Construction of Scientific Data Engineering System for Natural Disaster Emergency Response

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

Abstract

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

ZHANG Yaonan, TIAN Chenchen, REN Yanrun, KANG Jianfang, MIN Yufang, ZHANG Caihe, AI Minghao. Construction of Scientific Data Engineering System for Natural Disaster Emergency Response[J]. Frontiers of Data and Computing, 2024, 6(1): 46-56, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2024.01.005.

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References 33

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应急事件名称	下载次数（次）	下载数据量（TB）
2021/05/22青海省果洛州玛多县7.4级地震	14,537	197.9
2022/01/08青海省海北州门源县6.9级地震	28,905	1433.6
2022/03/17甘肃省张掖市肃南县5.1级地震	2,031	4.7
2022/03/26青海省海西州德令哈市6.0级地震	6,062	19.4
2022/06/01四川省雅安市芦山县6.1级地震	7,638	13.9
2022/06/10四川省阿坝州马尔康市6.0级地震	41,939	353.8
2022/08/18青海省大通县“8.18”山洪灾害	4,535	9.5
2022/09/05四川省甘孜州泸定县6.8级地震	48,124	358.1
2022/10/19青海省海西州茫崖市5.5级地震	4,371	9.9
2022/11/23 土耳其6.1级地震	2,927	19.7
2022/11/21 印度尼西亚爪哇岛5.5级地震	5,778	37.3
2023/01/30 新疆阿克苏沙雅县6.1级地震	1,844	8
2023/02/06 土耳其7.8级地震	13,935	156.6
2023/02/16菲律宾6.1级地震	2,964	7.5
2023/02/23 塔吉克斯坦7.2级地震	2,731	13.1
2023/03/22 阿富汗6.9级地震	893	3.4