Hazardous events such as floods, landslides, and other natural or anthropogenic disasters have posed significant challenges to public safety and territorial planning in Ecuador over the past decade. Understanding the spatial and temporal dynamics of such events is essential for effective risk management and the development of early warning systems. This paper presents a spatiotemporal analysis and predictive modeling framework for hazardous events in Ecuador, based on open government data from 2010 to 2023. Using a national-level dataset published by the Ecuadorian Secretariat for Risk Management, we explore the spatial, temporal, and categorical distribution of disaster-related incidents. We perform a comprehensive preprocessing pipeline, including temporal normalization, spatial discretization, and feature engineering. Our preliminary results highlight the viability of data-driven approaches in supporting early warning systems and guiding territorial planning efforts. The proposed methodology contributes to the development of more resilient and inclusive risk management strategies in Ecuador.