CLCYLGJan 12, 2025

Harnessing Large Language Models for Disaster Management: A Survey

arXiv:2501.06932v236 citationsh-index: 24ACL
Originality Synthesis-oriented
AI Analysis

It provides a taxonomy and analysis to guide the professional community in developing advanced LLMs for disaster management, which is an incremental contribution.

This paper presents a comprehensive survey of large language models (LLMs) applied to natural disaster management, addressing the lack of systematic review by categorizing existing works based on disaster phases and application scenarios.

Large language models (LLMs) have revolutionized scientific research with their exceptional capabilities and transformed various fields. Among their practical applications, LLMs have been playing a crucial role in mitigating threats to human life, infrastructure, and the environment. Despite growing research in disaster LLMs, there remains a lack of systematic review and in-depth analysis of LLMs for natural disaster management. To address the gap, this paper presents a comprehensive survey of existing LLMs in natural disaster management, along with a taxonomy that categorizes existing works based on disaster phases and application scenarios. By collecting public datasets and identifying key challenges and opportunities, this study aims to guide the professional community in developing advanced LLMs for disaster management to enhance the resilience against natural disasters.

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