Spatiotemporal Monitoring of Cyanobacterial Blooms and Aquatic Vegetation in Jiangsu Province

Strategic Insights -

Scientists at China University of Geosciences have developed an automated monitoring system to track changes in freshwater ecosystems, primarily focusing on cyanobacterial blooms and aquatic vegetation in Jiangsu Province. The system integrates phenology-based algorithms with Sentinel-2 MSI imagery, utilizing the AI Earth (AIE) platform developed by Alibaba DAMO Academy. This research aims to provide quantitative evidence supporting adaptive lake restoration strategies and assess freshwater ecosystem health.

Key Takeaways:

  • The automated monitoring system was applied to 12 ecologically sensitive lakes and reservoirs in Jiangsu Province, China, enabling multi-year tracking of spatiotemporal changes from 2019 to 2024.
  • A clear north-south gradient in cyanobacterial bloom intensity was observed, with southern lakes exhibiting higher bloom levels, while ecological restoration efforts in Cheng and Yuandang Lakes led to substantial increases in bloom intensity in 2024.
  • Aquatic vegetation dynamics displayed contrasting trends, with southern lakes experiencing significant increases in vegetation coverage, while northern lakes experienced long-term declines.
  • By 2024, compared to 2019, vegetation coverage in Gaoyou, Luoma, and Hongze Lakes decreased by 11.28%, 16.02%, and 47.32%, respectively.
  • These declines are likely linked to increased grazing pressure following fishing bans, which may have disrupted vegetation dynamics and reduced their ability to suppress cyanobacterial blooms.
  • The research provides quantitative evidence supporting adaptive lake restoration strategies and underscores the effectiveness of satellite-based phenological monitoring in assessing freshwater ecosystem health.

Statistics:

  • 12 lakes and reservoirs in Jiangsu Province, China, were monitored using the automated system.
  • The system tracked changes from 2019 to 2024, with a total of 6 years of data collected.
  • Cyanobacterial bloom intensities were recorded in the following lakes:

+ Southern lakes: averages ranged from 25.17% to 44.56% (2019-2024).

+ Northern lakes: averages ranged from 0.35% to 3.29% (2019-2024).

  • Vegetation coverage in southern lakes increased significantly, with Changdang Lake reaching 44.56% in 2024.
  • Vegetation coverage in northern lakes decreased by:

+ Gaoyou Lake: 11.28% (2019-2024).

+ Luoma Lake: 16.02% (2019-2024).

+ Hongze Lake: 47.32% (2019-2024).

Sources:

  • Spatiotemporal Monitoring of Cyanobacterial Blooms and Aquatic Vegetation in Jiangsu Province Using AI Earth Platform and Sentinel-2 MSI Data (2019-2024). Remote Sensing, 2025,17(13):2295. (Remote Sensing - http://www.mdpi.com/journal/remotesensing/).
  • China University of Geosciences, School of Water Resources and Environment, Beijing 100083, People's Republic of China.
  • Xin Xie, China University of Geosciences; Ting Song; Ge Liu; Tiantian Wang; Qi Yang.