PhaseNet-TF_Alaska

PhaseNet-TF Alaska: Advanced Seismic Arrival Time Detection

Model Description

PhaseNet-TF is an advanced deep learning model for automatic seismic phase picking (P-wave, S-wave, and PS-wave detection) using spectrogram-based image segmentation approaches. The model leverages DeepLabV3Plus architecture to detect seismic arrivals with high accuracy, especially for weak and noisy signals from ocean-bottom seismometers and weak phases such as slab interface refracted PS and SP waves. This Alaska version is specifically trained on the PS_Alaska dataset for P and S phases.

Available Versions

This repository contains two versions of the PhaseNet-TF Alaska model:

🔄 Iteration 1

• Model File: alaska_iter1.bin
• Config: config_iter1.json

🔄 Iteration 2

• Model File: alaska_iter2.bin
• Config: config_iter2.json

Model Architecture

• Backbone: DeepLabV3Plus with ResNet34 encoder
• Input: 3-component seismic waveforms converted to 6-channel spectrograms (real + imaginary)
• Output: Probability maps for P, S, PS phases and noise
• Sampling Rate: 40 Hz (dt_s = 0.025s)
• Window Length: 4800 points (120 seconds)
• Spectrogram Size: 64 × 4800 (frequency × time)
• Input Channels: 6 (3 real + 3 imaginary spectrogram channels)
• Output Classes: 4 (noise, P, S, PS)

Citation

If you use this model in your research, please cite:

@article{jie2026deep,
  title={Deep-Learning-Based Catalog of Background Seismicity and Aftershocks of the 2020--2021 Large Earthquakes Along the Alaska Peninsula},
  author={Jie, Yaqi and Wei, Songqiao Shawn and Zhu, Weiqiang and Freymueller, Jeffrey and Elliott, Julie},
  journal={Seismological Research Letters},
  volume={97},
  number={1},
  pages={187--203},
  year={2026},
  doi={10.1785/0220250072}
}

License

This model is licensed under the MIT License.