|Table of Contents|

Impact of urban public transportation accessibility on housing price(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2022年4期
Page:
87-97
Research Field:
交通工程
Publishing date:

Info

Title:
Impact of urban public transportation accessibility on housing price
Author(s):
LIU Qing-qing1;  XUE Chao2;  JU Yong-feng2;  FENG Hong-xia3
(1. School of Civil Engineering, Chang'an University, Xi'an 710061, Shaanxi, China; 2. School of Electronics and Control Engineering, Chang'an University, Xi'an 710064, Shaanxi, China; 3. College of Architecture, Xi'an University of Architecture and Technology, Xi'an 710055, Shaanxi, China)
Keywords:
traffic engineering;  urban public transportation;  traffic accessibility;  machine learning algorithm;  housing price prediction;  Xi'an
PACS:
U411
DOI:
10.19721/j.cnki.1671-8879.2022.04.009
Abstract:
In order to clarify the impact of urban public transportation accessibility on housing price, three urban public transportation indexes of walking accessibility, bus accessibility and metro accessibility were established, as well as a real estate price prediction model was built by using several machine learning algorithms. The influence of transport accessibility on housing price was explored according to the public transportation network data of Xi'an in 2021. First, the house property data, urban traffic data and urban spatial data of Xi'an were collected and preprocessed. Second, the spatial syntax theory method was applied to establish three indexes of walking accessibility, bus accessibility and metro accessibility. Last, the constructed data was took as the characteristic indexs, the real estate price prediction model of Xi'an was constructed by using RF, LGBM, GBDT and HPM algorithm. Xi'an Metro Line 3 was taken as an example, buffer analysis and RF algorithm were used to analyze the influence of subway accessibility on housing price before and after operation. The results show that the prediction accuracy of housing price by RF algorithm is 89.2% and the root mean square error is 1 766.89, which proves that real-time requirements and research expectations can be achieved by using RF algorithms, and it is superior to other models. The importance percentage of public transportation accessibility based on space syntax calculation is 23.8%, which indicates that the urban public transportation accessibility has an important impact on housing prices.Therefore, the improvement of regional economic vitality and the development of real estate economy depend on the development of urban public transportation to some extent, and it plays an important role in promoting economic and social coordination and sustainable development.2 tabs, 11 figs, 25 refs.

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Last Update: 2022-07-20