数据与计算发展前沿 ›› 2024, Vol. 6 ›› Issue (1): 46-56.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.01.005

doi: 10.11871/jfdc.issn.2096-742X.2024.01.005

• 技术与应用 • 上一篇    下一篇

自然灾害应急响应科学数据工程体系建设

张耀南1,2,3,*(),田琛琛1,3,任彦润1,3,康建芳1,2,3,敏玉芳1,2,3,张彩荷1,3,艾鸣浩1,2,3   

  1. 1.国家冰川冻土沙漠科学数据中心,甘肃 兰州 73000
    2.甘肃省科学数据总中心,甘肃 兰州 73000
    3.中国科学院西北生态环境资源研究院,甘肃 兰州 73000
  • 收稿日期:2023-04-20 出版日期:2024-02-20 发布日期:2024-02-21
  • 通讯作者: * 张耀南(E-mail: yaonan@lzb.ac.cn
  • 作者简介:张耀南,中国科学院西北生态环境资源研究院研究员,博士生导师,国家冰川冻土沙漠科学数据中心主任,主要研究方向为地学数据工程及数据工程防灾减灾、基于高性能计算的地学模型模拟、遥感图像处理及多源数据融合。
    本文承担的工作为:算法设计,文章撰写,实验方案规划。
    负责论文初稿撰写与框架设计。
    ZHANG Yaonan is a research fellow and doctoral supervisor at the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, and director of National Cryosphere Desert Data Center. His main research interests are geological data engineering and data engineering for disaster prevention and mitigation, Geo-model simulation based on high performance computing, remote sensing image processing and multi-source data fusion.
    In this paper, he is responsible for the first draft of the dissertation and framework design.
    E-mail: yaonan@lzb.ac.cn
  • 基金资助:
    国家重点研发计划“冰冻圈大数据挖掘分析关键技术及应用”(2022YFF0711700);中国科学院咨询项目“数据工程学理论体系及应用战略研究”(CAS-WX2023ZX02-01);中国科学院信息化项目“中国科学院冰川冻土沙漠科学数据中心能力建设”(WX 145XQ07-10)

Construction of Scientific Data Engineering System for Natural Disaster Emergency Response

ZHANG Yaonan1,2,3,*(),TIAN Chenchen1,3,REN Yanrun1,3,KANG Jianfang1,2,3,MIN Yufang1,2,3,ZHANG Caihe1,3,AI Minghao1,2,3   

  1. 1. National Cryosphere Desert Data Center, Lanzhou, Gansu 73000, China
    2. Gansu Scientific Data Center, Lanzhou, Gansu 73000, China
    3. Northwest Institute of Eco-Environment and Resources Research, Chinese Academy of Sciences, Lanzhou, Gansu 73000, China
  • Received:2023-04-20 Online:2024-02-20 Published:2024-02-21

摘要:

【背景】我国自然灾害随全球气候变化呈现出多发、频发的复杂态势。建立快速、精准、高效的科学数据应急响应支持,是灾害应急救援管理、减少灾害损失、预防次生灾害的重要基础。【方法】国家冰川冻土沙漠科学数据中心自2015年开展印尼地震科学数据应急服务以来,基于科学数据资源与信息化技术,构建了多部门联动应急响应、多源数据接引聚合、多源数据融合集成、专题数据制备生产、应急响应数据组织、灾害演变分析、灾情程度评估、次生灾害评估预警、数据共享推送服务9个数据工程体系。【结果】初步形成了科学数据灾害应急响应服务平台,可实现灾害发生后24小时内迅速做出科学数据灾害应急响应服务。先后16次完成了国内甘肃张掖肃南,青海玛多、门源、茫崖、德令哈,四川马尔康、泸定、芦山,国际土耳其、阿富汗、塔吉克斯坦地震,以及青海大通山洪的科学数据应急响应服务,为灾害救援、灾情调查评估提供了科学数据支撑。【结论】创新了科学数据服务于防灾减灾的应用场景。截至2023年3月底,已有18.9万余人次下载了2.6 PB的应急科学数据,在支持灾害应急救援、灾情调查评估和灾害成因研究中取得了较好的应用成效。

关键词: 自然灾害, 科学数据应急响应服务, 数据工程体系, 专题数据制备生产, 应急响应服务平台

Abstract:

[Objective] Natural disasters in China have shown a complex situation of multiple and frequent occurrence with global climate change. Rapid, accurate, and efficient scientific data support is an important basis for making disaster emergency response plans, reducing disaster losses, preventing secondary disasters, and helping post-disaster reconstruction. [Methods] Since the National Cryosphere Desert Data Center (NCDC ) launched the scientific data emergency service for the Nepal earthquake in 2015, nine data engineering systems, including multidisciplinary linkage emergency response, multi-source data referral and aggregation, multi-source data fusion and integration, thematic data preparation, emergency data organization, disaster evolution analysis, disaster extent assessment, secondary disaster assessment and early warning, and data sharing and pushing services, have been implemented in NCDC. [Results] A scientific data emergency response service platform has been built to quickly provide data emergency response within 24 hours after a disaster, and has now completed 16 scientific data emergency response services for earthquakes in Sunan Zhangye, Gansu Province; Mado, Menyuan, Monya and Delingha in Qinghai Province; and Markang, Luding and Lushan in Sichuan Province, Turkey, Afghanistan, Tajikistan and Datong flash floods in Qinghai Province, providing scientific data support for disaster relief, disaster investigation and assessment, and post-disaster reconstruction. [Conclusion] This work makes innovation in the application scenario of scientific data for disaster prevention and mitigation. As of March 2023, more than 189,000 persons have downloaded 2.6PB of data and formed a good effect in these applications.

Key words: natural disaster, scientific data for emergency response service, data engineering system, thematic data preparation, emergency response service platform