Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

Lingbo Liu,Hao Wu,Zhenghong Peng,Ru Wang,Jie Zhao,Hanchen Yu

doi:10.3390/ijgi11010057

Abstract

The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities accessibility of schools, hospitals, green space, and public transit stations with four kinds of accessibility models such as the nearest distance, real time travel cost, kernel density, and two step floating catchment area (2SFCA), and explores the multiscale effect of public services accessibility on house prices with multiscale geographically weighted regression model. The results show that the differentiated scale effect not only exists among different public facility accessibilities, but also exists in different accessibility models of the same sort of facility. The article also suggests that different facilities should adopt its appropriate accessibility model. This study provides insights into spatial heterogeneity of urban public service facilities accessibility, which will benefit decision making in equal accessibility planning and policy formulation for the layout of urban service facilities.

Highlights

Along with the ongoing planetary urbanization, the surging in urban population poses a major challenge for global cities to provide residents with safe, healthy, and sustainable public services [1]
Such a gap could be found in the comparison of accessibility of metro stations, the maximum API
There is similarity on population density and house age with a related study based on Geographic Weighted Regression model (GWR), which suggests that those two variables show both positive and negative connections with housing prices [45], but this study further shows that population density is of local spatial effect and not significant in most regions

Summary

Introduction

Along with the ongoing planetary urbanization, the surging in urban population poses a major challenge for global cities to provide residents with safe, healthy, and sustainable public services [1]. Housing prices are affected by spatial correlation [21] and spatial heterogeneity [22], for instance, there exist distance decay effect of facilities on urban housing prices, and different kinds of stations will have different impact on housing price [23]. Such a dilemma could be partly explained by the scale effect of spatial accessibility [23,24]

Methods

Results

Discussion

Conclusion