| 甘肃省生态环境质量遥感评价及其驱动因子定量识别 |
| 摘要点击 736 全文点击 66 投稿时间：2024-06-19 修订日期：2024-08-03 |
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| 中文关键词 谷歌地球引擎（GEE） 遥感生态指数（RSEI） 趋势分析 驱动因子 未来预测 甘肃省 |
| 英文关键词 Google Earth Engine（GEE） remote sensing ecological index（RSEI） trend analysis driving factors future prediction Gansu Province |
| 作者 | 单位 | E-mail | | 康利刚 | 西北师范大学地理与环境科学学院, 兰州 730070 | 2369564480@qq.com | | 辛存林 | 西北师范大学地理与环境科学学院, 兰州 730070 | xincunlin@163.com | | 杨羽帆 | 陕西师范大学地理科学与旅游学院, 西安 710119 | | | 辛顺杰 | 兰州大学资源环境学院, 兰州 730000 | | | 王玉 | 西北师范大学地理与环境科学学院, 兰州 730070 | | | 陈宁 | 西北师范大学地理与环境科学学院, 兰州 730070 | | | 张博 | 西北师范大学地理与环境科学学院, 兰州 730070 | | | 朱珂冰 | 西北师范大学地理与环境科学学院, 兰州 730070 | | | 马新淑 | 西北师范大学地理与环境科学学院, 兰州 730070 | | | 陈红香 | 西北师范大学地理与环境科学学院, 兰州 730070 | |
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| 中文摘要 |
| 利用遥感技术科学评估甘肃省生态环境质量时空变化及环境响应，对生态环境保护政策实施和美丽甘肃建设至关重要. 基于GEE平台构建遥感生态指数（RSEI）从而动态评估21世纪以来甘肃省生态环境质量的变化，并结合Mann-Kendall与Pettitt检验确定其突变年份；在此基础上采用ArcGIS空间分析、数理统计、Theil-Sen Median联合Mann-Kendall趋势分析和变异系数等方法揭示生态环境质量时空分异规律和变化趋势；进而使用地理探测器与双变量Moran's I识别生态环境质量空间分异的关键驱动因子并将驱动作用可视化；最终借助Hurst指数预测生态环境质量未来走向. 结果表明：①甘肃省生态环境质量随年份增加呈不显著波动上升趋势（P>0.05），年际变化斜率为0.001 3 a-1，突变节点发生在2007年. 生态环境质量为优、良、中、较差和差的占地面积分别以132.03、1 273.44、93.70、1 375.66和63.83 km2·a-1的速度增加或减少. 生态环境质量空间分布呈现两极分化现象，自东南向西北逐渐变差. 生态环境质量存在一定的地形效应，随海拔上升呈先升后降，随坡度和地形起伏度上升而持续上升. ②甘肃省生态环境质量空间趋势以上升为主，其中不显著上升区域占比最大. 大部分区域生态环境质量稳定性较好，甘肃省南部最为稳定. ③植被覆盖度和降水量是甘肃省生态环境质量空间分异的首要驱动因子. 因子交互后解释力更强，以植被覆盖度∩海拔高度、植被覆盖度∩气温作用最显著. 生态环境质量在同一研究年份与不同驱动因子之间空间聚集差异明显，在不同年份与同一驱动因子之间空间聚集情况高度类似. ④预测未来甘肃省生态环境质量上升区域面积为18.02万km2，下降区域面积达24.41万km2. 研究成果可为甘肃省实现可持续发展和生态文明建设提供数据支撑. |
| 英文摘要 |
| Utilizing remote sensing technology to scientifically assess the spatial and temporal changes of ecological environment quality and environmental response in Gansu Province is crucial for the implementation of ecological environment protection policies and the construction of beautiful Gansu. Based on the google earth engine（GEE） platform， the remote sensing ecological index （RSEI） was constructed to dynamically assess the changes of ecological environment quality in Gansu Province since the 21st century， and the Mann-Kendall and Pettitt tests were combined to determine the year of mutation. On this basis， we used ArcGIS spatial analysis， mathematical statistics， Theil-Sen Median with Mann-Kendall trend analysis， and coefficient of variation to reveal the spatial and temporal variation patterns and trends of ecological quality； we then used geodetectors and the bivariate Moran's I to identify the key drivers of the spatial variation of the ecological quality and visualize the driving effects； finally， we used the Hurst index to predict the future direction of the ecological quality. The results show that： ① The ecological environment quality in Gansu Province showed a non-significant fluctuating upward trend with the increase in years （P>0.05）， the slope of the interannual change was 0.001 3 a-1， and the sudden change node occurred in 2007. The occupied areas with excellent， good， moderate， poor， and poor ecological environment quality increased or decreased at a rate of 132.03， 1 273.44， 93.70， 1 375.66， and 63.83 km2·a-1， respectively. The spatial distribution of the quality of the ecological environment showed a polarization phenomenon， with a gradual deterioration from the southeast to the northwest. The quality of the ecological environment had a certain topographical effect， which rose and then fell with the rise in altitude and continued to rise with the rise in slope and topographical relief. ② The spatial trend of ecological environmental quality in Gansu Province was mainly upward， with the largest proportion of areas with insignificant increase. The stability of ecological environment quality was good in most regions， and the southern part of Gansu Province was the most stable. ③ Vegetation cover and precipitation were the primary drivers of spatial heterogeneity of ecological environmental quality in Gansu Province. The explanatory power was stronger after factor interaction， with vegetation cover ∩ altitude and vegetation cover ∩ temperature playing the most significant roles. The differences in spatial aggregation of ecological environment quality between the same study year and different drivers were obvious， and the spatial aggregation between different years and the same driver was highly similar. ④ It is predicted that in the future， the ecological environment quality of Gansu Province will increase in the area of 18.02×104 km2 and decrease in the area of 24.41×104 km2， and the results of the research can provide data support for the sustainable development and ecological civilization construction in Gansu Province. |
