Abstract
Vegetation is an important link between land, atmosphere, and water, making its changes of great significance. However, existing research has predominantly focused on long-term vegetation changes, neglecting the intra-annual variations of vegetation. Hence, this study is based on the Enhanced Vegetation Index (EVI) data from 2000 to 2022, with a time step of 16 days, to analyze the intra-annual patterns of vegetation changes in China. The average intra-annual EVI values for each municipal-level administrative region were calculated, and the time-series k-means clustering algorithm was employed to divide these regions, exploring the spatial variations in China’s intra-annual vegetation changes. Finally, the ridge regression and random forest methods were utilized to assess the drivers of intra-annual vegetation changes. The results showed that: (1) China’s vegetation status exhibits a notable intra-annual variation pattern of “high in summer and low in winter,” and the changes are more pronounced in the northern regions than in the southern regions; (2) the intra-annual vegetation changes exhibit remarkable regional disparities, and China can be optimally clustered into four distinct clusters, which align well with China’s temperature and precipitation zones; and (3) the intra-annual vegetation changes demonstrate significant correlations with meteorological factors such as dew point temperature, precipitation, maximum temperature, and sea-level pressure. In conclusion, our study reveals the characteristics, spatial patterns and driving forces of intra-annual vegetation changes in China, which contribute to explaining ecosystem response mechanisms, providing valuable insights for ecological research and the formulation of ecological conservation and management strategies.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Acknowledgements
Acknowledgement for the data support from Resource and Environment Science and Data Center, Chinese Academy of Sciences. (https://www.resdc.cn), Copernicus Climate Change Service Climate Data Store (https://cds.climate.copernicus.eu), and NASA EOSDIS LP DAAC (https://lpdaac.usgs.gov).
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This research was funded by the National Natural Science Foundation of China (grant number: 41871324), Key Laboratory Foundation of Nanchong (grant number: NCKJ201702) and Special Support Foundation of Young Teachers’ Research (grant number: 18D042).
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Funding acquisition, Mingliang Luo and Yong Wu; Methodology, ** Cheng; Supervision, Mingliang Luo and Yong Wu; Validation, Ke Chen and Jian Shun; Visualization, ** Cheng and Jian Shun; Writing—original draft, ** Cheng; Writing—review & editing, Yong Wu and Mingliang Luo. All authors have read and agreed to the published version of the manuscript.
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Cheng, X., Luo, M., Chen, K. et al. Intra-annual vegetation changes and spatial variation in China over the past two decades based on remote sensing and time-series clustering. Environ Monit Assess 196, 675 (2024). https://doi.org/10.1007/s10661-024-12816-7
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DOI: https://doi.org/10.1007/s10661-024-12816-7