文献类型：期刊文献

英文题名：Mobility census for monitoring rapid urban development

作者：Xiu, Gezhi[1,2];Wang, Jianying[3];Gross, Thilo[4,5,6];Kwan, Mei-Po[3];Peng, Xia[7];Liu, Yu[1]

第一作者：Xiu, Gezhi

通讯作者：Xiu, GZ[1];Xiu, GZ[2]

机构：[1]Peking Univ, Inst Remote Sensing & GIS, Beijing, Peoples R China;[2]Imperial Coll London, Dept Math, Ctr Complex Sci, London, England;[3]Chinese Univ Hong Kong CUHK, Inst Space & Earth Informat Sci, Hong Kong, Peoples R China;[4]Helmholtz Inst Funct Marine Biodivers HIFMB, Oldenburg, Germany;[5]Carl von Ossietzky Univ Oldenburg, Inst Chem & Biol Marine Environm ICBM, Oldenburg, Germany;[6]Alfred Wegener Inst, Helmholtz Ctr Marine & Polar Res, Bremerhaven, Germany;[7]Beijing Union Univ, Tourism Coll, Beijing, Peoples R China

第一机构：Peking Univ, Inst Remote Sensing & GIS, Beijing, Peoples R China

通讯机构：[1]corresponding author), Peking Univ, Inst Remote Sensing & GIS, Beijing, Peoples R China;[2]corresponding author), Imperial Coll London, Dept Math, Ctr Complex Sci, London, England.

年份：2024

卷号：21

期号：214

外文期刊名：JOURNAL OF THE ROYAL SOCIETY INTERFACE

收录：;EI(收录号：20242016083156);Scopus(收录号：2-s2.0-85192645238);WOS:【SCI-EXPANDED(收录号:WOS:001215388900002)】；

基金：No Statement Available

语种：英文

外文关键词：human mobility; manifold learning; cities

摘要：Monitoring urban structure and development requires high-quality data at high spatio-temporal resolution. While traditional censuses have provided foundational insights into demographic and socio-economic 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 analysing 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 by-product 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 500 m) 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.