基于深度学习的研究,评估和增强地质灾害应急疏散能力的战略,在长白山北景区的长白山北景区
Erzong Zheng1, Yichen Zhang2, Jiquan Zhang3
1College of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130021, China.
Scientific reports
|December 27, 2024
概括
这项研究使用先进的人工智能增强了长白山的地质灾害疏散能力. 它提高了远程传感图像清晰度,并计算了疏散时间,以便更好地规划安全.
科学领域:
- 地理空间分析是什么?
- 灾害管理 灾害管理
- 环境科学中的人工智能
背景情况:
- 由于数据限制,传统的疏散模型不适合风景区.
- 像长白山这样的风景区需要专门的应急规划方法.
- 地质灾害对旅游目的地构成重大风险.
研究的目的:
- 评估长白山北方风景区的紧急疏散能力.
- 在地质灾害发生时,制定改善疏散效率的策略.
- 解决风景区域评估中的数据采集和精度挑战.
主要方法:
- 利用现实增强超分辨率生成对抗网络 (Real-ESRGAN) 进行高分辨率遥感图像处理.
- 采用图形卷积网络 (GCN) 模型来计算点特定的紧急疏散时间.
- 开发了一个指标系统 (有效性,可访问性,安全性) 来评估拟议的改进策略.
主要成果:
- 成功提高了远程传感图像清晰度,克服了传统的局限性.
- 提供了对整个风景区疏散能力的全面评估.
- 确定了需要改进紧急疏散基础设施的特定区域.
- 通过科学指标系统验证了提议的增强战略的可行性.
结论:
- 综合的Real-ESRGAN和GCN方法大大提高了风景区的数据处理和评估准确性.
- 该研究为长白山地质灾害管理和应急规划提供了关键支持.
- 拟议的战略提供了一种基于科学的方法,以提高风景区的安全性和弹性.
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