An event logic graph for geographic environment observation planning in disaster chain monitoring

Effective geographic environment observation planning is the key to obtain disaster monitoring and warning information. The previous researches can only make observation plans for a single disaster at some specific stages. They are difficult to apply to the dynamic evolution of the disaster chain. Timely and comprehensive geographic environment observation planning is urgently needed to provide high-value monitoring data for the identification and response of secondary disaster chains. Event logic graph (ELG) shows great potential in evolutionary law expression and chain event reasoning. Therefore, this study proposed an observation ELG (OELG), in which events and their logical relationships are modeled as nodes and edges to express the occurrence and development motivation of observation events. The disaster chain observation planning can be transformed into the reasoning of potential continuous observation events. Subsequently, an OELG-based geographic environment observation planning framework was proposed, which realizes the construction, instantiation, and plan reasoning of OELG. The observation planning experiment was carried out taking the flood disaster chain that occurred in Beijing, China and Nordrhein-Westfalen, Germany as examples. The results show that OELG can generate disaster chain observation plan more timely, comprehensively, and continuously than other models, thus providing support for disaster chain risk monitoring and emergency response.