Supervised segmentation of NO2 plumes from individual ships using TROPOMI satellite data
Supervised segmentation of NO2 plumes from individual ships using TROPOMI satellite data
复制标题
使用 TROPOMI 卫星数据对单艘船舶的二氧化氮羽流进行监督分割
作者：
Solomiia Kurchaba;J. Vliet;F. Verbeek;J. Meulman;C. Veenman
航运业是氮氧化物-一种对人类健康和环境都有害的物质-最强的人为排放者之一。该行业的快速增长对控制船舶产生的排放水平造成了社会压力。目前用于船舶排放监测的所有方法都很昂贵，而且需要靠近船舶，这使得不可能进行全球和连续的排放监测。一个有希望的办法是应用遥感。研究表明，使用哥白尼哨兵5号前体（TROPOMI/S5 P）上的对流层监测仪器，可以从视觉上区分个别船只的一些NO2羽流。为了部署一个基于遥感的全球排放监测系统，需要一个自动化程序来估计单个船舶的NO2排放量。可用数据的极低信噪比以及缺乏地面真相使得这项任务非常具有挑战性。在这里，我们提出了一种方法，使用TROPOMI/S5 P数据上的监督机器学习对海船产生的NO2羽流进行自动分割。我们表明，所提出的方法导致超过20%的平均精度分数增加相比，在以前的研究中使用的方法和结果在0.834的高度相关性与理论推导的船舶排放代理。这项工作是朝着开发利用遥感数据进行全球船舶排放监测的自动化程序迈出的关键一步。
The shipping industry is one of the strongest anthropogenic emitters of NOx—a substance harmful both to human health and the environment. The rapid growth of the industry causes societal pressure on controlling the emission levels produced by ships. All the methods currently used for ship emission monitoring are costly and require proximity to a ship, which makes global and continuous emission monitoring impossible. A promising approach is the application of remote sensing. Studies showed that some of the NO2 plumes from individual ships can visually be distinguished using the TROPOspheric Monitoring Instrument on board the Copernicus Sentinel 5 Precursor (TROPOMI/S5P). To deploy a remote-sensing-based global emission monitoring system, an automated procedure for the estimation of NO2 emissions from individual ships is needed. The extremely low signal-to-noise ratio of the available data, as well as the absence of the ground truth makes the task very challenging. Here, we present a methodology for the automated segmentation of NO2 plumes produced by seagoing ships using supervised machine learning on TROPOMI/S5P data. We show that the proposed approach leads to more than a 20% increase in the average precision score in comparison to the methods used in previous studies and results in a high correlation of 0.834 with the theoretically derived ship emission proxy. This work is a crucial step towards the development of an automated procedure for global ship emission monitoring using remote sensing data.