论文标题
移动性人口普查用于监测快速城市发展
Mobility Census for monitoring rapid urban development
论文作者
论文摘要
监测城市结构和发展需要高时空分辨率的高质量数据。尽管传统的人口普查为城市生活的人口和社会经济方面提供了基本的见解，但它们的步伐可能并不总是与城市发展的速度保持一致。为了补充这些传统方法，我们探讨了分析替代大数据源的潜力，例如人类流动性数据。但是，这些通常嘈杂和非结构化的大数据构成了新的挑战。在这里，我们提出了一种从此类数据中提取有意义的解释变量和分类的方法。使用北京的运动数据，这些数据是移动通信的副产品，我们表明可以提取有意义的特征，例如揭示，例如，子中心的出现和吸收。该方法允许以高空间分辨率（此处为500m）和接近实时频率以及高计算效率分析城市动态，这特别适合追踪事件驱动的移动性变化及其对城市结构的影响。
Monitoring urban structure and development requires high-quality data at high spatiotemporal resolution. While traditional censuses have provided foundational insights into demographic and socioeconomic aspects of urban life, their pace may not always align with the pace of urban development. To complement these traditional methods, we explore the potential of analyzing alternative big-data sources, such as human mobility data. However, these often noisy and unstructured big data pose new challenges. Here we propose a method to extract meaningful explanatory variables and classifications from such data. Using movement data from Beijing, which are produced as a byproduct of mobile communication, we show that meaningful features can be extracted, revealing, for example, the emergence and absorption of subcentres. This method allows the analysis of urban dynamics at a high spatial resolution (here, 500m) and near real-time frequency, and high computational efficiency, which is especially suitable for tracing event-driven mobility changes and their impact on urban structures.
