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遥感技术与应用  2022, Vol. 37 Issue (5): 1043-1055    DOI: 10.11873/j.issn.1004-0323.2022.5.1043
综述     
矿山环境遥感监测研究进展
黄登冕1(),张聪1,姚晓军1(),杨显华2,刘娟3
1.西北师范大学 地理与环境科学学院,甘肃 兰州 730070
2.四川省地质调查院稀有稀土战略资源评价与利用四川省重点实验室,四川 成都 610081
3.甘肃省地质矿产勘查开发局第三地质矿产勘查院,甘肃 兰州 730050
Research Progress of Mine Environment Remote Sensing Monitoring
Dengmian Huang1(),Cong Zhang1,Xiaojun Yao1(),Xianhua Yang2,Juan Liu3
1.College of Geography and Environmental Science,Northwest Normal University,Lanzhou 730070,China
2.Sichuan Institute of Geological Survey,Chengdu 610081,China
3.The Third Institute of Geology and Minerals Exploration,Gansu Provincial Bureau of Geology and Minerals Exploration Development,Lanzhou 730050,China
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摘要:

矿产资源是人类赖以生存和发展的重要生产资料,开展矿山监测对于矿产资源开发利用和矿区环境保护至关重要。由于具有大范围、多时相和综合性等优势,遥感技术已成为矿山监测的主要手段。针对矿山开发利用状况、地质灾害问题以及生态环境监测与质量评价等需求,系统总结了矿山环境遥感监测所用的数据源、方法和模型。目前遥感监测数据源已趋于多样化并覆盖矿山监测各方面,得益于云计算平台及人工智能技术快速发展,大数据分析和深度学习等方法在矿山环境遥感监测中逐渐发挥重要作用,而多源数据融合、地物智能化提取、三维形变监测和定量反演等是矿山环境遥感监测存在的主要问题与挑战。

关键词: 矿山遥感监测矿产资源地质灾害生态环境    
Abstract:

Mineral resources are important production materials for human survival and development, and the monitoring of mine environment is crucial for mineral resources exploitation and protection. Due to the advantages including large-scale, multi temporal and comprehensive, remote sensing technology has become the main means of mine monitoring. Aiming to the requirements of mine development and utilization, geological disasters, ecological environment monitoring and quality evaluation, we systematically summarized data sources, methods and models used in remote sensing monitoring of mine environment. Especially, data sources adopted in remote sensing monitoring of mine have tended to diversify and involve in all aspects of mine monitoring. Along with the rapid development of cloud computing platform and artificial intelligence technology, methods such as big data analysis and deep learning have gradually played an important role in remote sensing monitoring of mine environment, while multi-source data fusion, intelligent extraction of features, three-dimensional deformation monitoring and quantitative inversion are the main problems and challenges.

Key words: Mine    Remote sensing monitoring    Mineral resources    Geological hazards    Ecological environment
收稿日期: 2021-11-19 出版日期: 2022-12-13
ZTFLH:  X87  
基金资助: 中国科学院“西部之光”人才培养引进计划项目“祁连山地区矿山遥感监测与生态恢复治理评价”;陇原青年创新创业人才个人项目“祁连山地区矿山环境遥感监测与生态恢复治理评价”资助
通讯作者: 姚晓军     E-mail: huangdm_nwnu@163.com;yaoxj_nwnu@163.com
作者简介: 黄登冕(1992-),男,甘肃白银人,硕士研究生,主要从事矿山环境遥感监测及深度学习目标检测方面的研究。E?mail:huangdm_nwnu@163.com
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引用本文:

黄登冕,张聪,姚晓军,杨显华,刘娟. 矿山环境遥感监测研究进展[J]. 遥感技术与应用, 2022, 37(5): 1043-1055.

Dengmian Huang,Cong Zhang,Xiaojun Yao,Xianhua Yang,Juan Liu. Research Progress of Mine Environment Remote Sensing Monitoring. Remote Sensing Technology and Application, 2022, 37(5): 1043-1055.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.5.1043        http://www.rsta.ac.cn/CN/Y2022/V37/I5/1043

类型适用场景卫星/传感器/产品分辨率/波段
光学地表占地要素识别GeoEye-1, GF-1/2, IKONOS, QuickBird, Pleiades, SuperView, WorldView, ALOS-1, CBERS-2, SPOT, Rapid Eye, ZY-02C/3, Sentinel-2, Landsat亚米级/2.5 m/5 m/10 m/30 m
植被指数和生态指数计算GF-1/2, WorldView, HJ-02C, ZY-3, Sentinel-2, Landsat, Hyperion, AVHRR产品, MODIS产品, GLOPEM-CEVSA NPP 产品

亚米级/2 m/10 m/

30 m/250 m/1 km

土壤水分含量、侵蚀量及重金属浓度反演Hyperion, ASTER, MODIS产品30 m/1 km
气溶胶光谱特性及粉尘PM值反演Sentinel-2, Hyperion, Landsat, HyMap, AVHRR产品, MODIS产品

10 m/30 m/50 m/

1 km

酸性矿井水识别,沉陷区水深和水储量反演ZY-3, Rapid Eye, Sentinel-2, ASTER, Landsat, HJ-1A, Google Earth, MODIS产品, GRACE2 m/5 m/10 m/30 m/100 m/1 km/0.5°
微波沉降监测,三维重建TerraSAR-X, TanDEM-X, Sentinel-1, RadarSat-1X/C波段
表面位移和尾矿库固结沉降监测,污染监测Envisat, Sentinel-1, TerraSAR-X, Cosmo-Skymed, TanDEM-X, HJ-1CSC/X/S波段
形变监测,三维重建ERS, Sentinel-1, 地基雷达, ALOS, JERS-1, GNSSC/L波段

无人机

遥感

地形测量,岩坡分析,水土污染、生态修复、复垦期地面沉降监测DJI Phantom 2数据, 机载AISA Eagle II数据, Micasense RedEdge-MX Dual, 多光谱传感器, 热成像传感器, 声呐传感器, IMU数据根据载荷确定
表1  矿山环境遥感监测不同场景常用的数据源
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