Abstract Timely available landslide information is highly valuable for organizing emergency response activities and infrastructure restoration. The collection process for landslide information can benefit from the use of Earth observation (EO) data because they are capable of sensing potentially affected areas quickly and comprehensively. Challenges for an EO-based rapid landslide mapping service lie in developing a reliable and fast information provision process and in appropriate integration of landslide information products in the workflows and working environment of first responders. Our gap analysis for a developed pre-operational web service for EO-based landslide mapping identified a need to implement new components to meet these requirements. These comprise better linkage to the Copernicus data hub, increasing the degree of automation in the landslide information extraction process with machine learning technologies, and improving and testing user interaction with the service.