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.

翻译：OpenContrails：基于GOES-16 ABI的凝结轨迹检测基准测试 翻译后的摘要： 凝结轨迹（Contrails）是由飞机引起的线状冰云，可能是航空引起气候变化的最大贡献者。避免凝结轨迹可能是显著减少航空气候影响的一种具有潜力的低成本方法。自动化凝结轨迹检测系统是开发和评估凝结轨迹避让系统的必要工具。在本文中，我们提出了一个人类标注的数据集OpenContrails，用于基于GOES-16 Advanced Baseline Imager (ABI) 数据训练和评估凝结轨迹检测模型。我们提出并评估了一种基于时间上下文环境的凝结轨迹检测模型，以提高检测精度。人类标注数据集和凝结轨迹检测结果可以在 Google Cloud Storage 的 gs: //goes_contrails_dataset上公开访问。