Dynamic Monitoring of Ecological Environment Quality and Analysis on Its Driving Factors in Upper Reaches of Zhanghe River Basin During 2000—2020

Abstract

[Objective] The spatiotemporal variation characteristics of ecological environment quality and its driving factors in the upper reaches of Zhanghe River basin were analyzed in order to provide a scientific basis for ecological environment construction and management of the region. [Methods] The Landsat images of the upper reaches of Zhanghe River basin from 2000 to 2020 was optimized and reconstructed. Based on remote sensing ecological index (RSEI), three indicators of slope, normalized difference mountain vegetation index (NDMVI) and difference index (DI) were introduced to construct the advanced remote sensing ecological index (ARSEI) model considering the impact of topography and particulate matter. Spatial analysis and statistical methods were used to quantitatively evaluate the ecological environment quality of the study area. [Results] ① ARSEI has good applicability, and can accurately indicate the ecological environment quality in the upper reaches of Zhanghe River basin. NDMVI had the greatest influence on ARSEI, and DI was the least. ② The overall ecological environment quality showed a spatial pattern of "poor in southwest and excellent in northeast" , and the grades were mainly poor or moderate. During the study period, 35.94% of the regions showed improvement, mainly by one grade, of which the improvement from 2010 to 2020 was the most significant, and the change pattern was characterized by "overall stability and local change" . ③ The influence order of different types of factors was model factor > topography factor > meteorological factor > social factor > economic factor. All of the influence factors showed synergistic enhancement, and the interaction of NDSI, NDMVI and slope had the greatest influence on the spatial heterogeneity of ARSEI. [Conclusion] The average value of ARSEI in the upper reaches of Zhanghe River basin showed an overall increasing trend during 2000—2020, and the ecological environment quality was improved. The main driving factors for the change were NDMVI and slope.

Keywords

• advanced remote sensing ecological index
• ecological environment quality
• spatiotemporal variation
• driving factors
• upper reaches of zhanghe river basin