Unsupervised learning (UL) has a long and successful history in untangling the complexity
of cities. As the counterpart of supervised learning, it discovers patterns from intrinsic data …

The growing ubiquity of location/activity sensing technologies and location-based services
(LBS) has led to a large volume and variety of location-based big data (LocBigData), such …

This study focuses on a mesoscale perspective to examine the structural and spatial
changes in the intercity mobility networks of China from three phases of before, during and …

The emergence of large-scale spatiotemporal trajectory data offers an excellent opportunity
to characterize collective human mobility patterns and their relationship with the urban built …

Mobile phone network data is a vital source for unveiling human mobility characteristics in
accordance with its large-scale spatiotemporal trajectory information. However, mobile …

ABSTRACT Urban Functional Zone (UFZ) identification is vital for urban planning, renewal,
and development. Point of Interest (POI), as one of the most popular data in UFZ studies, is …

Growing urbanization cause environmental problems such as vast amount of carbon
emissions and pollution all over the world. Smart Infrastructure and Smart Environment are …

近年来, 与人口流动相关的地理空间数据激增, 给定量研究人口流动模式创造了前所未有的条件,
生成了许多捕获和再现人口流动时空结构和规律的方法和模型, 为城市规划, 交通出行 …

Understanding intra-urban travel patterns through quantitative analysis is crucial for effective
urban planning and transportation management. In previous studies, a range of distribution …

The spatial pattern and mechanism of human flow are of great significance for urban
planning, economic development, transportation planning and so on. In this study, we used …