This study uses the MODIS-Aqua satellite data provided by the National Aeronautics and Space Administration (NASA) and matches with the time and location of the chlorophyll-a concentration data measured by SeaBASS to select the satellite data time and observation area. The number of matched data is 924. Firstly, remote sensing reflectance (Rrs) is used to classify satellite remote sensing data into different water bodies, and then the best chlorophyll-a concentration algorithm is established. The results show that the mean percentage difference (MPD) in Case 2 water is 131.2% through comparing the percentage of chlorophyll-a provided by MODIS with the in-situ observations. In addition, the chlorophyll-a concentration of the new algorithm compared with the in-situ chlorophyll-a concentration are also calculated. The mean percentage difference in Case 2 water is 26.6%, and the average chlorophyll-a is 6.16 mg/m3 , which is much closer to the in-situ value,7.22 mg/m3 than the average chlorophyll-a of MODIS, 13.7 mg/m3. The chlorophyll-a concentration deduced by the new algorithm of this study is consistent with the in-situ values in Case 2 water, and it is much more convergent than the data of MODIS. Obviously, the new algorithm established in this study can be used to improve the chlorophyll-a concentration estimation results in Case 2 water. When the new algorithm is applied to calculate the chlorophyll-a concentration of the marginal Northwestern Pacific, the value is still higher than the offshore waters. Additionally, the chlorophyll-a concentration calculated by this new algorithm is lower than the value provided by MODIS, but the difference between them in the offshore waters is small. However, the algorithm of this study can improve the overestimation of the original MODIS value.