A Data-Driven Framework for Analyzing Spatial Distribution of the Elderly Cardholders by Using Smart Card Data

Zhicheng Shi,Xintao Liu,Jianhui Lai,Wenzhong Shi,Chengzhuo Tong,Anshu Zhang

doi:10.3390/ijgi10110728

Abstract

In this era of population aging, it is essential to understand the spatial distribution patterns of the elderly. Based on the smart card data of the elderly, this study aims to detect the home location and examine the spatial distribution patterns of the elderly cardholders in Beijing. A framework is proposed that includes three methods. First, a rule-based approach is proposed to identify the home location of the elderly cardholders based on individual travel pattern. The result has strong correlation with the real elderly population. Second, the clustering method is adopted to group bus stops based on the elderly travel flow. The center points of clusters are utilized to construct a Voronoi diagram. Third, a quasi-gravity model is proposed to reveal the elderly mobility between regions, using the public facilities index. The model measures the elderly travel number between regions, according to public facilities index on the basis of the total number of point of interest (POI) data. Beijing is used as an example to demonstrate the applicability of the proposed methods, and the methods can be widely used for urban planning, design and management regarding the aging population.

Highlights

Population aging is a global trend, and it has become a challenge for many countries.According to the World Population Prospects 2019 [1], the world’s population will increase to 9.7 billion by 2050, with one out of six people aged 65 or over
Since over 98 percent of the smart card data of elderly is generated by bus, this study focuses on the bus travel of the elderly cardholders
This paper presented a framework for studying the spatial distribution pattern of elderly cardholders to help address the issue of the population ageing, and in the future

Summary

Introduction

Population aging is a global trend, and it has become a challenge for many countries.According to the World Population Prospects 2019 [1], the world’s population will increase to 9.7 billion by 2050, with one out of six people aged 65 or over. Population aging is a global trend, and it has become a challenge for many countries. In some European countries and North America, up to one out of four people will be aged 65 or over. Several solutions have been proposed, such as gradual or delayed retirement schemes [2,3], extension of working hours and encouragement for the elderly to form organizations with younger people to learn from each other and share their experiences. Urbanization should create many new job opportunities that attract the elderly working in cities. The study of the elderly distribution patterns has become a research topic of great interest to urban planners and policy makers [4]

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