1.浙江省测绘科学技术研究院,浙江 杭州,311100
2.武汉大学资源与环境科学学院,湖北 武汉,430079
李东阳,高级工程师,研究方向为地理信息系统。10648340@qq.com
谢静静,硕士,工程师。2053068547@qq.com
收稿:2025-05-28,
纸质出版:2025-06-05
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李东阳,申淑娟,谢静静,等.灾害防御全信息管理模型及其应用——以浙江省为例[J].武汉大学学报(信息科学版),2025,50(6):1200-1209.
LI Dongyang,SHEN Shujuan,XIE Jingjing,et al.Full Information Management Model for Disaster Prevention and Its Application: A Case Study of Zhejiang Province[J].Geomatics and Information Science of Wuhan University,2025,50(6):1200-1209.
李东阳,申淑娟,谢静静,等.灾害防御全信息管理模型及其应用——以浙江省为例[J].武汉大学学报(信息科学版),2025,50(6):1200-1209. DOI:10.13203/j.whugis20250151
LI Dongyang,SHEN Shujuan,XIE Jingjing,et al.Full Information Management Model for Disaster Prevention and Its Application: A Case Study of Zhejiang Province[J].Geomatics and Information Science of Wuhan University,2025,50(6):1200-1209. DOI:10.13203/j.whugis20250151
灾害防御数据是灾害防御工作的基础性资源,针对灾害防御数据多源异构和时空多维等特征,研究创建了一种灾害防御全信息管理模式,构建了面向灾害防御的空间、时间、主题、环节、时效、部门六元组标签数据管理策略,实现海量灾害数据的特征提取和快速标记;研究了自适应业务链流转技术,跟随业务节点变更动态抓取相关数据,实现当前业务节点下灾害数据的自动流转与分析。基于此模型建立了浙江省灾害防御数据库,整合了16个部门、14大类、138小类数据,实现多源灾害数据的标准化管理和高效输出,支撑了浙江省自然灾害风险防控和应急救援平台的建设和运行。在2021年“烟花”台风、2022年“梅花”台风、2023年“杜苏芮”“卡努”台风等多次台风灾害防御过程中提供了有力支撑。应用成果表明,所提模型可高效组织全省域的灾害防御数据,实现每年5亿余条数据的管理和应用,为灾害防治提供了有效的技术支撑。
Objectives
2
Disaster prevention data is the fundamental resource for disaster prevention work. The rapid and accurate integration and management of disaster prevention data is an important research content in the field of disaster prevention. In view of the multi-source heterogeneity and spatiotemporal multi-dimensional characteristics of disaster prevention data
this paper studies and creates a full information management model for disaster prevention.
Methods
2
A six-tuple tag data management strategy of space
time
theme
link
timeliness and department for disaster defense has been constructed to achieve feature extraction and rapid marking of massive disaster data. Focusing on the six major business nodes of emergency preparedness
risk identification
risk assessment
risk control
emergency rescue
and post-disaster evaluation
the adaptive business chain flow technology was studied. Relevant data was dynamically captured following the changes of business nodes to achieve the automatic flow and analysis of disaster data under the current business nodes.
Results
2
Based on this model
this paper establishes the disaster prevention database of Zhejiang Province
integrates the data of 14 major categories and 138 minor categories from 16 departments
and forms the disaster reduction resource database
risk monitoring database
risk hazard database
model product database and case database. Based on the database and model
this paper builds the Zhejiang Province Natural Disaster Risk Prevention and Control and Emergency Rescue Platform
generating business data such as one map for disaster element analysis
disaster situation forecast map
and the five-color map of multi-disaster risk. It has provided strong support during the defense against multiple typhoon disasters
including Typhoon“Yanhua”in 2021
Typhoon“Minghua”in 2022 and Typhoons“Dusuri”and“Kanu”in 2023.
Conclusions
2
The application results show that this model can efficiently organize the disaster prevention data of the entire province
achieve the management and application of more than 500 million pieces of data every year
and provide effective technical support for disaster prevention and control.
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