Quantifying and Characterizing Urban Leisure Activities by Merging Multiple Sensing Big Data: A Case Study of Nanjing, China

Shaojun Liu,Hao Liu,Yao Long,Ling Zhang

doi:10.3390/land10111214

Abstract

Studying the spatiotemporal pattern of urban leisure activities helps us to understand the development and utilization of urban public space, people’s quality of life, and the happiness index. It has outstanding value for improving rational resource allocation, stimulating urban vitality, and promoting sustainable urban development. This study aims at discovering the spatiotemporal distribution patterns and people’s behavioral preferences of urban leisure activities using quantitative technology merging ubiquitous sensing big data. On the basis of modeling individual activity traces using mobile signaling data (MSD), we developed a space-time constrained dasymetric interpolation method to refine the urban leisure activity spatiotemporal distribution. We conducted an empirical study in Nanjing, China. The results indicate that leisure plays an essential role in daily human life, both on weekdays and weekends. Significant differences exist in spatiotemporal and type selection in urban leisure. The weekend afternoon is the breakout period of leisure, and entertainment is the most popular leisure activity. Furthermore, the correlation between leisure resource allocation and leisure activity participation was argued. Our findings confirm that data-driven approaches would be a promising method for analyzing human behavior patterns; therefore, assisting in land planning decisions and promoting social justice and sustainability.

Highlights

Leisure activities refer to the behaviors performed for pleasure, relaxation, and other emotional benefits [1]
5.1 CAonstrciobmutpioanrsedanwd iFthintdhinegsstate-of-the-art research, this study extended the methods to measAursecuormbapnarleeidsuwreitshptahcee astnadted-oisfc-othvee-ratrhteredsyenaarcmhi,ctphaisttsetrundsyofepxeteonpdlee’ds pthaertimcieptahtoiodns itno measure urban leisure space and discover the dynamic patterns of people’s participation urban leisure activities
We propose an advanced framework for quantifying and characterizing urban leisure activities at a fine scale based on multisource big data fusion

Summary

Introduction

Leisure activities refer to the behaviors performed for pleasure, relaxation, and other emotional benefits [1]. As an integral part of people’s daily lives, participation in leisure activities positively correlates with quality of life and subjective well-being [2,3,4]. Owing to the rapid development of the economy and society, people’s consumption demands for culture and spiritual products is increasing day by day [5]. The scope of people’s leisure activities is constantly expanding. Urban public space plays a prominent role in enhancing social cohesion, alleviating racial tensions and conflicts [7], increasing urban diversity, and promoting the coordinated development of economy and cultural undertakings [8,9]. It leads to the proliferation and blind development of leisure space [2,10]

Objectives

Methods

Results

Conclusion