基于Landsat影像的采煤对地表植被覆盖度时空变化的影响研究

Study on the Influences of Coal Mining on the Temporal and Spatial Variations of Surface Vegetation Coverage Based on Landsat Images

研究地下采煤扰动下地表植被覆盖度的时空变化及驱动因素,可为煤炭资源合理开发和地表植被生态管理提供科学指导。以阳泉市大阳泉煤炭有限责任公司不同开采年份工作面为研究区,基于2009年和2019年的Landsat遥感影像,采用像元二分模型估算植被覆盖度,研究植被覆盖度的空间格局及其时空变化规律,并运用地理探测器模型探究植被覆盖度变化的主要驱动因素。结果表明:研究区近10年来植被覆盖总体情况良好,中高植被覆盖度和高植被覆盖度面积呈增加趋势;地形因子中,植被覆盖度随高程和坡度的增加呈现先增加后减小的趋势,在坡向上呈现出西北坡的最高,而东坡、南坡和东南坡的相对较低的趋势。对比2009—2019年植被覆盖度的时空变化特征发现:2007年前开采的大多数工作面的植被覆盖度明显改善,而2007年后开采的工作面植被覆盖状况呈退化趋势,表明生态系统的自我调节恢复能力会使生态系统逐渐向良性循环方向发展。因子探测结果表明:开采时间是影响植被覆盖度时空变化的最主要因素;交互作用探测中,以开采时间和高程的共同作用最强,表明人为因素与自然因素的协同增加了对植被覆盖度变化的影响。

The study of temporal and spatial variation and driving factors of the surface vegetation coverage under the disturbance of underground coal mining can provide scientific guidance for rational exploitation of coal resources and ecological management of surface vegetation. Taking the working faces of Dayangquan Coal Co., Ltd. in different mining years as the research area, based on Landsat remote sensing images of 2009 and 2019, the pixel dichotomy model is used to estimate the vegetation coverage. This paper studies the spatial pattern of vegetation coverage and its temporal and spatial changes, and its main driving factors are explored with the geographical detector model. The results are as follows. Firstly, in recent ten years, the vegetation coverage in the study area is generally good, with medium-high and high vegetation coverage areas showing an increasing trend. Secondly, among the topographic factors, the vegetation coverage first increases and then decreases with the increase of elevation and slope. Among different slopes, the vegetation coverage is the highest in the northeast, while is relatively lower in the east, south, and southeast slopes. Comparing the temporal and spatial characteristics of vegetation coverage from 2009 to 2019, it is found that the vegetation coverage of most working faces mined before 2007 has been significantly improved, while the vegetation coverage of working faces mined after 2007 has showed a trend of degradation, indicating that the self-regulation and recovery ability of the ecosystem will make the ecosystem develop towards a virtuous cycle gradually. The factor detection results show that mining time is the most important factor affecting the temporal and spatial changes of vegetation coverage. In the interaction detection, the combined effect of mining time and elevation is the strongest, which indicates that human factors and natural factors have synergistically increased the influence on vegetation coverage changes.