Exploring the Urban Structure of Recreational Spaces through Residents’ Mobility Behavior Using Mobile Phone Signaling Data

With urban development taking the shape of a people-oriented approach, combinations of human behavior and physical spaces are under the spotlight of urban research. This study aims to explore the methodology of integrating residents’ recreational behaviors with the structure of urban physical spaces, thereby providing a reference for improving and optimizing existing recreational spaces. It delves into a method for identifying residents’ recreational activities through mobile phone signaling data. From the standpoint of recreational behaviors, this study establishes an analytical framework for the urban structure of recreational spaces, which encompasses activity intensity, space radiation capacity, and recreational–residential function structures. Employing Nanjing, China, for empirical analysis, the results are as follows: (1) The distribution of activity density is unbalanced, which displays a high degree of polarization in the downtown and a gradual decline from the downtown outward. (2) There is a lack of city-wide influential recreation center and a higher proportion of recreational activities occur in the subdistricts adjacent to residences. (3) The structural proximity of residential recreational functions is influenced by administrative divisions.

Authors

Institutions

Publication Details

Journal
Journal of Urban Planning and Development
Published
2025-03-28
DOI
https://doi.org/10.1061/jupddm.upeng-5191
Citations
2
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
4.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the Urban Structure of Recreational Spaces through Residents’ Mobility Behavior Using Mobile Phone Signaling Data

Angela Xiao Wu, L. Wang, Yan He
2 citations
Journal of Urban Planning and Development
Human Mobility and Location-Based Analysis
4.35
article

Exploring the Urban Structure of Recreational Spaces through Residents’ Mobility Behavior Using Mobile Phone Signaling Data

Angela Xiao Wu, L. Wang, Yan He
article en
2 citations

Abstract

With urban development taking the shape of a people-oriented approach, combinations of human behavior and physical spaces are under the spotlight of urban research. This study aims to explore the methodology of integrating residents’ recreational behaviors with the structure of urban physical spaces, thereby providing a reference for improving and optimizing existing recreational spaces. It delves into a method for identifying residents’ recreational activities through mobile phone signaling data. From the standpoint of recreational behaviors, this study establishes an analytical framework for the urban structure of recreational spaces, which encompasses activity intensity, space radiation capacity, and recreational–residential function structures. Employing Nanjing, China, for empirical analysis, the results are as follows: (1) The distribution of activity density is unbalanced, which displays a high degree of polarization in the downtown and a gradual decline from the downtown outward. (2) There is a lack of city-wide influential recreation center and a higher proportion of recreational activities occur in the subdistricts adjacent to residences. (3) The structural proximity of residential recreational functions is influenced by administrative divisions.

Journal of Urban Planning and DevelopmentVol. 151(2)
Southeast University (BD), Anhui University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 8%
Human Mobility and Location-Based Analysis
4.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.