矿区生态环境评价中常采用单景、多景遥感数据来进行评价，但这2种数据存在时间不一致性和评估不准确性的缺点。为实现矿区生态环境的准确监测，以戈壁荒漠露天矿及其周边环境为研究对象，采用CFmask算法+Tmask算法获取纯净像元反射率。经时间序列模型合成研究区年度遥感数据，采用压力-状态-响应模型对其进行长时间序列生态环境评价。结果表明：①基于时间序列模型预测的地表反射率值与对应局部区域的卫星观测地表反射率值差异较小且其真彩色影像视觉差异较小，非纯净像元位置处预测反射率与周边纯净像元地表反射率真彩色影像视觉差异较小。以2022年各波段纯净像元反射率观测值与预测值验证精度，结果显示观测值与预测值显著相关(相关系数均大于0.6)。实地考察数据与经时间序列预测数据得到的生态环境指数的相关性(R²=0.450)优于单景生态指数(R²=0.347)、多景生态指数(R²=0.386)。② 2013—2021年研究区整体生态环境较差，呈南高北低、西高东低的空间格局，且随着时间增加，南部生态环境退化较为严重。矿区内生态环境变化较矿区外生态环境变化稳定，矿区外生态环境退化较快。③生态差、生态中、生态优面积的年变化速率分别为0.005/a、0.002/a、−0.007/a。各生态等级状况随时间呈现景观破碎度减小、景观异质性减小、聚合度增加态势，生态优斑块流向生态中、生态差斑块，生态差等级逐渐成为研究区生态环境主要生态等级。矿区内各等级占比稳定，矿区外生态差占比逐年增加。在对研究区进行生态修复时应尽量避免在半阳坡方向种植作物，且在阴坡、半阴坡、阳坡、半阳坡方向种植作物时均应避免坡度大于17.5°。

Single and multi-scene remote sensing data have been usually adopted to evaluate the ecological environment in mining areas, whereas these two types of data always presented the drawbacks of inconsistent time and inaccurate evaluation. To achieve the accurate monitoring of ecological environment in mining areas, the open-pit mine in Gobi desert and its surrounding environment was selected as the research object, and CFmask algorithm +Tmask algorithm were used to obtain pure pixel reflectance. The annual remote sensing data of study area was synthesized by the time series model, and then the pressure-state-response model was used for long-term ecological environment evaluation. The results show that: ① The difference between the predicted surface reflectance values based on time series model and the surface reflectance values observed by the satellite in the corresponding local area was small, while the difference between the true color image vision was relatively small. Meanwhile, the difference between the predicted reflectance value of the impeccable pixel position and the surface reflectance value of the surrounding pure pixel in true color image vision was small. The accuracy was verified by comparing the observed and predicted values of pure pixel reflectance of each band in the study area in 2022, and the results showed that the observed values were significantly correlated with the predicted values (with the correlation coefficients greater than 0.6). The correlation between the field investigation data and the ecological environment index obtained from the time series prediction data (R²=0.450) was better than that of the single-scene ecological index (R²=0. 347) and the multi-scene ecological index (R²=0.386).②From 2013 to 2021, the overall ecological environment of the study area was poor, presenting a spatial pattern of high in the south and low in the north, high in the west and low in the east. With the increasing time, the ecological environment in the south deteriorated more seriously. The change of ecological environment inside the mining area was more stable than that outside the mining area, with the ecological environment outside the mining area degenerating rapidly. ③The annual change rates of poor, moderate and superior ecological areas were 0.005 /a, 0.002/a and −0.007/a, respectively. The status of each ecological grade performed a trend of decreasing landscape fragmentation, decreasing landscape heterogeneity, and increasing convergence over time. The ecological superiority patch moved towards ecological medium and poor patches, and the ecological poor grade gradually became the main ecological grade of the ecological environment in the study area. The proportion of each grade within the mining area was stable, while the proportion of ecological poor level outside the mining area increased year by year. When ecological restoration would be conducted in the research area, crops planting should be avoided in the direction of semi-sunny slopes as much as possible. Moreover, it is recommended to avoid planting crops with slopes greater than 17.5°in the direction of shady slopes, semi-shady slopes, sunny slopes and semi-sunny slopes.