Quantitative estimation for the impact of mining activities on vegetation phenology and identifying its controlling factors from Sentinel-2 time series

文献类型： 外文期刊

第一作者： Sun, Xiaofei

作者： Sun, Xiaofei;Yuan, Linguo;Liu, Meng;Sun, Xiaofei;Li, Dongfeng;Liang, Shuneng;Liu, Liyang

作者机构：

关键词： Remote sensing; Sentinel-2 time series; Vegetation phenology; Mining area; Pareto principle

期刊名称：INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION （ 影响因子：7.672； 五年影响因子：7.332 ）

ISSN： 1569-8432

年卷期： 2022 年 111 卷

页码：

收录情况： SCI

摘要： Quantitative assessment of the negative environmental effects of mining is vital for the eco-environmental restoration and management of mining areas. However, it remains unclear about the spatial dimension of the influence on the environment that comes from mining. Here, we constructed a new method to quantify the vegetation impact of mining activity using Sentinel-2 time series and Pareto principle, and applied it to the Liaoning Nanfen iron mining area (LNMA), the Inner Mongolia Sanheming iron mining area (IMMA), and the Sichuan Hongge iron mining area (SCMA) in China. Based on the unequal relationship of 80% of the consequences determined by 20% of the causes, the influence of mining activities on vegetation was quantified by the maximum phenological difference, the decay rate, the asymptotic value of exponential trend and the distance from the mine. Results showed that the impact of mining activities on vegetation phenology decayed exponentially along with the increase of the distance to the mines. The influence distance of mining activities on vegetation were 1566.95 m, 1959.67 m, and 1809.61 m for LNMA, IMMA and SCMA, respectively. Compared to areas 5 km away from the mining activity, the start of the growing season for vegetation surrounding the mining activity was delayed by 1.1 +/- 0.4 days, 6.1 +/- 1.9 days, and 1.5 +/- 0.7 days for LNMA, IMMA and SCMA, respectively, while the length of the growing season was successively shortened by 1.0 +/- 0.6 days, 5.4 +/- 2.5 days, and 5.1 +/- 3.9 days, respectively. Our investigation found that the dust pollution, decreases in groundwater levels, and waterborne pollution were the main factors that directly caused phenological changes around the mining area, and the distance and degree of their impact on phenology were closely related to drought and topography. This finding could provide a reference for the environmental restoration and management of mining areas and help to add insights on the assessment for the long-term impacts of mining activities on vegetation.

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