TKRM: A Formal Knowledge Representation Method for Typhoon Events

Ye, Peng; Zhang, Xueying; Shi, Ge; Chen, Shuhui; Huang, Zhiwen; Tang, Wei

doi:10.3390/su12052030

Cited by 11 publications

(9 citation statements)

References 52 publications

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“…Disaster is the product of the comprehensive effect of three factors: pregnant environment, causing factor, and disaster-bearing body [ 21 , 22 ]. For meteorological disasters, the pregnant environment refers to the comprehensive earth surface environment, composed of the atmosphere, lithosphere, and hydrosphere; causing factor refers to weather phenomena that may cause property loss, casualty, resource and environment damage, and social disorder; disaster-bearing body refers to the main bodies of human society that are affected and damaged by disasters, including human beings themselves and all aspects of social development [ 23 , 24 ].…”

Section: Basic Ideas Of Meteorological Disaster Process Monitoringmentioning

confidence: 99%

Remote Sensing Approaches for Meteorological Disaster Monitoring: Recent Achievements and New Challenges

2022

IJERPH

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Meteorological disaster monitoring is an important research direction in remote sensing technology in the field of meteorology, which can serve many meteorological disaster management tasks. The key issues in the remote sensing monitoring of meteorological disasters are monitoring task arrangement and organization, meteorological disaster information extraction, and multi-temporal disaster information change detection. To accurately represent the monitoring tasks, it is necessary to determine the timescale, perform sensor planning, and construct a representation model to monitor information. On this basis, the meteorological disaster information is extracted by remote sensing data-processing approaches. Furthermore, the multi-temporal meteorological disaster information is compared to detect the evolution of meteorological disasters. Due to the highly dynamic nature of meteorological disasters, the process characteristics of meteorological disasters monitoring have attracted more attention. Although many remote sensing approaches were successfully used for meteorological disaster monitoring, there are still gaps in process monitoring. In future, research on sensor planning, information representation models, multi-source data fusion, etc., will provide an important basis and direction to promote meteorological disaster process monitoring. The process monitoring strategy will further promote the discovery of correlations and impact mechanisms in the evolution of meteorological disasters.

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Section: Basic Ideas Of Meteorological Disaster Process Monitoringmentioning

confidence: 99%

Remote Sensing Approaches for Meteorological Disaster Monitoring: Recent Achievements and New Challenges

2022

IJERPH

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“…Contemporary knowledge graphs represent spatiotemporal knowledge as the attribute of elements and neglect the evolution and interaction mechanism (Huang et al, 2019). Based on this, we improve the conventional 'state-process' model (Figure 4), and apply it in the representation of geoscience knowledge (Ye et al, 2020(Ye et al, , 2021.…”

Section: Geoscience Knowledge Representation Modelmentioning

confidence: 99%

Geoscience Knowledge Graph (GeoKG): Development, construction and challenges

Zhang

Huang

Zhang

et al. 2022

Transactions in GIS

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Big earth data is a cross‐domain of geoscience and information science, which provides a novel perspective for solving geoscience problems. Most contemporary research is driven by data but neglect the potential value of knowledge. As a new scientific language in Geoscience, GeoKG is essential for understanding, representing, and mining geoscience knowledge, and can contribute to the integration of big earth data, geoscience knowledge, and geoscience models. However, research on GeoKG lack spatiotemporal perspectives in knowledge cognition, representation, acquisition and management. To this end, this article first outlines a cognitive mechanism from the human–machine double perspective and categorizes the characteristics and content of geoscience knowledge. To express evolution and complex natural rules, a knowledge representation framework is proposed through ‘state‐process’ and ‘condition‐result’ models. Aiming at multimodal data, a workflow is put forward to acquire knowledge from a small sample, a knowledge graph, a map, and a schematic diagram. Furthermore, we discuss the organization of GeoKG by improving existing data models, developing spatiotemporal correlation indexing and advancing knowledge graph completion. The concrete construction process of GeoKG is analyzed thoroughly in this study, which can support the synthetic analysis of big earth data, promote the development of knowledge engineering and provide a foundation for improving intelligent geoscience.

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“…The process needs to be embodied and captured through transitions between states. The state is a static slice in a continuous process under specific spatio-temporal condition [30].…”

Section: Multi-level Information Model Of Typhoon Eventsmentioning

confidence: 99%

Information Detection for the Process of Typhoon Events in Microblog Text: A Spatio-Temporal Perspective

Zhang

Huai

et al. 2021

IJGI

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Typhoon is one of the most destructive natural disasters in the world. Real-time information on the process of typhoon events serves as important reference for disaster emergency. In the era of big data, microblog text has been gradual applied to the prevention, preparation, response, and recovery of disaster management. However, previous studies mostly focused on the acquisition of different disaster information in microblog text, while ignoring the structural integration of this fragmented information, and thus cannot reflect the dynamic process of typhoon events. In this paper, a typhoon event information model (TEIM) considering the multi-granularity and dynamic characteristics of information is constructed from the spatio-temporal perspective. On the basis of extracting the information elements of typhoon events from microblog text, a process-oriented information aggregation method (TEPIA) is proposed to provide an ordered information resource for detecting the evolution process of typhoon events. Based on the case study of typhoon “Lekima” event using Sina Weibo, the results show that the method proposed in this paper can comprehensively detect the information of different objects on any spatio-temporal node during the process of typhoon events, which is beneficial to mining disaster emergencies in small scale from microblog text.

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TKRM: A Formal Knowledge Representation Method for Typhoon Events

Cited by 11 publications

References 52 publications

Remote Sensing Approaches for Meteorological Disaster Monitoring: Recent Achievements and New Challenges

Remote Sensing Approaches for Meteorological Disaster Monitoring: Recent Achievements and New Challenges

Geoscience Knowledge Graph (GeoKG): Development, construction and challenges

Information Detection for the Process of Typhoon Events in Microblog Text: A Spatio-Temporal Perspective

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