From participation to data: collaborative mapping in the context of natural hazards and risks

Collaborative mapping has emerged as a key approach for collecting, analysing, and sharing geospatial information on natural hazards and risks. By integrating Citizen Science (CS) and Volunteered Geographic Information (VGI), it incorporates local knowledge, real-time observations, and crowdsourced data collection into risk assessment and management processes, where traditional data sources are limited or outdated. This study provides a systematic overview of collaborative mapping applications for natural hazards, including hydrogeomorphological (floods, landslides, coastal erosion), climate and weather related (storms and cyclones, wildfires, droughts and heat waves) and geophysical (earthquakes, tsunamis, volcanic eruptions) as well as multi-hazards contexts, examining how different terminologies, actor types, and technological approaches are represented across the literature. A total of 105 peer-reviewed studies were selected following a screening process based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, starting from major scientific databases. The results highlight an uneven distribution of research efforts, with a focus on floods and multi-hazard contexts. Furthermore, collaborative mapping is predominantly applied in mitigation, preparedness, and response phases. In terms of technologies, while traditional GIS-based methods dominate, computational approaches like Machine Learning (ML) are gaining traction. These approaches increasingly rely on the combined use of complementary geospatial sources: satellite and Unmanned Aerial Vehicle (UAV) imagery commonly serves as a basemap guiding the digitisation of features in OpenStreetMap (OSM), whose data are then extracted and integrated into hazard and risk analyses. This integration enables spatial datasets to be rapidly created and updated where authoritative data are scarce or outdated, thereby supporting disaster management across its different phases. By providing a structured synthesis of key elements, this review contributes to a better understanding of the current state of collaborative mapping in natural hazards and risks, identifies key gaps and directions for future research.