<p>Ocean remote sensing satellites provide observations with high spatiotemporal resolution. However, the influence of clouds, fog, and haze frequently leads to significant data gaps. Accurate and effective estimation of these missing data is highly valuable for engineering and scientific research. In this study, the radial basis function (RBF) method is used to estimate the spatial distribution of total suspended matter (TSM) concentration in Hangzhou Bay using remote sensing data with severe data gaps. The estimation precision is validated by comparing the results with those of other commonly used interpolation methods, such as the Kriging method and the basic spline (B-spline) method. In addition, the applicability of the RBF method is explored. Results show that the estimation of the RBF method is significantly close to the observation in Hangzhou Bay. The average of the mean absolute error, mean relative error, and root mean square error in all the experiments is evidently smaller than those of the Kriging and B-spline interpolations, indicating that the proposed method is more appropriate for estimating the spatial distribution of the TSM in Hangzhou Bay. Finally, the TSM distribution in the blank observational area is predicted. This study can provide some reference values for handling watercolor remote sensing data.</p>