| 利用GEE进行1990~2022年小江流域生态环境质量时空格局与演变趋势分析 |
| 摘要点击 1022 全文点击 254 投稿时间：2023-08-08 修订日期：2023-10-11 |
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| 中文关键词 生态环境质量 遥感生态指数（RSEI） GEE平台 小江流域 时空格局 趋势变化 |
| 英文关键词 ecological environment quality remote sensing ecological index （RSEI） GEE platform Xiaojiang River Basin spatial and temporal patterns trend change |
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| 中文摘要 |
| 云南省小江流域是长江上游生态修复示范区,评估和监测该区的生态环境质量是该区生态文明建设中一项非常重要的基础工作. 选取1990年、1995年、2000年、2005年、2010年、2014年、2018年和2022年的Landsat遥感影像数据,提取了绿度（NDMVI）、湿度（WET）、干度（NDBSI）和热度（LST）这4个指标,采用主成分分析法构建了遥感生态指数（RSEI）,利用GEE平台、ArcGIS 10.7平台和Python平台,结合地学信息图谱、变异系数、Mann-Kendall趋势检验、Sen's斜率估计和Hurst指数等分析方法,对1990~2022年间小江流域的生态质量时空格局和变化趋势进行分析. 结果表明：①研究区生态质量空间上具有较明显的地理分异性,到2022年生态质量等级为优、良的区域主要分布在高山植被覆盖较好的区域,生态质量较差的区域主要分布在地势相对较低的泥石流沟谷区域；时间尺度上,1990~2022年研究区的RSEI指数从1990年的0.41增长到2022年的0.55,生态环境质量整体呈波动改善趋势,平均增幅为0.048（10 a）-1,这与近些年该区大力开展的退耕还林、泥石流防治和水土保持、重金属污染治理等一系列生态建设工程密不可分. ②相较于NDVI指标,NDMVI对地形起伏区域的植被信息更加敏感,尤其是在阴影区域,能更准确定量描述植被信息,更适合用于高山峡谷区的绿度信息表达,从而使得RSEI更适用于高山峡谷区的生态质量评价；③小江流域RSEI变异系数平均值为0.202,生态环境质量整体的波动性较小,高波动主要集中在沿小江断裂带两侧的泥石流沟谷区域中,这些区域地表由裸露岩石、泥沙构成,容易受季节、气候和人为活动的影响；④该区生态环境质量上升面积占85.72%,下降面积占10.15%,未来变化趋势将以持续改善和未来退化为主,占比分别为44.75%和39.97%,因此,需要紧密监测处于退化潜在风险的区域. 研究结果可为小江流域进一步开展生态环境保护、治理和可持续发展工作提供理论依据. |
| 英文摘要 |
| Assessment and monitoring of the quality of the ecological environment in the area is a very important fundamental task in the development of ecological civilization in the Xiaojiang River Basin in Yunnan Province, which serves as a demonstration area for ecological restoration in the upper reaches of the Yangtze River. The Landsat remote sensing images from 1990, 1995, 2000, 2005, 2010, 2014, 2018, and 2022 were chosen, and the four indexes of greenness （NDMVI）, humidity （WET）, dryness （NDBSI）, and heat （LST） were extracted. The remote sensing ecological index （RSEI） was created using the principal component analysis method, then the spatial and temporal patterns and trends of ecological quality in the Xiaojiang River Basin between 1990 and 2022 were examined using the GEE platform, ArcGIS 10.7 platform, and Python platform, combining the analysis methods of geographic information mapping, coefficient of variation, Mann-Kendall trend test, Sen's slope estimation, and Hurst's index. The findings demonstrated that： ① the ecological quality of the study area had more obvious geographic differentiation spatially, and by 2022, the areas with excellent and good ecological quality grades were primarily distributed in the areas with better alpine vegetation cover, and those with poor ecological quality were primarily distributed in the areas of the mudslide ravines with relatively low terrain. On a time scale, the study area's RSEI index increased from 0.41 in 1990 to 0.55 in 2022, with a fluctuating overall trend of ecological quality improvement and an average increase of 0.048（10 a） -1； this progress was directly related to a number of ecological construction initiatives that have been energetically carried out, such as converting farms to forests, preventing mudslides, saving soil and water, managing heavy metal contamination, etc. ② The RSEI was more appropriate for the evaluation of ecological quality in alpine ravine areas because, in comparison to the NDVI index, the NDVMI adopted in this study was more sensitive to vegetation information in topographic undulation areas, especially in shaded areas, and could more accurately and quantitatively describe the vegetation information. ③ The RSEI in the Xiaojiang River Basin had a mean coefficient of variation of 0.202. Overall, its volatility was low, and its high volatility was mostly concentrated in the mudslide gully area along both sides of the Xiaojiang River fracture zone, where the surface was made up of bare rocks and sediment that was easily impacted by the changing of the seasons, the climate, and human activity. ④ The quality of the ecological environment in the region was significantly improving, with the rising area reaching 85.72% of the total area and the declining area accounting for approximately 10.15% of the total area. The future trend of change will be dominated by ongoing improvement and future degradation, accounting for 44.75% and 39.97%, respectively. It is important to pay close attention to areas that could potentially degrade. The findings of this study can serve as a theoretical foundation for additional ecological environmental conservation, management, and sustainable development in the Xiaojiang River Basin. |
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