Work

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

Year: 2024

Type: article

Abstract: • Circumstances are divided using five types of elements in Zhengzhou city. • There are five main circumstance evolution processes during the “7·20″ incident. • Public opinion elements weaken the differentiation between circumstances. 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.

Source: International Journal of Applied Earth Observation and Geoinformation

DOI: 10.1016/j.jag.2024.104032

Authors: Shunli Wang, Rui Li, Huayi Wu

Institutions: Wuhan University, State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing

Language: English

Topic: Flood Risk Assessment and Management

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,820