Study on the ecological cumulative effect (ECE) in mining area is an effective way to understand the impact of long-term coal mining on the ecological environment. However, the existing quantitative models to evaluate the ECE in mining area focus more on region-wide features, static analysis and multi-temporal comparison with numerical results, but less on the spatial heterogeneity, dynamic changes trajectory and visual mapping of ECE. In order to fill this gap, we have proposed a pixel-based time series model of ecosystem service value (ESV) to quantify the ECE in mining area and reveal its spatial distribution, heterogeneity and dynamic process. The model was constructed from three dimensions, namely space, time and element, which were analyzed from pixel scale, the whole research period and the perspective of ESV respectively. Taking Yanzhou coalfield as the study area, from 1987 to 2016 as the time span, the model was used to analyze the ECE. The study results showed that: 1) it could display the detail about each pixel’s spatio-temporal change of ESV credibly by dynamic equivalent factor method based on time-series remote sensing (RS), with equivalent factor rectified by remote sensing-based ecological index (RSEI) and modified normalized difference water index (MNDWI) pixel by pixel. 2) The pixel-based time series model of ESV showed a good performance in reflecting the spatial distribution and heterogeneity of ECE, revealing the direction and extent of accumulation, and achieving the dynamic evaluation of ECE in the time dimension. 3) The change of ecosystem service value cumulant (COESVC) in Yanzhou coalfield decreased by 644.49 million RMB, showing obviously negative ECE. The areas with negative ECE were mainly distributed outside the area above mining faces, while that with positive ECE mostly appeared in waterlogged areas, especially those within the area above mining faces. The evaluation result of ECE could be used in decision-making for improving ecological quality and developing coal mining strategies. This paper may also offer an idea and method for dynamic and quantitative evaluation of the ECE in mining and similar area by time-series Landsat-based RS.

研究矿区生态累积效应（ECE）是了解长期采煤对生态环境影响的有效途径。但是，现有的评估矿区ECE的定量模型更多地侧重于区域范围的特征，静态分析和具有数值结果的多时相比较，而很少关注ECE的空间异质性，动态变化轨迹和视觉映射。为了填补这一空白，我们提出了一种基于像素的生态系统服务价值（ESV）时间序列模型，以量化矿区的ECE并揭示其空间分布，异质性和动态过程。该模型是从空间，时间和元素三个维度构建的，分别从像素尺度，整个研究时期和ESV的角度进行了分析。以Yan州煤田为研究区域，以1987年至2016年为时间跨度，对该模型进行了ECE分析。研究结果表明：1）基于时间序列遥感（RS）的动态等效因子方法能够可靠地显示每个像素的ESV时空变化的细节，并通过基于遥感的生态指数对等效因子进行校正。 （RSEI）和修改的归一化差异水指数（MNDWI）逐像素。2）ESV的基于像素的时间序列模型在反映ECE的空间分布和异质性，揭示积累的方向和程度以及实现ECE在时间维度上的动态评估方面表现出良好的性能。3）Yan州煤田生态系统服务价值累积量（COESVC）减少6.449亿元，显示出明显的负ECE。ECE值为负的区域主要分布在采煤工作面以上区域之外，而ECE值为正的区域主要出现在涝区，尤其是采掘面以上区域。ECE的评估结果可用于提高生态质量和制定煤矿开采策略的决策。本文还可以为基于时间序列的基于Landsat的RS动态和定量评估采矿及类似地区的ECE提供一种思路和方法。ECE的评估结果可用于提高生态质量和制定煤矿开采策略的决策。本文还可以为基于时间序列的基于Landsat的RS动态和定量评估采矿及类似地区的ECE提供一种思路和方法。ECE的评估结果可用于提高生态质量和制定煤矿开采策略的决策。本文还可以为基于时间序列的基于Landsat的RS动态和定量评估采矿及类似地区的ECE提供一种思路和方法。