Abstract：
The global use of mineral resources has increased exponentially for decades and will continue to grow for the foreseeable future, resulting in increasingly negative impacts on the surrounding environment. However, to date, there are a lack of historical and current spatial extent datasets with high accuracy for mining areas in many parts of the world, which has hindered a more comprehensive understanding of the environmental impacts of mining. Using the Google Earth Engine cloud platform and the Landsat normalized difference vegetation index (NDVI) datasets, the spatial extent data of open-pit mining areas for eight years (1985, 1990, 1995, 2000, 2005, 2010, 2015, and 2020) was extracted by the Otsu algorithm. The limestone mining areas in Qingzhou, Shandong Province, China, was selected as a case study. The annual maximum NDVI was first derived from the Landsat NDVI datasets, and then the Otsu algorithm was used to segment the annual maximum NDVI images to obtain the extent of the mining areas. Finally, the spatiotemporal characteristics of the mining areas in the study region were analyzed in reference to previous survey data. The results showed that the mining areas were primarily located in Shaozhuang Town, Wangfu Street and the northern part of Miaozi Town, and the proportion of mining areas within these three administrative areas has increased annually from 88% in 1985 to more than 98% in 2010. Moreover, the open-pit mining areas in Qingzhou gradually expanded from a scattered, point-like distribution to a large, contiguous distribution. From 1985 to 2020, the open-pit mining area expanded to more than 10 times its original size at a rate of 0.5 km2/year. In 2015, this area reached its maximum size of 19.7 km2 and slightly decreased in 2020. Furthermore, the expansion of the mining areas in Qingzhou went through three stages: a slow growth period before 1995, a rapid expansion period from 1995 to 2005, and a shutdown and remediation period after 2005. A quantitative accuracy assessment was performed by calculating the Intersection over Union (IoU) of the extraction results and the visual interpretation results from Gaofen-2 images with 1-m spatial resolution. The IoU reached 72%. The results showed that it was feasible to threshold the Landsat annual maximum NDVI data by the Otsu algorithm to extract the annual spatial extent of the open-pit mining areas. Our method will be easily transferable to other regions worldwide, enabling the monitoring of mine environments.
摘要：
全球对矿产资源的利用几十年来呈指数级增长,并将在可预见的未来继续增长,对周围环境的负面影响越来越大。然而,到目前为止,在世界许多地方，缺乏高精度的采矿区的历史和当前空间范围数据集，这阻碍了更全面地了解采矿对环境的影响。使用GoogleEarthEngine云平台和Landsat归一化差异植被指数(NDVI)数据集,利用Otsu算法提取了8年(1985年、1990年、1995年、2000年、2005年、2010年、2015年和2020年)露天矿区的空间范围数据.青州的石灰岩矿区，山东省,中国,被选为案例研究。年度最大NDVI首先来自LandsatNDVI数据集，然后使用Otsu算法对年度最大NDVI图像进行分割，以获得矿区的范围。最后,参考以往的调查数据，分析了研究区域矿区的时空特征。结果表明,矿区主要位于邵庄镇,王府街和苗子镇北部，这三个行政区域内的矿区比例从1985年的88%逐年上升到2010年的98%以上。此外，青州的露天矿区逐渐从分散扩大，点状分布到一个大的，连续分布。从1985年到2020年，露天开采面积以0.5km2/年的速度扩大到原来的10倍以上。2015年，该区域面积达到最大19.7km2，2020年略有下降。此外，青州矿区的扩张经历了三个阶段：1995年之前的缓慢增长期，1995年至2005年的快速扩张期和2005年之后的停产整治期。通过计算提取结果的交集（IoU）和空间分辨率为1-m的Gaofen-2图像的视觉解释结果来进行定量准确性评估。IoU达到72%。结果表明，利用Otsu算法对Landsat年最大NDVI数据进行阈值化，以提取露天矿区的年空间范围是可行的。我们的方法将很容易转移到全球其他地区，能够监测矿井环境。
