In recent years, there is a growing eutrophication of surface freshwaters. In many cases, this has resulted in an increase in the occurrence and persistence of cyanobacterial blooms, not only large lakes, but also in small reservoirs. There is an urgent need for new and better monitoring approaches. Satellite based remote sensing is one important and increasing accessible tool. However, the application of MODIS and other satellite data with low spatial resolution (about 500 m) but high temporal frequency was limited to larger lakes. While with higher spatial resolution satellite data (<30 m), such as Landsat-8, have longer return periods, making them less useful for blooms monitoring. This study explores the usage of the Chinese HJ-1A\B CCD and GF-1 WFV sensors, together with the United States Landsat-8 OLI and other high-resolution satellite data for joint observation of cyanobacteria blooms in a small reservoir (Yuqiao Reservoir,Tianjin). An algal extraction was developed for each satellite sensor, and the output of different satellite sensors was evaluated. The results indicate that:(1) the combined satellite monitoring provided consistent results when compared to the visual interpretation of multiband satellite images with a mean square root error and relative error of 0.78 km² and 4.9%; (2) different satellite sensors provided consistent results, with an accuracy of 99.5%; (3) According to the research in 2016, the water quality of Yuqiao Reservoir was eutrophic, and algal bloom was the most serious in the two seasons of summer and autumn. The use of combined observations of high-resolution data was an effective, alternative strategy for monitoring cyanobacterial blooms in small waterbodies, opening up new possibilities to improve monitoring of these important freshwater environments.