Advantages and potentials of SuperDove imagery for fine monitoring of suspended particulate matter in estuaries and tidal channels

• A highly accurate SPM retrieval model for SuperDove was developed. • The spectra and SPM of SuperDove were compared with those of OLI and MSI. • Effect of river lateral transport on SPM within tidal channels was revealed. • Impact of observation scales of common satellites on monitoring SPM was assessed. Suspended particulate matter (SPM) concentration is an essential biogeochemical parameter for water quality evaluation and morphodynamic researches. As the newest satellite in Planet family, SuperDove (SD) with eight spectral bands achieves observation to Earth with unprecedented temporal and spatial resolution. In this study, we developed a SPM retrieval model for SD using in-situ datasets in Yellow River Estuary, and compared the spectral and SPM products of SD with Sentinel-2 MSI and Landsat-8 OLI, and finally investigated SPM variations within typical tidal channels in recent years using multiple SD images. The results revealed that SPM concentrations derived from SD achieved high accuracy (R 2 = 0.95, Relative Percentage Difference = 30.69 %) based on our algorithm. While SD, MSI and OLI agreed well in terms of top-of-atmosphere reflectance, remote sensing reflectance and retrieved SPM concentrations, SD was able to effectively monitor SPM dynamics in tidal channels due to its higher spatial resolution. Several human-derived floods in recent years caused damage to the south embankment of Yellow River, resulting in lateral transport of high-SPM river water, which dramatically increased SPM concentration in the tidal channels and influenced the neighboring tidal channel networks through the newly developed fine trenches. Moreover, for commonly used satellite data, the spatial resolution of 3–30 m is required to characterize the details of SPM distribution, and the observation frequency of at least 1/1d is necessary to capture monthly change pattern of SPM, which demonstrated that SD imagery has great potential for monitoring SPM or other parameters in high-turbidity, strong-dynamic and small-scale waters.