Remote Sensing for Surface Coal Mining and Reclamation Monitoring in the Central Salt Range, Punjab, Pakistan

被引:7
|
作者
Ali, Nafees [1 ,2 ,3 ]
Fu, Xiaodong [1 ,2 ,3 ]
Ashraf, Umar [4 ]
Chen, Jian [1 ,2 ,3 ]
Hung Vo Thanh [5 ]
Anees, Aqsa [4 ]
Riaz, Muhammad Shahid [6 ]
Fida, Misbah [7 ]
Hussain, Muhammad Afaq [8 ]
Hussain, Sadam [9 ]
Hussain, Wakeel [9 ,10 ]
Ahmed, Awais [11 ]
机构
[1] Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] China Pakistan Joint Res Ctr Earth Sci, Islamabad 46000, Pakistan
[4] Yunnan Univ, Sch Ecol & Environm Sci, Inst Ecol Res & Pollut Control Plateau Lakes, Kunming 650500, Yunnan, Peoples R China
[5] Seoul Natl Univ, Sch Earth & Environm Sci, 1 Gwanak Ro, Seoul 08826, South Korea
[6] Quaid I Azam Univ Campus, Ctr Earthquake Studies, Natl Ctr Phys, Islamabad 15320, Pakistan
[7] Changan Univ, Sch Water & Environm, Xian 710054, Peoples R China
[8] China Univ Geosci, Sch Geog & Informat Engn, Wuhan 430074, Peoples R China
[9] China Univ Geosci, Dept Geol Resources & Engn, Wuhan 430074, Peoples R China
[10] China Univ Geosci, Fac Earth Resources, Dept Petr Engn, Wuhan 430079, Peoples R China
[11] Wuhan Univ Sci & Technol, Sch Resources & Environm Engn, Dept Min Engn, Wuhan 430081, Peoples R China
基金
中国国家自然科学基金;
关键词
coal mining; remote sensing; Tasseled Cap Transformation; Landsat data; TRANSFORMATION; TEMPERATURE; PREDICTION; CITY;
D O I
10.3390/su14169835
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The expansion and exploitation of mining resources are essential for social and economic growth. Remote sensing provides vital tools for surface-mining monitoring operations as well as for reclamation efforts in the central Salt Range of the Indus River Basin, Pakistan. This research demonstrates the applicability of remote sensing techniques to the coal mining monitoring scheme to allow for effective and efficient monitoring and to offset the adverse consequences of coal mining activities. Landsat 8 OLI images from June 2019 and 2020, and a Landsat 7 ETM+ image from June 2002, were used for this study. A three-phase methodology including Normalized Difference Vegetation Index (NDVI) analysis, land cover mapping, and change detection approaches was adopted. Image classification based on Tasseled Cap Transformation and the brightness temperature At-satellite using the K-means algorithm was implemented in a GIS program to identify seven land cover classes within the study area. The results show some level of surface disturbance to the landscape due to the coal mining reclamation activities that had taken place over the 18-year time period. From 2019 to 2020, about 3.622 km(2) of coal mines or barren land were converted into bare agricultural land. Over the years, it was also observed that reclamation areas exhibited higher values of NDVI than coal mining areas. The mean NDVI for coal mining areas was 0.252 km(2), and for areas of reclamation, it was 0.292 km(2) in 2020, while in 2019, the value for coal mining sites was 0.133 km(2), and 0.163 km(2) for reclamation sites. This trend suggests that coal-mining operations can be monitored using satellite data, and the progress of reclamation efforts can be assessed using satellite NDVI data from the target locations. This study is beneficial to agencies responsible for monitoring land cover changes in a coal mine because it provides a cost-effective, efficient, and robust scientific tool for making mine site allocation decisions and for monitoring the progress of reclamation efforts.
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页数:26
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