Construction and application of the 3D geo-hazard monitoring and early warning platform
Abstract: As geo-hazard monitoring data increases in category and size, conventional geo-hazard information management systems, without a unified integration framework and visualized data display, are unable to satisfy the urgent needs of geo-hazard information management. Representational State Transfer (REST), a resource-centered service architecture, abstracts data and services into resources for unified Uniform Resource Identifier access, enabling it to take full advantage of HTTP with great flexibility and scalability. Based on the REST service architecture, this paper constructs a 3D geo-hazard monitoring and early warning platform with sound service compatibility and scalability by integrating geographical information, real-time monitoring data, and early warning models into the 3D Digital Earth framework. The platform displays topography, stratum lithology, and relevant information, as well as real-time monitoring data in a 3D visual, and provides early warning services for geo-hazards through access to real-time early warning models. As a result, it is capable of providing comprehensive information management, monitoring, and early warning of multiple geo-hazards, aiding decision-making in disaster prevention and mitigation, and enhancing the information level of geo-hazard prevention and mitigation work.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Construction and application of the 3D geo-hazard monitoring and early warning platform ; volume:13 ; number:1 ; year:2021 ; pages:1040-1052 ; extent:13
Open Geosciences ; 13, Heft 1 (2021), 1040-1052 (gesamt 13)
- Urheber
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Liu, Dunlong
He, Lei
Wu, Qian
Gao, Yan
Liu, Bin
Liu, Shuang
Luo, Han
- DOI
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10.1515/geo-2020-0293
- URN
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urn:nbn:de:101:1-2501051703354.116737990738
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:28 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Liu, Dunlong
- He, Lei
- Wu, Qian
- Gao, Yan
- Liu, Bin
- Liu, Shuang
- Luo, Han
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