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：凝结尾迹（condensation trails）是由飞机产生的线状冰云，很可能是航空业对气候变化影响的最大单一因素。避免凝结尾迹生成可能是一种低成本且显著减少航空气候影响的方法。自动化凝结尾迹检测系统是开发和评估凝结尾迹规避策略的关键工具。本文提出了一个人工标注数据集OpenContrails，用于基于GOES-16先进基线成像仪（ABI）数据训练和评估凝结尾迹检测模型。我们提出并评估了一种融合时间上下文信息以提高检测精度的凝结尾迹检测模型。该人工标注数据集及凝结尾迹检测结果已公开于谷歌云存储（地址：gs://goes_contrails_dataset）。