一个整合性框架,用于人工智能支持的沿海水力学监测和分析
Ruo-Qian Wang1, Gustavo Pacheco-Crosetti2, Christian Villalta Calderon2
1Department of Civil and Environmental Engineering, Rutgers, the State University of New Jersey, New Jersey, USA. rq.wang@rutgers.edu.
Scientific reports
|April 11, 2025
概括
气候变化威胁到海岸的海平面上升和风暴. 本研究介绍了一种先进的沿海危险监测系统,使用人工智能更好地识别和绘制水界,改善灾害准备.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 地理空间分析是什么
背景情况:
- 气候变化加剧了风暴和海平面上升等沿海危险.
- 发展不足的监测基础设施阻碍了有效的沿海管理.
- 迫切需要先进的,可适应的监控解决方案.
研究的目的:
- 为基础设施有限的地区引入创新的沿海危险监测系统.
- 使用先进技术评估沿海水域动态.
- 提高灾难准备能力和沿海抗灾能力.
主要方法:
- 集成分段任何模型 (SAM) 进行高分辨率图像分割.
- 动态模式分解 (DMD) 的应用用于沿海模式识别.
- 使用与数字海拔模型 (DEM) 结合的单块地板,用于准确地形绘制.
主要成果:
- 通过使用SAM成功识别了水陆边界,尽管图像扭曲和可变照明.
- 在复杂的地形中表现出强大的沿海绘图能力.
- 提供了沿海水域动态的全面评估.
结论:
- 开发的系统比传统的监测方法提供了实质性的改进.
- 先进的技术提高了对气候变化对海岸的影响的理解和管理.
- 这些发现对于可持续的沿海管理和防灾准备至关重要.
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