太原城市群生态环境质量监测及驱动力分析

刘晋; 陈天伟; 刘鹏; 贾相苹

doi:10.13961/j.cnki.stbctb.2023.04.019

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太原城市群生态环境质量监测及驱动力分析

试验研究

- 太原城市群生态环境质量监测及驱动力分析
- Monitoring and Analyzing Driving Forces of Ecological Environmental Quality in Taiyuan Urban Agglomeration
- 水土保持通报 2023年43卷第4期页码：154-161
- 作者机构：
  
  桂林理工大学测绘地理信息学院,广西,桂林,541006
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“地下管线多尺度几何语义建模研究”(41861050);广西壮族自治区自然科学基金项目“熵函数融合地统计原理构造格网DEM插值模型的研究”(2017GXNSFAA198308)
- DOI：10.13961/j.cnki.stbctb.2023.04.019
  中图分类号： X87;X821;X171.1
- 纸质出版：2023
- 稿件说明：
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刘晋, 陈天伟, 刘鹏, 等. 太原城市群生态环境质量监测及驱动力分析[J]. 水土保持通报, 2023,43(4):154-161.

Liu Jin, Chen Tianwei, Liu Peng, et al. Monitoring and Analyzing Driving Forces of Ecological Environmental Quality in Taiyuan Urban Agglomeration[J]. Bulletin of Soiland Water Conservation, 2023, 43(4): 154-161.
刘晋, 陈天伟, 刘鹏, 等. 太原城市群生态环境质量监测及驱动力分析[J]. 水土保持通报, 2023,43(4):154-161. DOI： 10.13961/j.cnki.stbctb.2023.04.019.

Liu Jin, Chen Tianwei, Liu Peng, et al. Monitoring and Analyzing Driving Forces of Ecological Environmental Quality in Taiyuan Urban Agglomeration[J]. Bulletin of Soiland Water Conservation, 2023, 43(4): 154-161. DOI： 10.13961/j.cnki.stbctb.2023.04.019.

摘要

[目的] 研究太原城市群2002—2021年生态环境质量变化状况，为城市可持续发展及绿色转型提供科学建议。[方法] 基于GEE平台与MODIS影像，利用主成分分析法耦合绿度、湿度、热度、干度构建生态遥感指数(RSEI)，结合稳定性分析、空间自相关分析研究太原城市群生态环境质量变化的空间性质，并利用地理探测器量化分析多种因子对RSEI的影响。[结果] 各年份第一主成分贡献率均高于75%，表明基于第一主成分提取RSEI能够综合表征研究区生态环境质量；2002—2021年，太原城市群生态环境质量总体呈现上升趋势，从0.433提高到0.488，增长率约为0.002 9/a。生态改善面积所占比例为17.1%，主要分布在西北部的岚县、静乐县；研究区生态环境质量变化存在明显空间自相关，Moran’I指数为0.729，高高集聚与低低集聚区域与生态改善、退化区域基本重合；太原城市群生态环境质量与气候因子中的相对湿度、气温、潜在蒸散量有显著相关性。[结论] 2002—2021年太原城市群生态环境质量得到改善，植被覆盖和城市扩张因素影响较大，RSEI能够有效监测研究区生态环境质量变化。

Abstract

[Objective] The changes in ecological environmental quality in the Taiyuan urban agglomeration from 2002 to 2021 were studied in order to provide scientific recommendations for sustainable urban development and green transformation. [Methods] We used the GEE platform

MODIS images

and principal component analysis to construct the ecological remote sensing index (RSEI) by coupling greenness

humidity

heat

and dryness. The spatial properties of ecological quality changes in the Taiyuan urban agglomeration were studied by using combining stability analysis and spatial autocorrelation analysis. The influence of various factors on RSEI was quantified by geographic detectors. [Results] The contribution rate of the first principal component was greater than 75% in all years

indicating that RSEI values extracted based on the first principal component could comprehensively characterize the ecological environmental quality in the study area. The ecological environmental quality of the Taiyuan urban agglomeration showed an overall upward trend from 2002 to 2021

increasing from 0.433 to 0.488

with a growth rate of about 0.0029/yr. The ecological improvement area accounted for 17.1%

mainly located in Lanxian County and Jingle County in the northwest. There was obvious spatial autocorrelation in the change of ecological environmental quality in the study area

and the Moran’s I index was 0.729. The high-high and low-low aggregation areas basically coincided with the ecological improvement and degradation areas

respectively. The ecological environmental quality of the Taiyuan urban agglomeration was significantly correlated with the climatic factors of relative humidity

air temperature

and potential evapotranspiration. [Conclusion] The ecological environmental quality of the Taiyuan urban agglomeration has improved from 2002 to 2021

and the vegetation coverage and urban expansion factors have had great impacts. RSEI can effectively monitor changes in the ecological environmental quality in the study area.

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