Abstract: This paper uses the mid-August 2009 cyanobacteria blooms in East Lake as a case study to comparatively analyze three periods of the cyanobacteria bloom using HJ-1 satellite multi-spectral remote sensing data. Using RVI, NDVI and EVI index models to extract cyanobacteria information, we determined the thresholds of the three models using verified sampling points, then analyzed the accuracy of the three models and their discrimination of cyanobacteria blooms. The results show that HJ-1 remote sensing data can be used to quickly identify the range and extent of cyanobacteria blooms. Atmospheric correction highlighted the spectral difference of cyanobacteria and other features. The EVI method has high precision and can eliminate the interference of suspended solids such as sediment when assessing water quality, and it can be used for empirical detection of cyanobacteria in urban lakes.