鄱阳湖赣江尾闾段藻类水华遥感反演及暴发机制

Key Points

• The aim is to clarify the mechanism behind algal blooms in the Ganjiang River and improve remote sensing accuracy.
• Utilized Sentinel-2/Landsat satellite data to analyze algal blooms.
• Applied an improved method integrating internal masking techniques with phytoplankton algal indices (FAI) and Otsu threshold method.
• Conducted factor analysis using a random forest regression model to identify driving factors for algal blooms.
• Algal blooms predominantly occur in late summer and early autumn, particularly in August and September.
• Significant spatial clustering of blooms noted in slow-flow areas along the southern and middle branches of the Ganjiang River.
• Daily maximum temperature showed a strong correlation with algal bloom area (47.1% contribution rate), outpacing other factors such as nutrients and wind speed.

Abstract