Integrated expression and analysis of urban flood disaster events from the perspective of multi-spatial semantic fusion

Abstract

With the escalating global climate changes and rapid urbanization, urban flood disasters have become more frequent and severe, hindering progress toward global sustainability goals. The rapid growth of information technology provides abundant data for disaster monitoring, but transitioning from static to dynamic and structured to heterogeneous data poses challenges for organized flood disaster information analysis. This study conducts an in-depth analysis of flood disaster components and spatiotemporal characteristics, exploring qualitative information expression in diverse contexts and quantitative dynamic analysis. Using dimensions like spatiotemporal, semantic, and hierarchical correlations, we introduce a multi-level, multi-dimensional “circumstance-event” model for flood disaster events. Leveraging proximity and semantic relationships, we establish a dynamic semantic association network among geographical units, supporting disaster circumstance division using semantic correlation graphs. Introducing bidirectional relationship discrimination, we enhance the traditional group evolution discovery method to determine the evolution of circumstances in consecutive time windows. Taking the “7·20” heavy rain in Zhengzhou, China as a case study, we observe significant improvement in circumstance division based on semantic correlation graphs, with an average modularity exceeding 0.745. Our bidirectional community evolution method reveals the evolution sequences of circumstances throughout the flood disaster period in Zhengzhou. This approach effectively organizes the entire flood disaster event lifecycle and dynamically analyzes event evolution, offering vital support for comprehensive disaster management.

Keywords

• Urban flood disaster
• Disaster circumstance
• Multidimensional space
• Integrated semantic expression
• Dynamic evolution analysis