Please use this identifier to cite or link to this item:
Title: Understanding the functionality of human activity hotspots from their scaling pattern using trajectory data
Authors: Jia, T 
Ji, Z
Keywords: Trajectory data
Human activity hotspots
Urban functionality
Bayesian inference model
Issue Date: 2017
Publisher: Molecular Diversity Preservation International (MDPI)
Source: ISPRS international journal of geo-information, Nov. 2017, v. 6, no. 11, 341 How to cite?
Journal: ISPRS international journal of geo-information 
Abstract: Human activity hotspots are the clusters of activity locations in space and time, and a better understanding of their functionality would be useful for urban land use planning and transportation. In this article, using trajectory data, we aim to infer the functionality of human activity hotspots from their scaling pattern in a reliable way. Specifically, a large number of stopping locations are extracted from trajectory data, which are then aggregated into activity hotspots. Activity hotspots are found to display scaling patterns in terms of the sublinear scaling relationships between the number of stopping locations and the number of points of interest (POIs), which indicates economies of scale of human interactions with urban land use. Importantly, this scaling pattern remains stable over time. This finding inspires us to devise an allometric ruler to identify the activity hotspots, whose functionality could be reliably estimated using the stopping locations. Thereafter, a novel Bayesian inference model is proposed to infer their urban functionality, which examines the spatial and temporal information of stopping locations covering 75 days. Experimental results suggest that the functionality of identified activity hotspots are reliably inferred by stopping locations, such as the railway station.
EISSN: 2220-9964
DOI: 10.3390/ijgi6110341
Rights: © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Jia, T., & Ji, Z. (2017). Understanding the functionality of human activity hotspots from their scaling pattern using trajectory data. ISPRS International Journal of Geo-Information, 6(11), 341 is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Jia_Human_Hotspots_Trajectory.pdf1.73 MBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents


Citations as of Dec 12, 2018


Last Week
Last month
Citations as of Dec 16, 2018

Page view(s)

Citations as of Dec 17, 2018


Citations as of Dec 17, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.