| Issue |
E3S Web Conf.
Volume 583, 2024
Innovative Technologies for Environmental Science and Energetics (ITESE-2024)
|
|
|---|---|---|
| Article Number | 01010 | |
| Number of page(s) | 7 | |
| Section | Geoinformatics, Mining Geology and Mineral Resources | |
| DOI | https://doi.org/10.1051/e3sconf/202458301010 | |
| Published online | 25 October 2024 | |
Analysis of geographically distributed ore deposit production status data
1 Bauman Moscow State Technical University, Moscow, Russia
2 Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia
* Corresponding author: ilya-kleshko@mail.ru
Analyzing the geographic distribution of ore deposits is crucial in understanding global resource availability, economic implications, and environmental impacts of mining activities. This article examines the distribution patterns of various ore types worldwide, highlighting their economic significance and current mining status. Utilizing tools such as Pandas for data preprocessing, Matplotlib and Seaborn for visualization, Geopandas for geographic data handling, and Scikit-learn for clustering analysis, we present a comprehensive review of ore deposits. Major ore types such as gold, copper, and iron are explored, emphasizing their industrial importance and geographic prevalence. The analysis reveals that many deposits are classified as Past Producers, indicating extensive historical mining activity. This underscores the need for efficient resource management and sustainable mining practices in the future. By understanding these distributions and statuses, stakeholders can better strategize for future mining ventures and environmental stewardship.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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