Satellite-based Earth observations and numerical modeling for improved detection, assessment and forecast of natural hazards Natural hazards typically strike with little to no warning, frequently leading to considerable economic losses and fatalities worldwide. The scientific community anticipates that a changing climate will exacerbate the outcomes of these phenomena. Heavy rainfall that usually triggers landslides, for example, is already shifting in magnitude, frequency, and location. Open-source Earth Observations, machine learning, and other technological advances have proven useful for monitoring, studying, and developing methods that can help predict and evaluate hazard events at various scales. These methods have increasingly made it easier to sense spatial and temporal changes at local and regional scales with enhanced resolution and accuracy. In this talk, Dr. Cullen, an active member of the GEO programme, will discuss how Open-source data can help determine rainfall-triggered shallow landslides risk at large scales. Please see the abstract above. Authors and Affiliations – City University of New York/ GEO Track – Transition to FOSS4G Topic – FOSS4G implementations in strategic application domains: land management, crisis/disaster response, smart cities, population mapping, climate change, ocean and marine monitoring, etc. Level – 1 - Principiants. No required specific knowledge is needed. Language of the Presentation – English