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Monitoring surface mining belts using multiple remote sensing datasets: A global perspective
DOI:10.1016/j.oregeorev.2018.08.019.png)
摘要
En 中文
Quantifying the spatiotemporal change of land cover and understanding their ecological, environmental, and socioeconomic impacts are important for sustainable development. Surface mining by the minerals industry is one driver of the changes in land cover, leading to loss of natural vegetation and top soils, and interruption of ecosystem service flows. This study investigates the effectiveness of remote sensing datasets to identify and map land cover changes, with the specific goal of understanding the impact of surface mining activities on land cover globally from 1980s to 2013. Diverse remote sensing datasets with long term observations are analyzed, including high-resolution images in Google Earth, Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM +)/Operational Land Imager (OLI), the Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) product and Defense Meteorological Satellites Program (DMSP)/Operational Linescan System (OLS) stable night-time light. The results indicated that after entering 21st century, North America (e.g., the United States and Canada) was the only continent to have more surface mining spots categorized as Shrink type (rehabilitated) rather than Expand type. South America (e.g., Chile and Brazil) and Asia (e.g., India and China) had the highest proportions of Expand Type of surface mining spots. Detailed demonstrations on how those remote sensing datasets could help in mining spot monitoring are presented.
Keyword:
Change detection
Surface mining
Time series
Global
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期刊
IF:
3.6
论文数:
6.6K
被引数:
2.2W
机构
引用论文
Surface coal mine area monitoring using multi-temporal high-resolution satellite imagery基于多时相高分辨率卫星影像的露天煤矿区监测
Sustainable Post-Mining Land Use: Are Closed Metal Mines Abandoned or Re-Used Space?
SUSTAINABILITY
IF3.3

