时间变化的GPS位移网络建模通过序列的蒙特卡洛模型
Suchanun Piriyasatit1,2, Ercan Engin Kuruoglu1,2, Mehmet Sinan Ozeren3
1Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China.
Entropy (Basel, Switzerland)
|April 26, 2024
概括
这项研究使用粒子过来分析GPS数据,揭示隐藏的网络动态和地面位移时间序列中的关系. 这种方法增强了对未来异常检测的地测观测的理解.
科学领域:
- 地测和地球物理学的地质学.
- 地震科学 地震科学 地震科学
背景情况:
- 高速全球定位系统 (GPS) 的时间序列数据使得毫米级地面变形建模成为可能.
- 目前的应用重点是地速度场和地震位移检测,留下固有的数据关系未被探索.
研究的目的:
- 开发GPS位移时间序列网络中的关系的时间变化分析.
- 揭示潜在的网络动态,并提高对地质观测的理解.
- 为改进关系分析引入图形表示.
主要方法:
- 序列的蒙特卡洛方法,特别是颗粒过 (PF).
- 多站GPS位移数据的时间变化分析.
- 图形表示用于网络关系可视化.
主要成果:
- 成功的参数跟踪澄清了GPS位移观测的动态.
- 使用来自2011年东北奥基地震的1赫兹GEONET GNSS数据证明了有效性.
- 在GPS时间序列网络中确定了以前未被探索的关系.
结论:
- 颗粒过为分析复杂的地理测量网络动态提供了一种新的方法.
- 拟议的图形表示有助于理解站际关系.
- 这些发现有可能在未来用于检测异常地面位移的应用.
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