The remote sensing retrieval of algal blooms in river systems is often interfered by the boundary effects of riparian wetlands, leading to limited accuracy with traditional methods in narrow water bodies. The tail-end section of the Ganjiang River, as a typical sensitive water area, has an unclear mechanism for algal bloom outbreaks. This study proposes an improved algorithm integrating the inward masking technique, coupling the Phytoplankton Absorption Index (FAI) with the Otsu method, effectively suppressing near-shore interference. Based on Sentinel-2/Landsat satellite data from 2019 to 2024, this study accurately extracts algal blooms in the tail-end section of the Ganjiang River. By combining remote sensing retrieval results with hydrological and meteorological data, the temporal and spatial distribution characteristics and outbreak mechanisms of algal blooms in this region were analyzed. The results indicate: (1) From 2019 to 2024, the scale of algal blooms showed an increasing trend with significant seasonality, peaking in late summer and early autumn (August and September), predominantly characterized by small-scale blooms. (2) Spatially, algal blooms were significantly concentrated in the near-shore slow-flow areas of the southern and middle branches of the Ganjiang River. The high-temperature heatwave weather during the late summer and early autumn low-flow period is the primary driving factor for the large-scale outbreak of algal blooms in this region.