Accurate nearshore bathymetry estimation remains a critical challenge, impacting coastal forecasting evolution assessments through the inaccuracies in both in-situ and remote sensing surveys. This article introduces the Satellite Derived Bathymetry (SDB) temporal correlation method, showcasing its ability in deriving accurate nearshore bathymetry from one minute spaceborne videos. The approach utilises correlation of pixel intensity time series, shifted in time and space, extracted from a frame stack within a defined correlation window. The resulting correlation is then projected using the Radon Transform to infer wave characteristics (celerity and wavelength) for the estimation of depth through wave linear dispersion. Moreover, the adaptation of the correlation window based on a first wavelength estimation provided a more focused assessment of the wavefield that reveals morphological features such as sandbars in the bathymetric estimation. The method’s capabilities using adapted correlation window is illustrated through its application to a metric resolution Jilin satellite video (57 s at 5 Hz) along the Saint-Louis coast in Senegal. Through this demonstration, the temporal correlation method is among the first SDB methods to successfully capture the submerged sandbar along a beach. Comparison against in-situ measurements conducted three years prior to the video acquisition shows a good agreement with a bias of 0.97 m within the initial 2 km of the cross-shore profile. Furthermore, the application of previously developed sky-glint surface elevation analysis on video pixel intensity, prior to the bathymetry estimation, significantly reduces the bias to 0.44 m in the Saint-Louis estimation. This article highlights the potential applications of future Earth observation satellite missions that will capture image sequences (or videos) such as CO3D (CNES/Airbus).