Satellite optical imagery: towards fully integrated measurements of the coastal zone.

Space-based coastal observations are emerging as satellite imagery becomes more freely available through large-scale programs such as Landsat and Copernicus. Remote sensing techniques enable large-scale, even global, studies with sufficient spatio-temporal resolution, given that, for example, optical satellite imagery from the Sentinel-2 program has a global coastal coverage of up to 20 km offshore and a revisit of 2 to 5 days. The availability of data combined with accessible tools has enabled an explosion in space-based observations, even if these observations now go beyond the research phase alone and can support large-scale decision-making (see, for example, the Space Climate Observatory). However, most spaceborne applications for the coastal zone focus on useful but indirect proxy indicators such as waterline estimation. Submerged bathymetry and emergent topography are often not taken into account, even though they are essential for the usage and forecasting with of process-based models. Here, we present current work by the French Space Agency in collaboration with LEGOS and Shom on the future of space-based coastal observations: total, fully integrated monitoring of the coastal zone from space. This includes simultaneous measurements of bathymetry, coastline and topography at multiple spatial and temporal scales. Sentinel-2's large-scale bathymetry estimation and coastline detection, complemented by 3D topography using very high-resolution Pleiades images, offer a solution for monitoring the coastal zone from space over large regional scales. All these components of coastal monitoring are open-source, such as the CNES CARS routines for DEM 3D topography estimation, the CNES-IRD-SHOM S2SHORES bathymetry estimation. While focusing on current capabilities, we will also present prospects for future Earth observation missions, such as CO3D, and new capabilities for obtaining fully integrated measurements in a single satellite pass.