从空间测量经济活动：使用飞行飞机和COVID-19的案例研究
Measuring economic activity from space: a case study using flying airplanes and COVID-19
摘要：
这项工作介绍了一种新的解决方案，通过遥感测量经济活动的范围广泛的空间区域。我们假设，由重大生活变化事件引起的人类行为干扰在卫星图像中留下了特征，从而可以设计相关的基于图像的指标来估计其影响并支持决策者。我们提出了一个案例研究的COVID-19冠状病毒爆发，造成严重的流动性限制，并造成全球范围内的中断，使用飞行飞机检测周围的30个最繁忙的机场在欧洲量化和分析封锁的影响和封锁后的恢复。我们的解决方案赢得了由欧洲航天局和欧盟委员会赞助的快速行动冠状病毒地球观测（RACE）升级挑战赛，现在集成了RACE仪表板。该平台结合了卫星数据和人工智能，以促进逐步和安全地重新开放基本活动。代码和CNN模型可在https://github.com/maups/covid19-custom-script-contest上获得
英文摘要：
This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas. We hypothesized that disturbances in human behavior caused by major life-changing events leave signatures in satellite imagery that allows devising relevant image-based indicators to estimate their impacts and support decision-makers. We present a case study for the COVID-19 coronavirus outbreak, which imposed severe mobility restrictions and caused worldwide disruptions, using flying airplane detection around the 30 busiest airports in Europe to quantify and analyze the lockdown's effects and post-lockdown recovery. Our solution won the Rapid Action Coronavirus Earth observation (RACE) upscaling challenge, sponsored by the European Space Agency and the European Commission, and now integrates the RACE dashboard. This platform combines satellite data and artificial intelligence to promote a progressive and safe reopening of essential activities. Code and CNN models are available at https://github.com/maups/covid19-custom-script-contest
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
