李军, 彭传盈, 张成业, 等. 基于大样本的露天开采植被扰动范围一般性统计规律——以神东煤炭基地为例[J]. 煤炭学报, 2023, 48(2): 975-985.
引用本文: 李军, 彭传盈, 张成业, 等. 基于大样本的露天开采植被扰动范围一般性统计规律——以神东煤炭基地为例[J]. 煤炭学报, 2023, 48(2): 975-985.
LI Jun, PENG Chuanying, ZHANG Chengye, et al. General statistical rules of vegetation disturbance range by open-pit mining based on a large sample: A case study of Shendong coal base[J]. Journal of China Coal Society, 2023, 48(2): 975-985.
Citation: LI Jun, PENG Chuanying, ZHANG Chengye, et al. General statistical rules of vegetation disturbance range by open-pit mining based on a large sample: A case study of Shendong coal base[J]. Journal of China Coal Society, 2023, 48(2): 975-985.

基于大样本的露天开采植被扰动范围一般性统计规律——以神东煤炭基地为例

General statistical rules of vegetation disturbance range by open-pit mining based on a large sample: A case study of Shendong coal base

  • 摘要: 露天开采对植被的扰动范围对于矿区生态环境治理与修复具有重要意义。现有研究主要以单个或若干个煤矿为研究对象,所得结论仅能反映个体煤矿的特点,缺乏对区域尺度上大量露天煤矿的开采扰动一般性规律研究,难以在实践中推广使用。针对上述问题,本研究根据临近煤矿分布特点与生态扰动类型,定义了4种类型的露天煤矿区OD-NDVI曲线(Orientation Distance-Normalized Difference Vegetation Index Curve),包括“负独立型曲线”、“负密集型曲线”、“正独立型曲线”和“正密集型曲线”,并提出了基于OD-NDVI曲线的开采植被扰动距离提取方法,包括数据预处理、OD-NDVI曲线提取、曲线分类与开采扰动距离识别4个主要步骤。以神东煤炭基地106个露天煤矿为研究对象,提取所有煤矿的开采扰动距离并进行定量统计分析,揭示了研究区露天开采对植被扰动范围的一般性统计规律。结果如下:(1)采用Shapiro-Wilk统计检验方法进行显著性检验,发现神东煤炭基地露天煤矿的开采扰动距离符合正态分布(R2=0.95),开采扰动距离大多在均值1 214 m附近,且68.26%的开采扰动距离分布在939.05 m, 1 488.71 m内(均值的1倍标准差内);(2)借助箱线图统计,揭示了露天煤矿的开采扰动距离存在有界性特点,最大值为2 025 m,最小值为600 m,仅有0.13%的开采扰动距离大于2 038.37 m(超过均值3倍标准差);(3)通过分析露天煤矿在8个方向上开采扰动距离的变异系数,发现其开采扰动距离存在显著的方向异质性,70.7%的煤矿方向开采扰动距离存在较强或中等方向异质性,仅有29.3%存在弱方向异质性;(4)通过拟合建模分析,发现开采扰动距离与实际年产煤量存在显著的对数模型关系(R2=0.613),随着煤矿的年产煤量增长,其开采扰动距离呈对数增加,但在年产煤量增加至232万t后,年产煤量对扰动距离无明显影响作用。基于大样本露天煤矿的统计分析结果具有更强的普适性和精细度,有望为干旱半干旱煤矿区的分级分区治理、精准修复、生产计划优化等提供科学指导。

     

    Abstract: The range of vegetation disturbance by open-pit mining is of theoretical and practical significance for the ecological management and restoration of mining areas. The current researches mainly focus on a single coal mine or several coal mines, and the conclusions obtained only reflect the characteristics of particular coal mines, lacking of the investigation of general patterns of mining disturbance for a large number of open-pit coal mines at a regional scale, which is difficult to be promoted and used in practice. In terms of above problems, four types of OD-NDVI(Orientation Distance-Normalized Difference Vegetation Index) curves for open-pit coal mines are defined based on the distribution characteristics of adjacent coal mines and the type of ecological disturbance, including “negative independent curve”,“negative dense curve”,“positive independent curve” and “positive dense curve”. Also, a distance extracting method for vegetation disturbance by mining based on the OD-NDVI curves is proposed, which includes four main steps: data pre-processing, OD-NDVI curve extraction, curve classification and mining disturbance distance identification. In a case study, all mining disturbance distances were extracted and statistically analyzed with 106 open-pit coal mines in the Shendong coal base, which revealed the general statistical patterns of vegetation disturbance range by open-pit mining in the study area. The results are as follows:(1) The Shapiro-Wilk for significance test shows that the mining disturbance distance of the open-pit coal mines in the Shendong coal base obeys a normal distribution(R2=0.95),with most of the mining disturbance distance around the mean value of 1 214 m, and 68.26% of the mining disturbance distance is distributed in the range of 939.05 m, 1 488.71 m(within the mean value with one time of the standard deviation).(2) There are bounded characteristics of mining disturbance distances in open-pit coal mines by using the box plot statistics, with a maximum value of 2 025 m and a minimum value of 600 m, and only 0.13% of mining disturbance distances are greater than 2 038.37 m(above the mean value with three times of the standard deviation).(3) Through analyzing the coefficient of variation of mining disturbance distances in eight directions in open pit coal mines, a significant directional heterogeneity has been observed in the directional mining disturbance distances of the open-pit coal mines, with strong or moderate directional heterogeneity in 70.7% of the mines and weak directional heterogeneity in only 29.3%.(4) A significant logarithmic relationship is found between the mining disturbance distance and the actual annual coal production(R2=0.613) via fitting modeling analysis, which increases logarithmically as the annual coal production increased, but after the annual coal production increases to 2.32 million tons, the annual coal production has no significant effect on the disturbance distance. The results of statistical analysis based on a large sample of open-pit coal mines have stronger general applicability and fineness, which are expected to provide scientific guidance for hierarchical zoning management, precise restoration, and production scheduling optimization in arid and semi-arid coal mining areas.

     

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