亚开行-快速洞察早期行动：大数据在基于影响的预测、即时预报和灾后损失评估中的作用（英）-2023.12-12页_701kb

ADB Brief No. 279: The Role of Big Data in Disaster Management

Key Points

Core Value & Benefits

• Enhanced Decision-Making: Big data enables rapid, cost-effective assessments for forecasting, nowcasting, and post-disaster damage evaluations, providing authorities with timely insights to mitigate disaster impacts and expedite relief efforts.
• Cost and Time Efficiency: Compared to traditional ground-based surveys, big data tools reduce the financial and temporal burdens of impact assessments, facilitating quicker resource allocation and response.
• Granular Insights: Earth observation, social media, and mobility data offer detailed socioeconomic and physical impact analyses, improving the relevance and accuracy of disaster response strategies.

Challenges & Risks

Access & Infrastructure

• Lack of regulatory frameworks for data access, especially from private sectors, restricts availability and sustainability of big data for disaster management.

Data Quality

• Biases in coverage (e.g., missing low-income populations), inaccuracies, and noise in big data compromise equity and reliability.

Capacity & Skills

• Limited technical expertise and infrastructure in developing nations hinder the effective processing and utilization of big data.

Privacy & Governance

• Risks of data misuse, privacy violations, and regional variations in data-sharing regulations create adoption barriers.

Governance & Recommendations

Data Access & Infrastructure

• Establish formalized agreements and standardized protocols for secure and sustained data sharing between providers and users.

Capacity Building

• Strengthen technical skills and invest in regional collaboration to enhance data processing capabilities and address human resource shortages.

Integration & Funding

• Embed big data tools into existing DRM frameworks and secure dedicated funds for tool development and implementation.

Policy & Regulation

• Develop clear regulatory policies, ensure transparency in data handling, and adopt anonymization techniques to mitigate privacy risks.

**End of Report Summary**