Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters

• An equation-based analytical method is developed to retrieve bottom reflectance. • The method simultaneously retrieves bottom reflectance in the blue and green bands without any auxiliary data. • Bottom reflectance can be retrieved accurately in both magnitude and shape. Under anthropogenic disturbances and global warming, coral reef ecosystems are degrading, and there is growing concern about the changes in benthic habitats in shallow coral reef waters. As an essential parameter, bottom reflectance can be used to indicate the health of benthic habitats in coral reefs. However, accurately determining bottom reflectance from satellite data remains challenging. This study presents an equation-based analytical method to estimate the bottom reflectance from high-spatial-resolution multispectral images in shallow coral reef waters by establishing two equations independent of bottom type and water depth. With the required parameters estimated from the sampling pixels of the multi-spectral image, the bottom reflectance data for the blue and green bands were derived by solving the two equations without a prior knowledge of bottom types, water properties, and water depths. To evaluate the method, simulated remote-sensing reflectance datasets from various combinations of the water properties, depths, and bottom types were used to derive the bottom reflectance. The root mean square errors (RMSEs) of the derived bottom reflectance in the blue band were generally <0.02 for most cases, except when the colored dissolved organic matter spectral absorption coefficient at the 440 nm wavelength [a CDOM (440)] was 0.1 m −1 and concentration of chlorophyll (C CHL ) was ≥0.5 μg/L. Comparatively, the lower RMSEs in the green band were observed only when a CDOM (440) < 0.05 m −1 , concentration of non-algal particles (C NAP ) < 0.25 mg/L, and C CHL < 0.5 μg/L. Furthermore, the proposed method was applied to the two real satellite multispectral images to derive the bottom reflectance. By visually comparing to the subsurface reflectance images and validating with the field-measured reflectance data, we demonstrated that the satellite derived bottom reflectance in the blue and green bands was accurate in both magnitude and shape by the proposed method. Finally, the impacts of the spatial inhomogeneity of the water properties, purity of sampling pixels for estimating the band ratio of the total diffused attenuation coefficients, and errors in the radiometric correction on the bottom reflectance retrieval were discussed and analyzed.