城市轨道站点可达性与住宅特性关系研究——以苏州市为例

 2022-10-27 11:10

论文总字数:29145字

摘 要

城市轨道交通具有运量大、速度快、安全准点、乘车条件舒适、污染小等特点,是建设公交都市不可或缺的重大基础设施之一。其作为一种重要的城市公共基础设施,社会效益是巨大的,但是其主要效益凝聚在了沿线土地的溢价上,具有典型的正外部性。住宅价格既是评价轨道交通外部效益、引导轨道交通投融资模式优化的重要观测指标,又是影响居民置业行为进而影响居民通勤模式选择的重要因素,两者之间存在的反作用,对城市人口空间分布进而对轨道交通客流结构具有决定性的影响。研究城市中不同区域城市轨道站点的时空距离与住宅价格关系,评估轨道交通的实际影响范围对后续开展轨道交通周边存量用地更新和新建轨道交通沿线土地收储及综合开发具有实际参考价值。

本文以苏州市为例,用时空法量化轨道交通站点可达性,采用火车采集器和分别获取住宅区位特征变量、邻里特征变量、建筑自身特征变量所所需数据;采用python自编程序调用百度地图开发者平台API获取评价轨道交通站点可达性的各出行方式耗时、路径距离数据,采用ArcGIS处理清洗筛选空间数据。通过建立住宅特征价格评价模型,使用STATA进行统计分析,揭露了城市不同发展程度区域住宅综合特征质量与轨道交通时空距离的关系。

研究的主要结果有:1、改进的半对数模型在住宅特征综合质量(即住宅价格)与时空距离回归分析时拟合优度较其他模型更高。2、轨道交通 1 号线对周边住宅价格的影响呈现空间不稳定性,对城市新区的影响最为显著,实证证明住宅特征价格模型在城市新区的评估中显著性也最好。3、城市轨道交通对住宅价格的影响与距轨道交通站点的时空距离有关。以新城为例,距古城中心站点距离与住宅价格正相关,住宅与古城距离每增加1km,住宅价格增加4.87%;距新城中心站点距离与住宅价格负相关,住宅与新城中心站点距离每增加1km,住宅价格减少8.27%;距最近地铁站距离与住宅价格负相关,住宅与最近地铁站的距离每增加1km,住宅价格减少2.55%。4、采用何种出行方式表征时空距离对模型拟合优度有较大影响。在用各种出行方式耗时和路径距离对时空距离量化时,步行优于骑行、骑行优于自驾;出行耗时比出行距离拟合程度更高,综合采用步行时间来量化时空距离和可达性最佳,采用自驾路径距离最差。

关键词:轨道站点可达性;时空距离;特征价格模型,住宅价格,轨道空间效应

Research on the Relation between Accessibility of Urban Rail Station and Residential Characteristics——Taking Suzhou as an Example

Abstract

Urban rail transit (URT) is one of the most important infrastructures for the construction of public transport city, which has the characteristics of large volume, fast speed, safety, punctuality, comfortable riding conditions and low pollution. As an important urban public infrastructure, its social benefits are enormous, but its main benefits are concentrated on the premium of land along the line, which has a typical positive externality. Housing price is not only an important observation index for evaluating the external benefits of rail transit and guiding the optimization of investment and financing modes of rail transit, but also an important factor affecting residents' purchase behavior and then the choice of commuting modes. The interaction between them has a decisive impact on the spatial distribution of urban population and the passenger flow structure of rail transit. Studying the relationship between the space-time distance of urban rail stations and housing prices in different regions of the city, and evaluating the actual impact scope of rail transit have practical reference value for subsequent renewal of the existing land around rail transit and land storage and comprehensive development along the newly built rail transit.

Taking Suzhou as an example, this paper quantifies the accessibility of rail transit stations by space-time method, uses train collector and obtains the data needed by residential location characteristic variables, neighborhood characteristic variables and building own characteristic variables respectively, and uses Python self-programming program to call Baidu Map Developer Platform API to obtain the travel mode time-consuming and path distance data for evaluating the accessibility of rail transit stations. By establishing the housing characteristic price evaluation model, this paper reveals the relationship between the comprehensive characteristic quality of housing and the space-time distance of rail transit in different urban development areas.

The main results of the study are as follows: 1. The improved semi-logarithmic model has higher goodness of fit than other models in the regression analysis of comprehensive quality of housing characteristics (i.e. housing price) and space-time distance. 2. The impact of Rail Transit Line 1 on the surrounding housing prices is spatially unstable, with the most significant impact on new urban areas. Empirical evidence shows that the housing hedonic price model is also the most significant in the evaluation of new urban areas. 3. The influence of urban rail transit on housing price is related to the space-time distance from rail transit station. Taking Xincheng as an example, the distance from the central station of the ancient city is positively correlated with the housing price. For every 1 km increase in the distance between the residence and the ancient city, the housing price increases by 4.87%; for every 1 km increase in the distance between the residence and the central station of the new city, the housing price decreases by 8.27%; for every distance between the nearest subway station and the nearest subway station, the distance between the residence and the nearest subway station is negatively correlated with the housing price. Increasing by 1 km will reduce housing prices by 2.55%. 4. What kind of travel mode to characterize the space-time distance has a great influence on the goodness of fit of the model. When quantifying the space-time distance with various travel modes and path distances, walking is better than cycling and cycling is better than self-driving; travel time is higher than travel distance fitting degree; comprehensive use of walking time to quantify space-time distance and accessibility is the best, and self-driving path distance is the worst.

Key words: Rail Station Accessibility; Space-time Distance; Hedonic Price Model, Housing Price, Orbital Space Effect

目录

城市轨道站点可达性与住宅特性关系研究——以苏州市为例 I

摘 要 I

Abstract II

第一章 绪论 1

1.1研究背景 1

1.2研究内容和目的 1

1.2.1研究目的 1

1.2.2研究内容 1

1.3方法与技术路线 2

1.3.1研究方法 2

1.3.2技术路线 2

1.3.3内容安排 3

第二章 相关概念界定及国内外研究现状 4

2..1轨道站点可达性及时空距离概念界定 4

2.1.1可达性概念及评价方法 4

2.1.2时空法对轨道交通站点可达性评价的综述 4

2.2轨道交通对于住宅价格影响的综述 4

2.2.1城市轨道交通对住宅价格影响的空间范围综述 4

2.2.2城市轨道交通对住宅价格影响在不同区域的差异性综述 5

2.3特征价格理论研究综述 6

2.3.1特征价格理论 6

2.3.2特征价格理论在住宅价格上的应用综述 6

2.4本章小结 7

第三章 理论模型与指标选取 8

3.1住宅价格特征模型 8

3.1.1模型方法 8

3.1.2模型估计与检验 8

3.2住宅特征变量选择 9

第四章 数据获取与处理 11

4.1研究范围概述 11

4.1.1苏州市概述 11

4.1.2苏州市轨道交通一号线概述 11

4.1.3数据分析范围及简介 12

4.2数据获取及清洗 13

4.2.1住宅类数据 13

4.2.2时空类数据 14

4.2.3商业设施类数据 15

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