Chai Huabin, Zhao Yuqiao, Xu Hui, Xu Mingtao, Li Wanyin, Chen Lulu, Wang Zhan
School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China.
Sensors (Basel). 2024 Oct 11;24(20):6560. doi: 10.3390/s24206560.
As a major coal-producing area, the Shanxi section of the Yellow River Basin has been significantly affected by coal mining activities in the local ecological environment. Therefore, an in-depth study of the ecological evolution in this region holds great scientific significance and practical value. In this study, the Shanxi section of the Yellow River Basin, including its planned coal mining area, was selected as the research subject. An improved remotely sensed ecological index model (NRSEI) integrating the remotely sensed ecological index (RSEI) and net primary productivity (NPP) of vegetation was constructed utilizing the Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, and the Sen + Mann-Kendall analysis method was employed to comprehensively assess the ecological environment quality and its evolutionary trends in the study area. The findings in this paper indicate the following data: (1) The contribution of the first principal component of the NRSEI model is more than 70%, and the average correlation coefficient is higher than 0.79. The model effectively integrates the information of multiple ecological indicators and enhances the applicability of regional ecological environment evaluation. (2) Between 2003 and 2022, the ecological environment quality in the Shanxi section of the Yellow River Basin showed an overall upward trend, with the average NRSEI value experiencing phases of fluctuation, increase, decline, and stabilization. The NRSEI values in non-coal mining areas consistently remained higher than those in coal mining areas. (3) Over 60% of the areas have improved ecological conditions, especially in coal mining areas. (4) The impact of coal mining on the ecological environment is significant within a 6 km radius, while the effects gradually diminish in the 6 to 10 km range. This study not only offers a reliable methodology for evaluating ecological environment quality on a large scale and over a long time series but also holds significant guiding value for the ecological restoration and sustainable development of the Shanxi section of the Yellow River Basin and its coal mining area.
作为主要产煤区，黄河流域山西段的当地生态环境受到煤炭开采活动的显著影响。因此，深入研究该地区的生态演变具有重大的科学意义和实用价值。本研究选取黄河流域山西段（包括其规划的煤炭开采区）作为研究对象。利用谷歌地球引擎平台构建了一个改进的遥感生态指数模型（NRSEI），该模型整合了遥感生态指数（RSEI）和植被净初级生产力（NPP）。计算了2003年至2022年的NRSEI时间序列数据，并采用森 + 曼肯德尔分析方法全面评估研究区域的生态环境质量及其演变趋势。本文的研究结果表明如下数据：（1）NRSEI模型第一主成分的贡献率超过70%，平均相关系数高于0.79。该模型有效整合了多个生态指标的信息，提高了区域生态环境评价的适用性。（2）2003年至2022年期间，黄河流域山西段的生态环境质量总体呈上升趋势，平均NRSEI值经历了波动、上升、下降和稳定阶段。非煤炭开采区的NRSEI值始终高于煤炭开采区。（3）超过60%的区域生态状况得到改善，尤其是在煤炭开采区。（4）煤炭开采对生态环境的影响在半径6公里范围内显著，而在6至10公里范围内影响逐渐减弱。本研究不仅为大规模、长时间序列的生态环境质量评价提供了可靠的方法，而且对黄河流域山西段及其煤炭开采区的生态修复和可持续发展具有重要的指导价值。
