Analyzing Spatial-Temporal Change of Vegetation Ecological Quality and Its Influencing Factors in Anhui Province, Eastern China Using Multiscale Geographically Weighted Regression

Abstract

Vegetation is a crucial component of terrestrial ecology and plays a significant role in carbon sequestration. Monitoring changes in vegetation ecological quality has important guidance value for sustainable development. In this study, we investigated the spatial and temporal variation characteristics of Ecological Quality Index of Terrestrial Vegetation (EQI) in Anhui Province during the growing season from 2000 to 2020 using trend analysis, partial correlation analysis and bivariate spatial autocorrelation analysis. Based on the Multiscale Geographically Weighted Regression (MGWR), the spatial heterogeneity of the effects of average temperature, precipitation, elevation, slope, and human activity factors on EQI was explored. Our results showed an increasing trend in EQI during the growing season in Anhui Province from 2000 to 2020. The significantly increasing areas accounted for 43.49%, while the significantly decreasing areas accounted for 3.60%. EQI had a mostly positive correlation with precipitation and a negative correlation with average temperature (p p human activity > slope > average temperature > precipitation. MGWR results indicated that human activities and topographic factors had a stronger impact on EQI at the local scale, while climate factors tended to influence EQI at the global scale.

Keywords

• vegetation ecological quality
• spatial and temporal variation
• Google Earth Engine
• human activities
• bivariate spatial autocorrelation
• multiscale geographic weighted regression