sea-ice-binary-ai4seaice

Scripts for training and evaluating semantic segmentation CNNs for water-ice classification of Sentinel-1 images

References

Please cite us!

The code in this repository was the main source for a sudy published as a peer-reviewed paper titled Model Ensemble With Dropout for Uncertainty Estimation in Sea Ice Segmentation Using Sentinel-1 SAR. The preprint is also available. The bibtex entry for the paper is below:

@ARTICLE{sea_ice_unc_2023,
  author={Pires de Lima, Rafael and Karimzadeh, Morteza},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={Model Ensemble With Dropout for Uncertainty Estimation in Sea Ice Segmentation Using Sentinel-1 SAR}, 
  year={2023},
  volume={61},
  number={},
  pages={1-15},
  doi={10.1109/TGRS.2023.3331276}
}

The uncertainty analysis for sea ice classification was only part of a series of published studies on machine learning for sea ice. Code in https://github.com/geohai/sea-ice-segment might also be of interest. Other than uncertainty analysis, we talked about:

• Enhancing sea ice segmentation in Sentinel-1 images with atrous convolutions (preprint)
• Comparison of Cross-Entropy, Dice, and Focal Loss for Sea Ice Type Segmentation (preprint)
• Deep Learning on SAR Imagery: Transfer Learning Versus Randomly Initialized Weights (preprint)

The bibtex entry for the publications above is listed below:

@ARTICLE{enhancing_sea_ice_2023,
    author = {Pires de Lima, Rafael and Vahedi, Behzad and Hughes, Nick and Barrett, Andrew P. and Meier, Walter and Karimzadeh, Morteza},
    title = {Enhancing sea ice segmentation in Sentinel-1 images with atrous convolutions},
    journal = {International Journal of Remote Sensing},
    volume = {44},
    number = {17},
    pages = {5344-5374},
    year = {2023},
    publisher = {Taylor & Francis},
    doi = {10.1080/01431161.2023.2248560},
}

@INPROCEEDINGS{comparison_sea_ice_2023,
  author={Pires de Lima, Rafael and Vahedi, Behzad and Karimzadeh, Morteza},
  booktitle={IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium}, 
  title={Comparison of Cross-Entropy, Dice, and Focal Loss for Sea Ice Type Segmentation}, 
  year={2023},
  pages={145-148},
  address = {Pasadena, CA, USA}
  doi={10.1109/IGARSS52108.2023.10282060}
}

@INPROCEEDINGS{tl_sea_ice_2023,
  author={Karimzadeh, Morteza and Pires de Lima, Rafael},
  booktitle={IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium}, 
  title={Deep Learning on SAR Imagery: Transfer Learning Versus Randomly Initialized Weights}, 
  year={2023},
  pages={1983-1986},
  address = {Pasadena, CA, USA}
  doi={10.1109/IGARSS52108.2023.10281892}
}