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- Title
Intra-annual vegetation changes and spatial variation in China over the past two decades based on remote sensing and time-series clustering.
- Authors
Cheng, Xi; Luo, Mingliang; Chen, Ke; Sun, Jian; Wu, Yong
- 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.
- Subjects
CHINA; VEGETATION dynamics; SPATIAL variation; REMOTE sensing; REGIONAL economic disparities; DEW point; REGIONAL disparities; TIME series analysis
- Publication
Environmental Monitoring & Assessment, 2024, Vol 196, Issue 7, p1
- ISSN
0167-6369
- Publication type
Article
- DOI
10.1007/s10661-024-12816-7