文献类型：期刊文献

英文题名：Mobility Census for the analysis of rapid urban development

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

第一作者：Xiu, Gezhi

机构：[1] Institute of Remote Sensing, GIS, Peking University, China; [2] Institute of Space and Earth Information Science, The Chinese University of Hong Kong [CUHK], Hong Kong; [3] Centre for Complexity Science, Department of Mathematics, Imperial College London, United Kingdom; [4] Helmholtz Institute for Functional Marine Biodiversity [HIFMB], Oldenburg, Germany; [5] University of Oldenburg, Institute of Chemistry and Biology of the Marine Environment [ICBM], Oldenburg, Germany; [6] Alfred-Wegener Institute, Helmholtz Center for Marine and Polar Research, Bremerhaven, Germany; [7] Tourism College, Beijing Union University, China

第一机构：Institute of Remote Sensing, GIS, Peking University, China

年份：2022

外文期刊名：arXiv

收录：EI(收录号：20220469801)

语种：英文

外文关键词：Big data - Data mining

摘要：Traditionally urban structure and development are monitored using infrequent high-quality datasets such as censuses. However, human culture is accelerating and aggregating, leading to ever-larger cities and an increased pace of urban development. Our modern interconnected world also provides us with new data sources that can be leveraged in the study of cities. However, these often noisy and unstructured sources of 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 is produced as a byproduct of mobile communication, we show that meaningful features can be extracted, revealing for example the emergence and absorption of subcenters. In the future this method will allow the analysis of urban dynamics at a high spatial resolution (here, 500m) and near real-time frequency. ? 2022, CC BY.