| 引用本文: | 祁 帅,袁瑞强,薛 宇,等.基于改进遥感生态指数的黄河流域内蒙古段
生态环境质量监测及影响因素分析[J].灌溉排水学报,2025,44(10):133-144. |
| QI Shuai,YUAN Ruiqiang,XUE Yu,et al.基于改进遥感生态指数的黄河流域内蒙古段
生态环境质量监测及影响因素分析[J].灌溉排水学报,2025,44(10):133-144. |
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| 摘要: |
| 【目的】监测2000—2022年黄河流域内蒙古段生态环境质量，分析生态环境质量空间变化特征及影响因素。【方法】以2000—2022年长时序Landsat-5 TM、Landsat-8 OLI和Landsat-9 OLI2卫星遥感影像作为主要数据源，基于谷歌地球引擎（Google Earth Engine，GEE）利用核盐分遥感生态指数（KSRSEI）方法进行监测与分析黄河流域内蒙古段生态环境质量时空变化特征及影响因素。利用Theil-Sen结合Mann-Kendall分析生态环境质量趋势和变化特征，利用Hurst指数评估该地区生态环境质量动态的可持续性，利用重心转移模型进一步分析KSRSEI重心变化规律。最后通过对KSRSEI与气温、降水偏相关分析以及对土地覆盖类型进行统计分析进行研究区生态环境质量影响因素分析。KSRSEI使用kNDVI代替NDVI并加入综合盐度指数（CSI），与RSEI相比KSRSEI与实际生态系统密切相关，能够更好地监测和评估该区域的生态环境质量。【结果】黄河流域内蒙古段近23 a生态环境质量均值处于0.341 1~0.448 1，2000—2013年增速为0.031/10 a，2013—2022年下降速率为0.024/10 a。KSRSEI在空间分布上呈四周低中间沿黄区域高的空间分布格局，狼山、库布齐沙漠和毛乌素沙地等区域KSRSEI较低，且生态环境质量持续下降，而河套灌区、敕勒川平原、大青山一线和靠近吕梁山一侧等地区KSRSEI较高。黄河流域内蒙古段有13.55%的区域显著增加，13.56%的区域发生了明显地退化，72.89%的区域无显著变化。【结论】黄河流域内蒙古段气候趋于暖干化，KSRSEI对气候因子响应较强，对降水的响应强于对气温的响应。 |
| 关键词: 改进型遥感生态指数；谷歌地球引擎；时空变化分析；黄河流域内蒙古段 |
| DOI：10.13522/j.cnki.ggps.2025077 |
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| Spatiotemporal dynamics of ecological-environmental quality and its driving factors in the Inner Mongolia Section of the Yellow River Basin |
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QI Shuai, YUAN Ruiqiang, XUE Yu, DUAN Cheng, LIU Yan
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1. Institute of Geological Survey, Inner Mongolia Autonomous Region, Hohhot 010020, China;
2. School of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
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| Abstract: |
| 【Objective】The Inner Mongolia section of the Yellow River Basin is an ecologically fragile region that plays a critical role in environmental security of northern China. Long-term monitoring of its habitat quality and its underlying determinants is essential for effective ecological protection. This paper proposes a method to track the spatiotemporal changes of the ecological environment quality in the region from 2000 to 2022 and identify the primary drivers of the changes.【Method】Remote sensing data from Landsat-5 TM, Landsat-8 OLI and Landsat-9 OLI2 were used as the main data sources. Based on the Google Earth Engine (GEE) platform, a Kernel-based Salinity Remote Sensing Ecological Index (KSRSEI), which incorporates kNDVI and the Comprehensive Salinity Index (CSI), was proposed to calculate ecological and environmental quality. The Theil-Sen estimator and Mann-Kendall test were used to assess the temporal change of the environmental quality, and the Hurst index was used to evaluate ecological sustainability. A centroid shift model was applied to analyze the spatial displacement of ecological quality; partial correlation analysis of temperature and precipitation and land cover were used to identify influencing factors.【Result】Between 2000 and 2022, mean ecological environment quality values ranged from 0.341 1 to 0.448 1. The environmental quality in the region had improved at an average rate of 0.031/10 a from 2000 to 2013, followed by a decline from 2013 to 2022 at an average rate of 0.024/10 a. Spatially, ecological quality was the highest in the Hetao Plain, Daqing Mountains, and Lüliang Mountains, and the lowest in the Kubuqi Desert and Mu Us Sandy Land with persistent soil degradation. Overall, 13.55% of the study area saw significant improvement in environmental quality, 13.56% experienced significant decline, and 72.89% remained stable.【Conclusion】Ecological and environmental quality in the Inner Mongolia section of the Yellow River Basin is spatiotemporally heterogeneous, with precipitation being the most important influencing factor, underscoring the importance of climate in shaping ecosystem dynamics. These findings are helpful for ecological restoration, water management and sustainable land use in the region. |
| Key words: Kernel Salinity Remote Sensing Ecological Index(KSRSEI); Google Earth Engine; characteristics of spatial-temporal variation; the Inner Mongolia section of the Yellow River Basin |
