方法对比

	Sendai Framework Indicator Monitoring	EM-DAT Disaster Database Analysis
领域	Disaster Studies	Disaster Studies
方法族	Process / pipeline	Process / pipeline
起源年份	2015	1988
提出者	United Nations Office for Disaster Risk Reduction (UNDRR)	Centre for Research on the Epidemiology of Disasters (CRED), UCLouvain
类型	Indicator-based monitoring framework for global disaster-risk-reduction targets	Database-driven descriptive and trend analysis of disaster occurrence and impact
开创性文献	United Nations Office for Disaster Risk Reduction (2015). Sendai Framework for Disaster Risk Reduction 2015-2030. UNDRR, Geneva.	Delforge, D., Wathelet, V., Below, R., Lanfredi Sofia, C., Tonnelier, M., van Loenhout, J. A. F., & Speybroeck, N. (2025). EM-DAT: the Emergency Events Database. International Journal of Disaster Risk Reduction, 124, 105509.
别名	Sendai Framework Monitor, Disaster Risk Reduction Target Monitoring, Sendai Indicators	EM-DAT Analysis, Emergency Events Database Analysis, Global Disaster Loss Data Analysis
相关	3	3
摘要	Sendai Framework indicator monitoring is the standardized methodology by which countries measure progress in reducing disaster risk under the Sendai Framework for Disaster Risk Reduction 2015-2030, adopted by United Nations member states and coordinated by UNDRR. The framework sets seven global targets — reducing disaster mortality, the number of affected people, direct economic loss, and damage to critical infrastructure and basic services, while increasing national and local risk-reduction strategies, international cooperation, and access to multi-hazard early warning. Progress against these targets is measured through 38 agreed indicators, populated from national disaster loss databases and policy records, normalized where appropriate by population or GDP, and compared against a 2005-2015 baseline. Reported through the Sendai Framework Monitor, the system makes disaster-risk reduction measurable and comparable across countries and links directly to indicators of the Sustainable Development Goals.	EM-DAT, the Emergency Events Database maintained by the Centre for Research on the Epidemiology of Disasters (CRED) at UCLouvain, is the most widely used global compilation of disaster occurrence and impact, and its analysis is a standard empirical method in disaster studies. The database records mass disasters from 1900 to the present according to explicit entry criteria, classifies each event by a natural or technological hazard taxonomy, and captures human and economic impacts — deaths, people affected, and damage. Analyzing EM-DAT means querying these records, adjusting economic losses for inflation and exposure, normalizing human impacts by population, and examining trends and patterns across hazard types, regions, and time. Because the data carry known inclusion thresholds and reporting biases, rigorous EM-DAT analysis is as much about understanding what the database can and cannot say as about the statistics themselves.