Automated Author Profile

Liu, Jianxiong

Hengyang Normal University

Current S-Index

2.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

2.0

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

76.9%

Average FAIR Score per dataset

Total Citations

1

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Monitoring long-term vegetation dynamics over the Yangtze River Basin, China, using multi-temporal remote sensing data (Version: 3)

Vegetation plays a crucial role in nature, with intricate interactions between it and the geographical environment. The Yangtze River Basin (YRB) refers to the third-largest river basin globally and an essential ecological security barrier in China. Monitoring vegetation dynamics in the basin is of profound significance for addressing climate change, soil erosion, and biodiversity loss in the basin’s ecosystems. Here, we investigate the spatiotemporal variations of vegetation at both the basin and land-cover scales in the YRB from 2000 to 2020. We elucidate the determinants driving the changes and explore future NDVI trends. The results indicate that NDVI in the YRB increased at a rate of 0.0032 yr−1 (P < 0.01) over the past 21 years, and it is anticipated to maintain an upward trend in the future. Regions in the upper and middle reaches of the YRB demonstrated higher NDVI, whereas regions in the headwater area and the lower reaches showed lower NDVI. Significant vegetation improvement was primarily concentrated in the central part of the basin, while noticeable vegetation degradation was observed in the eastern region. Temperature and wind speed were identified as the primary controlling factors affecting vegetation greenness. Global-scale climate oscillations played a significant role in driving periodic variations in NDVI, with La Niña events tending to increase NDVI, while El Niño events hindered its rise. Land cover types were influenced by long-term interactions between natural factors and human activities, although short-term vegetation variations might be more affected by the latter. Our findings provide valuable insights into the mechanisms behind vegetation variability driven by multiple variables, and the strong vegetation carbon sink capacity advances the conservation and development of ecosystems.

Authors

  • Fu, Jing ;
  • Liu, Jianxiong ;
  • Qin, Jianxin ;
  • Yang, Liguo ;
  • Zhang, Zhongbo ;
  • Deng, Yunyuan ;
  • Hu, Yong ;
  • Su, Baoling
1 Citation0 Mentions77% FAIR2.0 Dataset Index
10.5061/dryad.w3r2280zhFebruary 2024