天空中的简·雅各布斯：用开放的卫星数据预测城市活力
Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data
摘要：
人们整天都在城市地区，通常被称为“城市活力”，这是世界级城市最渴望的品质之一，但也是最难实现的品质之一。早在20世纪70年代，简·雅各布斯（Jane Jacobs）就提出了城市活力的理论，并发现促进城市生活需要四个条件：土地使用的多样性、小街区的大小、经济活动的混合以及人口的集中。为了建立这四个条件的代理，并最终大规模测试简·雅各布斯的理论，研究人员不得不从各种来源收集私人和公共数据，这花了几十年的时间。在这里，我们建议使用一个单一的数据来源，这恰好是公开的：哨兵-2卫星图像。特别是，由于前两个条件（土地利用的多样性和小块大小）在卫星图像中是肉眼可见的，我们测试了我们是否可以用最先进的深度学习框架自动提取它们，以及最终提取的特征是否可以预测生命力。在六个意大利城市，我们有呼叫数据记录，我们发现，我们的框架能够解释平均55%的城市活力的变化，从这些记录中提取。
英文摘要：
The presence of people in an urban area throughout the day -- often called 'urban vitality' -- is one of the qualities world-class cities aspire to the most, yet it is one of the hardest to achieve. Back in the 1970s, Jane Jacobs theorized urban vitality and found that there are four conditions required for the promotion of life in cities: diversity of land use, small block sizes, the mix of economic activities, and concentration of people. To build proxies for those four conditions and ultimately test Jane Jacobs's theory at scale, researchers have had to collect both private and public data from a variety of sources, and that took decades. Here we propose the use of one single source of data, which happens to be publicly available: Sentinel-2 satellite imagery. In particular, since the first two conditions (diversity of land use and small block sizes) are visible to the naked eye from satellite imagery, we tested whether we could automatically extract them with a state-of-the-art deep-learning framework and whether, in the end, the extracted features could predict vitality. In six Italian cities for which we had call data records, we found that our framework is able to explain on average 55% of the variance in urban vitality extracted from those records.
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。
