Vegetation is essential for ecosystem function and sustainable urban development. In the context of urbanization, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), as the typical urban-dominated region, has experienced a remarkable increase in social and economic activities. Their impact on vegetation is of great significance but unclear, as interannual flow data and linear methods have limitations. Therefore, in this study, we used human and vehicle flow data to build and simulate the indices of mobile human activity. In addition, we used partial least squares regression (PLSR), random forest (RF), and geographical detector (GD) models to analyze the impact of mobile human activities on vegetation change. The results showed that indices of mobile human and vehicle flow increased by 1.43 and 7.68 times from 2000 to 2019 in the GBA, respectively. Simultaneously, vegetation increased by approximately 64%, whereas vegetation decreased mainly in the urban areas of the GBA. Vegetation change had no significant linear correlation with mobile human activities, exhibiting a regression coefficient below 0.1 and a weight of coefficients of PLSR less than 40 between vegetation change and all the factors of human activities. However, a more significant nonlinear relationship between vegetation change and driving factors were obtained. In the RF regression model, vegetation decrease was significantly affected by mobile human activity of vehicle flow, with an importance score of 108.11. From the GD method, vegetation decrease was found to mainly interact with indices of mobile human and vehicle inflow, and the highest interaction force was 0.82. These results may support the attainment of sustainable social-ecological systems and global environmental change.
Keywords: climate change; land use change; mobile human activities; nonlinear relationship; vegetation change.