Knowledge Graph Representation of Multi-Source Urban Storm Surge Hazard Information Based on Spatio-Temporal Coding and the Hazard Events Ontology Model
Gorde:
| Argitaratua izan da: | ISPRS International Journal of Geo-Information vol. 13, no. 3 (2024), p. 88 |
|---|---|
| Egile nagusia: | |
| Beste egile batzuk: | , , |
| Argitaratua: |
MDPI AG
|
| Gaiak: | |
| Sarrera elektronikoa: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Etiketak: |
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3002692608 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2220-9964 | ||
| 024 | 7 | |a 10.3390/ijgi13030088 |2 doi | |
| 035 | |a 3002692608 | ||
| 045 | 2 | |b d20240101 |b d20241231 | |
| 084 | |a 231472 |2 nlm | ||
| 100 | 1 | |a Xinya Lei |u The International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; <email>xiaolei@cug.edu.cn</email>; School of Computer Science, China University of Geosciences, Wuhan 430078, China; <email>yuewei.w@cug.edu.cn</email> (Y.W.); <email>weihan@cug.edu.cn</email> (W.H.); Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430078, China | |
| 245 | 1 | |a Knowledge Graph Representation of Multi-Source Urban Storm Surge Hazard Information Based on Spatio-Temporal Coding and the Hazard Events Ontology Model | |
| 260 | |b MDPI AG |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Tidal waves | ||
| 653 | |a Typhoons | ||
| 653 | |a Geographical coordinates | ||
| 653 | |a Hazards | ||
| 653 | |a Storm surges | ||
| 653 | |a Ontology | ||
| 653 | |a Floods | ||
| 653 | |a Hurricanes | ||
| 653 | |a Emergency response | ||
| 653 | |a Emergency preparedness | ||
| 653 | |a Knowledge representation | ||
| 653 | |a Coding | ||
| 653 | |a Weather hazards | ||
| 653 | |a Case studies | ||
| 653 | |a Storms | ||
| 653 | |a Knowledge | ||
| 653 | |a Graph representations | ||
| 653 | |a Disasters | ||
| 653 | |a Web Ontology Language-OWL | ||
| 653 | |a Temporal variations | ||
| 653 | |a Information processing | ||
| 653 | |a Graphical representations | ||
| 700 | 1 | |a Wang, Yuewei |u School of Computer Science, China University of Geosciences, Wuhan 430078, China; <email>yuewei.w@cug.edu.cn</email> (Y.W.); <email>weihan@cug.edu.cn</email> (W.H.); Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430078, China | |
| 700 | 1 | |a Han, Wei |u School of Computer Science, China University of Geosciences, Wuhan 430078, China; <email>yuewei.w@cug.edu.cn</email> (Y.W.); <email>weihan@cug.edu.cn</email> (W.H.); Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430078, China | |
| 700 | 1 | |a Song, Weijing |u The International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; <email>xiaolei@cug.edu.cn</email>; School of Computer Science, China University of Geosciences, Wuhan 430078, China; <email>yuewei.w@cug.edu.cn</email> (Y.W.); <email>weihan@cug.edu.cn</email> (W.H.); Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430078, China | |
| 773 | 0 | |t ISPRS International Journal of Geo-Information |g vol. 13, no. 3 (2024), p. 88 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3002692608/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3002692608/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3002692608/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |