With the development of quantitative ocean color remote sensing, estimation of chlorophyll-a concentration in the coastal waters has aroused increasing attention from researchers. Currently, researches are confronted with difficulty in improving the accuracy of chlorophyll-a concentration estimation for turbid waters. Atmospheric correction, chlorophyll-a concentration modeling, and scale effect have already been identified as three critical factors affecting coastal water remote sensing. The in-depth exploration of them will accelerate the research progress of ocean color remote sensing. The ultimate objective of atmospheric correction and scale effect correction is to accurately estimate active constituents of turbid coastal waters in an optical way. Accordingly, the chlorophyll-a concentration modeling is a basic problem to be resolved, while atmospheric correction is the essential one. The scale effect problem arises during the modeling procedure where unrealistic homogeneous assumption is taken to measure chlorophyll-a concentration from the realistic non-homogeneous pixel. In the coastal remote sensing field, these three problems have become the most important topics in the current researches, and they will remain be the hot topics in the future.