College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, China.
State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing, 102209, China.
Environ Monit Assess. 2022 Dec 23;195(1):224. doi: 10.1007/s10661-022-10815-0.
Considering the spatio-temporal heterogeneity, this study resolved the coupling influence of a variety of driving factors on vegetation changes in mining areas and discovered the influencing characteristics of the respective driving factors, especially mining activities. First, the spatio-temporal characteristics of FVC (fractional vegetation cover) variation were analyzed in the Sheng-Li mining area. Second, the quantitative relationships among the natural factors (temperature, precipitation, and elevation), artificial factors (mining activities, urban activities), and FVC were constructed by GTWR (geographically and temporally weighted regression) to quantify the contribution of each factor to the change in FVC. Third, the influencing characteristics of the respective driving factors, especially mining activities, were analyzed and summarized. The results show that (1) the FVC change was mainly influenced by natural factors in the areas far from mines and towns and artificial factors in the areas close to mines and towns. (2) The contribution of mining activities to vegetation change (C-Mine) was spatially characterized by two features: (a) distance attenuation characteristics: C-Mine showed logarithmic decrement with distance; (b) directional heterogeneity: C-Mine varied significantly in different directions. In particular, there was a high C-Mine area located near multiple mining areas, and the range of this area shifted to include the mine with more production over time. Overall, unmixing the coupling influence from driving factors with spatio-temporal heterogeneity and achieving a quantitative description of the influencing characteristics in mining areas were the main contributions of this study. The quantification methods and results in this paper provide important support for decision-making on ecological protection and restoration in mining areas.
考虑到时空异质性，本研究解决了多种驱动因素对矿区植被变化的耦合影响，并发现了各驱动因素的影响特征，尤其是采矿活动。首先，分析了胜利矿区 FVC（植被覆盖分数）变化的时空特征。其次，通过 GTWR（时空加权回归）构建了自然因素（温度、降水和海拔）、人为因素（采矿活动、城市活动）与 FVC 之间的定量关系，以量化各因素对 FVC 变化的贡献。第三，分析和总结了各驱动因素，尤其是采矿活动的影响特征。结果表明：（1）远离矿山和城镇的区域 FVC 变化主要受自然因素影响，而靠近矿山和城镇的区域则主要受人为因素影响。（2）采矿活动对植被变化的贡献（C-Mine）在空间上具有两个特征：（a）距离衰减特征：C-Mine 随距离呈对数递减；（b）方向非均质性：C-Mine 在不同方向上变化显著。特别是在多个采矿区附近存在一个高 C-Mine 区域，该区域的范围随着时间的推移逐渐扩大，包括生产更多的矿山。总的来说，本研究的主要贡献是，通过时空异质性分解驱动因素的耦合影响，并对矿区的影响特征进行定量描述。本文提出的量化方法和结果为矿区生态保护和恢复的决策提供了重要支持。
