monitor, manage, and mitigate environmental risk factors to prevent the expansion of drought into northern forests, highlighting the need for appropriate intervention measures.
Exploration
Mobin Saremi; Saeed Yousefi; Mahyar Yousefi
Abstract
The Mineral Prospectivity Mapping (MPM) is a procedure of integrating various exploration data to identify promising areas for follow up mineral exploration programs. MPM facilitates identification of mineral deposit prospects through reducing search spaces for the purpose of mitigating cost and time ...
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The Mineral Prospectivity Mapping (MPM) is a procedure of integrating various exploration data to identify promising areas for follow up mineral exploration programs. MPM facilitates identification of mineral deposit prospects through reducing search spaces for the purpose of mitigating cost and time shortages. In this regard, geochemical anomaly maps constitute one of the most important evidential layers for MPM. In this research work, to produce an efficient geochemical evidential layer, the Staged Factor Analysis (SFA) method and Geochemical Mineralization Probability Index (GMPI) were performed on a dataset of 657 stream sediment samples. In addition to the mentioned maps, a layer of proximity to faults was used to efficiently identify the intended targets of copper hydrothermal deposits. The layers were then weighted and combined using logistic functions and the geometric average method. Based on the obtained results, the promising areas were found in three parts including western, central, and northern areas, which correspond to the faulted units of andesite, tuff, granite, and granodiorite intrusive masses. Finally, in order to evaluate the generated model, the prediction-area (P-A) plot was used, which shows the relative success of the generated map in specifying the desired exploration targets. The P-A plot showed that this model has a prediction rate of 64%. It seems that the proposed method by considering multi-element geochemical signatures and combination by another exploratory layer target the promising areas, those that are simultaneously present with other exploration evidence.
Mahyar Yousefi; Samaneh Barak; Amir Salimi; Saeed Yousefi
Abstract
In this paper, we discuss the concepts behind dispersion patterns of geochemical anomalies when applied for prospecting mineral deposits in different exploration scales. The patterns vary from regional to local scale geochemical surveys, which is due to the differences in the corresponding underlying ...
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In this paper, we discuss the concepts behind dispersion patterns of geochemical anomalies when applied for prospecting mineral deposits in different exploration scales. The patterns vary from regional to local scale geochemical surveys, which is due to the differences in the corresponding underlying processes. Thus the ways for modelling the dispersion patterns and driving significant geochemical signatures should consider the variety when the area under study are delimited from regional to deposit scales exploration. Subsequently, this paper faces with two questions, namely (1) should various geochemical indicators be integrated in different exploration scales aiming at introducing stronger signatures of mineral deposits? and (2) how does the exploration scale affect dispersion patterns of geochemical indicator elements? We demonstrate that the exploration scale plays an important role on the reliability and usefulness of geochemical anomaly models. In this regard, although fusion may achieve reputable outcomes at regional scale exploration, we demonstrate that integration doesn’t gain accurate results for exploration at local scale, which is due to the diversities of the elemental distributions in the two different scales. This achievement is approved by comparing two geochemical signatures, one obtained by integration of two different indicator factors and the other one that used a single factor. The former produces almost the whole studied area as prospective, while the later recognizes ~10% of the area for further exploration, which is closely related to the porphyry Cu mineralization and is verified by drilling results.
