Impact of Check-In Data on Urban Vitality in the Macao Peninsula

Chen Pan,Junling Zhou,Xiaohua Huang,Chenxi Huang

doi:10.1155/2021/7179965

Abstract

High activity is an important manifestation of the stable development of urban social economy. Quantitative research on urban development based on the geographical label perception of urban vitality is a new technical means and way to study urban vitality. In this paper, points of interest and Weibo check-in geographic markers are used to analyze urban vitality indicators and urban vitality distribution patterns. Through the application of different indexes, the ordinary linear regression and spatial autoregressive models between urban vitality and built environment are established to explore the factors that affect urban vitality. Results of the research show that interest points and social media check-in data can better indicate urban vitality. The urban vitality of the Macao Special Administrative Region is mainly affected by the density of land use, buildings, and public transportation.

Highlights

With the profound transformation of urban society, the importance of cities is becoming a hot topic in urban geography, urban planning, urban economy, and urban management
Linear regression models and spatial autoregressive models are constructed using land use, urban transportation, buildings, and other built-in environmental factors [15]. It shows the environmental impact mechanism of urban vitality and the stability of the impact mechanism [16]. e study shows that the data scattered in different geographical locations have similar urban spatial patterns [17]. e city’s vitality is largely affected by land use, building congestion, and the number of bus stops [18]. is study evaluates the vitality of the current city on the Macao Peninsula [19], discusses the trend of urban space development, determines the mechanism that affects the vitality of the city [20] and the importance of urban vitality to the promotion of urban development, and eventually puts forward targeted policies [21]
≤0.001 0 selection of variables in the spatial autoregressive model is based on the linear regression results, that is, the variables eliminated by the stepwise multiple linear regression

Summary

Introduction

With the profound transformation of urban society, the importance of cities is becoming a hot topic in urban geography, urban planning, urban economy, and urban management. With the continuous integration of information technology and positioning technology, big data using geographical location labels (such as mobile signals, point of interest, and social media information) can be used to display a large amount of data about human activities, provide methods to identify physical and social locations in cities, and measure the importance of cities. [12] Wang Di used different statistical analysis methods, such as kernel density estimation and focus analysis, to analyze the characteristics of crowd activity from the perspectives of time and space in the urban Weibo attendance data [13]. Linear regression models and spatial autoregressive models are constructed using land use, urban transportation, buildings, and other built-in environmental factors [15] It shows the environmental impact mechanism of urban vitality and the stability of the impact mechanism [16]. It shows the environmental impact mechanism of urban vitality and the stability of the impact mechanism [16]. e study shows that the data scattered in different geographical locations have similar urban spatial patterns [17]. e city’s vitality is largely affected by land use, building congestion, and the number of bus stops [18]. is study evaluates the vitality of the current city on the Macao Peninsula [19], discusses the trend of urban space development, determines the mechanism that affects the vitality of the city [20] and the importance of urban vitality to the promotion of urban development, and eventually puts forward targeted policies [21]

Methods

Experiment and Result Analysis

Findings

Conclusion and Discussion