Monitoring and Analyzing Driving Forces of Ecological Environmental Quality in Taiyuan Urban Agglomeration

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.

Keywords

• taiyuan urban agglomeration
• ecological environmental quality
• rsei
• principal component analysis
• geodetector