# OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI

arXiv: https://arxiv.org/abs/2304.02122 · HTML: https://mlsanity.com/paper/2304.02122/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 42 references that are in the map.
- First posted on arXiv 4 Apr 2023.

## Builds on (most cited first, 14 of 14)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://mlsanity.com/paper/1905.11946/) (2019)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1802.02611/) (2018)
- [Non-local Neural Networks](https://mlsanity.com/paper/1711.07971/) (2017)
- [Rethinking Atrous Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1706.05587/) (2017)
- [The Kinetics Human Action Video Dataset](https://mlsanity.com/paper/1705.06950/) (2017)
- [Deep Networks with Stochastic Depth](https://mlsanity.com/paper/1603.09382/) (2016)
- [Bag of Tricks for Image Classification with Convolutional Neural Networks](https://mlsanity.com/paper/1812.01187/) (2018)
- [Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks](https://mlsanity.com/paper/1711.10305/) (2017)
- [Revisiting ResNets: Improved Training and Scaling Strategies](https://mlsanity.com/paper/2103.07579/) (2021)
- [Deep learning in remote sensing: a review](https://mlsanity.com/paper/1710.03959/) (2017)
- [Graph-RISE: Graph-Regularized Image Semantic Embedding](https://mlsanity.com/paper/1902.10814/) (2019)
- [Evaluating Self and Semi-Supervised Methods for Remote Sensing Segmentation Tasks](https://mlsanity.com/paper/2111.10079/) (2021)

## Built on by (most cited first, 4 of 4)

- [GVCCS: A Dataset for Contrail Identification and Tracking on Visible Whole Sky Camera Sequences](https://mlsanity.com/paper/2507.18330/) (2025)
- [Flight Contrail Segmentation via Augmented Transfer Learning with Novel SR Loss Function in Hough Space](https://mlsanity.com/paper/2307.12032/) (2023)
- [Combining UPerNet and ConvNeXt for Contrails Identification to reduce Global Warming](https://mlsanity.com/paper/2310.04808/) (2023)
- [CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds](https://mlsanity.com/paper/2401.14486/) (2024)

## Abstract (arXiv)

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.