OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI

Joe Yue-Hei Ng, Kevin McCloskey, Jian Cui, Vincent R. Meijer, Erica Brand +4 more
4/4/2023
cs.CV

No official code found. Best implementation: patmejia/contrails_vision (12 stars, MIT, last commit 2023-08-23).

Abstract

Contrails (condensation trails) are line-shaped ice clouds caused by aircraft and are likely the largest contributor of aviation-induced climate change. Contrail avoidance is potentially an inexpensive way to significantly reduce the climate impact of aviation. An automated contrail detection system is an essential tool to develop and evaluate contrail avoidance systems. In this paper, we present a human-labeled dataset named OpenContrails to train and evaluate contrail detection models based on GOES-16 Advanced Baseline Imager (ABI) data. We propose and evaluate a contrail detection model that incorporates temporal context for improved detection accuracy. The human labeled dataset and the contrail detection outputs are publicly available on Google Cloud Storage at gs://goes_contrails_dataset.

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Code Implementations(1)

patmejia/contrails_visionCommunity69%
MIT

Climate Analytics | contrail detection in GOES-16 imagery, aiding climate change mitigation. | Preprint: https://arxiv.org/abs/2304.02122

121PythonJun 24, 20233 years agoMIT

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Cite this paper

@article{ng2023opencontrails,
  title  = {OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI},
  author = {Joe Yue-Hei Ng and Kevin McCloskey and Jian Cui and Vincent R. Meijer and Erica Brand and Aaron Sarna and Nita Goyal and Christopher Van Arsdale and Scott Geraedts},
  year   = {2023},
  eprint = {2304.02122},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2304.02122v2}
}

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