The European Copernicus Coastal Flood Awareness System (ECFAS) project will contribute to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS will provide a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits. The ECFAS Proof-of-Concept development will run from January 2021-December 2022. The ECFAS project is a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and is funded by the European Commission H2020 Framework Programme within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. This project has received funding from the European Union’s Horizon 2020 programme Description of the containing files. GUIDE 03: MAPPING PRODUCTS AND SHORELINE ANALYSIS includes a brief description of the Mapping components of ECFAS that were developed to (i) improve the efficiency and performance of Copernicus Emergency Management Service (CEMS) On-Demand Mapping component through the provision of forecasted flood extent and impact layers in support of image analysis; (ii) implement new coast-targeted product such as the observation of shoreline displacements (beach erosion impact) in the aftermath of a storm event and beach recovery analysis using Sentinel 2 and Landsat 8-9 satellite images. Disclaimer: ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided. This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211