Paper Info
Title
Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns
Abstract
AbstractUnderstanding the stability of urban flows is critical for urban transportation, urban planning and public health. However, few studies have measured the stability of aggregate human convergence or divergence patterns. We propose a spatiotemporal model for assessing the stability of human convergence and divergence patterns. A mobile phone location data set obtained from Shenzhen, China, was used to assess the stability of daily human convergence and divergence patterns at three different spatial scales, i.e. points cell phone towers, lines bus lines and areas traffic analysis zones [TAZs]. Our analysis results demonstrated that the proposed model can identify points and bus lines with time-dependent variations in stability, which is useful for delineating TAZs for transportation planning, or adjusting bus timetables and routes to meet the needs of bus riders. Comparisons of the results obtained from the proposed model and the widely used entropy measure indicated that the proposed model is suitable for assessing the differences in stability for various types of spatial analysis units, e.g. cell phone towers. Therefore, the proposed model is a useful alternative approach of measuring spatiotemporal stability of aggregate human convergence and divergence patterns, which can be derived from the space–time trajectories of moving objects.
Year
DOI
Venue
2017
10.1080/13658816.2017.1346256
Periodicals
Keywords
Field
DocType
Convergence, divergence, human mobility, stability, mobile phone data
Convergence (routing),Data mining,Traffic analysis,Divergence,Computer science,Urban transportation,Urban planning,Location data,Mobile phone,Transportation planning
Journal
Volume
Issue
ISSN
31
11
1365-8816
Citations 
PageRank 
References 
4
0.41
18
Authors
5
Name
Order
Citations
PageRank
Zhixiang Fang18817.90
Xiping Yang283.55
Yang Xu3657.03
Shih-Lung Shaw434123.87
Ling Yin540.41