NDVI based vegetation dynamics and responses to climate change and human activities at Xinjiang from 2001 to 2020 - Yuanbo Lu; Yang Yu; Lingxiao Sun; Chunlan Li; Jing He; Zengkun Guo; Li Duan; Jing Zhang; Ruide Yu (Scientific Reports)
Abstract As global climate change intensifies and human activity increases, the frequency and severity of droughts worldwide are escalating. In response, the Chinese government has implemented extensive afforestation efforts to combat ecological degradation, but their effectiveness in arid areas needs further evaluation. This study employed the Mann–Kendall (MK) trend test and correlation analysis to investigate the temporal and spatial dynamics of vegetation changes, as well as their association with climate factors, in Xinjiang from 2001 to 2020. The analysis was based on the normalized vegetation index (NDVI) and high-resolution meteorological data. Additionally, we assessed the potential effects of human activities on NDVI dynamics through residual analysis. The results indicate significant temporal and spatial heterogeneity in NDVI change in Xinjiang, with varying growth rates across different seasons and regions. While some regions showed a downward trend, a significant overall increase in NDVI was observed. High NDVI values were primarily found in mountainous regions, whereas low values were more common in plains. Temperature was the main climate factor influencing interannual, spring, and autumn NDVI changes, while precipitation was primarily associated with vegetation growth during summer and winter. Residual analysis revealed that human activities had contributed to vegetation degradation in certain regions, primarily in northern Xinjiang. However, overall vegetation change showed a positive trend, with human activities accounting for over 60% to NDVI changes across different periods and regions. These findings highlight the importance of considering the impact of human activities when developing vegetation restoration and conservation strategies to ensure the long-term sustainability of ecosystems.