Evolution path identification and process analysis of surface vegetation-soil state in dryland system of China
As typical fragile ecosystems,dryland systems exhibit nonlinear evolution of their surface states,profoundly affecting ecological balance and human well-being.However,existing studies have yet to fully uncover their complex dynamic evolution processes.Based on monthly time-series products of vegetation and soil endmember fractions from 2001 to 2022,this study employs a trend and breakpoint detection algorithm based on discrete wavelet transform to identify the evolution paths of vegetation-soil states in dryland systems and analyze their dynamic changes.The results indicated that:①From 2001 to 2022,the fractions of photosynthetic vegetation and non-photosynthetic vegetation endmembers in China's dryland systems showed a significant increasing trend,while the fractions of soil endmembers exhibited a significant decreasing trend.②The sudden increase,A-shaped increase,and V-shaped increase state evolution paths for photosynthetic vegetation accounted for 9.9％,16.8％,and 21.9％of the total dryland area,respectively,while the corresponding state evolution paths for non-photosynthetic vegetation accounted for 9.1％,12.6％,and 28.8％,respectively.③Overall,vegetation restoration in dryland had promoted the reduction of soil exposure,but in local areas,water scarcity and human activities had led to vegetation degradation.This study provides a new perspective for understanding the surface state evolution and its response mechanisms in China's dryland systems and offers scientific evidence for land degradation monitoring and ecological restoration.
dryland systemsvegetation-soil stateendmember fractions time seriesdiscrete wavelet transformevolutionary path
万方数据
维普
