Content area

Abstract

Coastal cities are increasingly vulnerable to urban storm surge hazards and the secondary hazards they cause (e.g., coastal flooding). Accurate representation of the spatio-temporal process of hazard event development is essential for effective emergency response. However, current knowledge graph representations face the challenge of integrating multi-source information with various spatial and temporal scales. To address this challenge, we propose a new information model for storm surge hazard events, involving a two-step process. First, a hazard event ontology is designed to model the components and hierarchical relationships of hazard event information. Second, we utilize multi-scale time segment integer coding and geographical coordinate subdividing grid coding to create a spatio-temporal framework, for modeling spatio-temporal features and spatio-temporal relationships. Using the 2018 typhoon Mangkhut storm surge event in Shenzhen as a case study and the hazard event information model as a schema layer, a storm surge event knowledge graph is constructed, demonstrating the integration and formal representation of heterogeneous hazard event information and enabling the fast retrieval of disasters in a given spatial or temporal range.

Details

1009240
Title
Knowledge Graph Representation of Multi-Source Urban Storm Surge Hazard Information Based on Spatio-Temporal Coding and the Hazard Events Ontology Model
Author
Xinya Lei 1   VIAFID ORCID Logo  ; Wang, Yuewei 2 ; Han, Wei 2   VIAFID ORCID Logo  ; Song, Weijing 1 

 The International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; [email protected]; School of Computer Science, China University of Geosciences, Wuhan 430078, China; [email protected] (Y.W.); [email protected] (W.H.); Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430078, China 
 School of Computer Science, China University of Geosciences, Wuhan 430078, China; [email protected] (Y.W.); [email protected] (W.H.); Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430078, China 
Volume
13
Issue
3
First page
88
Publication year
2024
Publication date
2024
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
22209964
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-03-11
Milestone dates
2023-11-06 (Received); 2024-03-06 (Accepted)
Publication history
 
 
   First posting date
11 Mar 2024
ProQuest document ID
3002692608
Document URL
https://www.proquest.com/scholarly-journals/knowledge-graph-representation-multi-source-urban/docview/3002692608/se-2?accountid=208611
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-04-29
Database
ProQuest One Academic