The Tibetan Plateau,the highest ecologically fragile region in the world,provides an ideal setting for studying vegetation change and its responses to environmental drivers;however,previous studies have focused on the direct effects of these drivers on vegetation change,with relatively few examining the interactions between the drivers and their indirect ef-fects.In this study,we selected southeast Tibet as the study area,calculated the kernel normalised difference vegetation index(kNDVI)on the Google Earth Engine platform,and analyzed the spatial and temporal changes of vegetation cover from 2000 and 2020,and the geo-detector method was used to analyze the direct effects of factors such as climate,topography,and hu-man activities on vegetation cover;and basing on the above studies,the partial least squares structural equation model(PLS-SEM)was introduced to explore the interaction between various factors and their direct and potential effects on vegetation.The results of the study showed on the whole,the vegetation cover of southeast Tibet was improved in 2000-2020,with 64.04％of the area showing an increasing trend.The main factors influencing the changes in vegetation cover involved elevation,air temperature and potential evapo-transpiration,with these factors explanatory power being over 50％of the variance;and the topographic factor had exerted a significant negative impact on vegetation change through its direct(-0.298)effect and potential(-0.437)effect resulting in a total effect of-0.735,becoming the most dominant influencing factor.
关键词
kNDVI/植被覆盖变化/驱动因子/地理探测器/PLS-SEM/藏东南地区
Key words
kNDVI/vegetation cover change/driving factors/geo-detector/PLS-SEM/southeast Tibet
维普
万方数据