研究论文

基于多源信息融合与态势评估技术的信息预警实践

  • 徐晓锋 ,
  • 黄洁 ,
  • 张岩
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  • 兰州大学管理学院 兰州 730000
徐晓锋,副教授,博士,硕士生导师;黄洁,硕士研究生;张岩,青年研究员,博士,通信作者,E-mail:yanzh@lzu.edu.cn。

收稿日期: 2024-07-29

  修回日期: 2024-11-08

  网络出版日期: 2025-06-11

基金资助

本文系国家重点研发计划“地质灾害生态地质环境调查与生态问题识别诊断”(项目编号:2023YFC3007101)研究成果之一。

Information Early Warning Realization Based on Multi-Source Information Fusion and Situation Assessment

  • Xu Xiaofeng ,
  • Huang Jie ,
  • Zhang Yan
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  • School of Management, Lanzhou University, Lanzhou 730000
Xu Xiaofeng,associate professor,PhD,master supervisor;Huang Jie,master candidate;Zhang Yan,young researcher,PhD,corresponding author,E-mail:yanzh@lzu.edu.cn.

Received date: 2024-07-29

  Revised date: 2024-11-08

  Online published: 2025-06-11

Supported by

This work is supported by the National Key Research and Development Program of China, titled “Geological Hazard Ecological Geological Environment Investigation and Ecological Problem Identification and Diagnosis”(Grant No. 2023YFC3007101)

摘要

[目的/意义] 通过融合多维、多源时空分布特征的传感器数据与社会数据,构建延安县级区域的灾害精准预警模型,实现基层政府针对社会—自然耦合灾害的事前应急管理并提供决策依据。[方法/过程] 结合多源信息融合与态势评估的理论模型与案例构建,完善区域数字化技术的嵌入式预警信息架构,同时基于县域政府综合负面清单与短板识别的数字化治理,识别区域风险因子并叠加空间因子进行信息预警。[结果/结论] 只侧重于自然技术部分的风险信息治理与灾害智能识别效果有限,嵌入多维、多源、多模态信息技术并结合地方政府自然灾害防治政策等社会部分的刚性规制,能最大限度发挥新数字化技术及智能识别预警等防灾减灾与民生政策效应。

本文引用格式

徐晓锋 , 黄洁 , 张岩 . 基于多源信息融合与态势评估技术的信息预警实践[J]. 图书情报工作, 2025 , 69(12) : 76 -89 . DOI: 10.13266/j.issn.0252-3116.2025.12.007

Abstract

[Purpose/Significance] By integrating multi-dimensional and multi-source spatiotemporal data from sensors and social sources, this study develops an accurate disaster early-warning model for Yan’an county-level regions, which enables grassroots governments to implement pre-event emergency management and decision-making support for social-natural coupling disasters. [Method/Process] Integrating a theoretical model and case construction of multi-source information fusion and situation assessment, the study improved the embedded early warning information architecture with regional digital technology. At the same time, this study identified regional risk factors and overlaid spatial elements for information early warning through the digital governance of comprehensive negative lists and short-board recognition by county governments. [Result/Conclusion] Solely focusing on the effects of natural technical aspects on risk information governance and intelligent disaster identification is insufficient. Integrating multi-dimensional, multi-source, and multi-modal information, with the rigid regulations and control policies on natural disaster prevention proclaimed by local government, can maximize the efficacy of new digital technologies, intelligent identification, early warning, and disaster reduction and livelihood policies.

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