A Novel Landsat-Derived Multispectral Index for Coal Dust Detection: Spatiotemporal Dispersion Patterns and Natural Driving Forces
文献类型：期刊论文
| 作者 | Yan, Xiaoxiao2,3; Li, Jing2; Shao, Yang4; Wang, Kewen2; Yan, Xingguang2; Benndorf, Joerg1 |
| 刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
 |
| 出版日期 | 2025 |
| 卷号 | 18页码:15198-15208 |
| 关键词 | Coal Soil Pollution Grasslands Wind speed Indexes Reflectivity Dispersion Coal mining Landsat Coal dust pollution dispersion patterns fluent simulation landsat imagery mining-environment coal dust index (MECDI) meteorological and topographic factors spatiotemporal dispersion |
| ISSN号 | 1939-1404 |
| DOI | 10.1109/JSTARS.2025.3567467 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Coal dust pollution, a major byproduct of mining, poses significant environmental and health risks. However, the temporal diffusion and spatial extent of coal dust remain unclear, complicating ecological restoration efforts and intensifying conflicts between mining and human settlements. This study develops a mining-environment coal dust index (MECDI) using Landsat imagery (1989-2022) to monitor coal dust in the Baorixile coalfield, Inner Mongolia, enhancing detection accuracy. Fluent simulations analyzed the influence of meteorological and topographic factors on dust dispersion. Results indicate that coal dust spreads beyond the mining zones, with significant reductions since 2019 due to control measures. In open-pit mines, coal dust follows a right-skewed patterns over time. In the underground mine area, dust diffusion increased until 2017, then stabilized, following a logistic curve in S shape. The highest dust concentrations were within 800 m of the mining area and along transportation routes. Coal dust accumulation is more affected by slope degree than aspect, with lower slopes more prone to dust buildup. High wind speeds and greater pressure differences facilitate dust dispersion, while low wind speeds and circulation patterns contribute to dust accumulation at the pit bottom. The proposed MECDI index introduces an innovative and scalable metric for coal dust pollution monitoring, enabling more precise assessments and informed mitigation strategies that support sustainable mining and regional environmental governance. |
| URL标识 | 查看原文 |
| WOS关键词 | PARTICLE-SIZE |
| WOS研究方向 | Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001518786800002 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/215423]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Li, Jing |
| 作者单位 | 1.Freiberg Univ Technol, Inst Mine Surveying & Geodesy, D-09599 Freiberg, Germany 2.China Univ Min & Technol Beijing, Sch Geosci & Surveying Engn, Beijing 100083, Peoples R China; 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 4.Virginia Tech, Coll Nat Resources & Environm, Dept Geog, Blacksburg, VA 24061 USA; |
| 推荐引用方式 GB/T 7714 | Yan, Xiaoxiao,Li, Jing,Shao, Yang,et al. A Novel Landsat-Derived Multispectral Index for Coal Dust Detection: Spatiotemporal Dispersion Patterns and Natural Driving Forces[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2025,18:15198-15208. |
| APA | Yan, Xiaoxiao,Li, Jing,Shao, Yang,Wang, Kewen,Yan, Xingguang,&Benndorf, Joerg.(2025).A Novel Landsat-Derived Multispectral Index for Coal Dust Detection: Spatiotemporal Dispersion Patterns and Natural Driving Forces.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,18,15198-15208. |
| MLA | Yan, Xiaoxiao,et al."A Novel Landsat-Derived Multispectral Index for Coal Dust Detection: Spatiotemporal Dispersion Patterns and Natural Driving Forces".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 18(2025):15198-15208. |
入库方式： OAI收割
来源：地理科学与资源研究所
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