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公共设施可达性对住宅价格影响的空间异质性分析——以乌鲁木齐市为例
Alternative TitleAnalysis of the spatial heterogeneity of the impact of public facilities accessibility on housing prices—A Case Study of Urumqi
刘韬
Subtype硕士
Thesis Advisor杨德刚
2020-06-30
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline理学硕士
Keyword公共设施可达性 住宅价格 空间异质性 地理探测器 乌鲁木齐 Public facility accessibility Housing price Spatial heterogeneity Geodetector Urumqi
Abstract住宅作为居民生活必需品, 影响其价格的因素不只是建筑本身的差异,还包括区位及周边环境的不同。 同时,住宅作为一种异质性产品,其价格分布具有空间异质性,即空间不同位置受相同因子的影响及其强度具有差异性。 如医院、学校、公交站点等公共服务设施对城市住宅价格都有显著的提升作用,但由于区位差异其影响程度有所不同。本文在参照相关研究基础上,选择教育科研、 医疗卫生、 交通出行、 文化娱乐、 金融服务和商业购物等 6 大种类(包含小学、医院、公交站等 12 个类型)的公共设施。 首先运用空间分析方法识别 12 类公共设施和住宅小区的空间分布模式、方向和形态特征以及房价的空间分异特征;其次, 采用基于路网、坡度和地形起伏度差异的成本栅格法计算住宅小区到距其最近的公共设施可达性; 最后利用地理探测器计算不同类型设施可达性在整体空间上对房价的影响力,并以此作为权重综合计算六大种类设施可达性对不同圈层、不同方向的房价影响力、交互作用差异,进而总结出影响异质性模式图。 得到主要结论有:(1)公共设施空间分布不均衡,其分布模式、方向和形态与该类设施布局以效率还是公平为导向而不同。 多数设施都表现为聚集分布模式, 医疗卫生、文体设施和商业购物等效率型设施方向性显著,教育科研、金融服务等公平型设施空间形态基本都呈“T”字型。(2)住宅小区空间分布具有集聚、密度从内向外降低、“T”型分布等特点,居住空间与公共设施分布空间匹配性良好。 房价具有显著的空间分异性, 表现为东西方向从中心向外围降低,南北方向为“南高北低”,并具有显著的空间自相关性(古牧地片区低低集聚、高铁和铁路片区高高集聚)。(3) 设施可达水平呈现出从中心向外递减的圈层式格局,城区中心可达性高但服务范围小、服务小区数量多,公共设施服务压力大。(4) 因子探测结果显示:效率型设施对住宅价格的影响力大于公平型设施,不同圈层之间影响力表现为三环>整体>二环>一环,城北区域影响力大于城南;越远离城区中心,居民对公共设施的依赖越大。交互探测结果显示:不同因子间均存在交互作用, 尤其是医疗卫生、文化休闲设施具有较强的交互力。(5) 公共设施可达性对房价的影响表现为“多核心+扇形”的“T”型空间结构,不同区域对房价起主导作用的设施种类不同。 形成了多种设施共同影响的综合区域、沿河滩快速路分布的带状教育设施主导区、位于二环和米东区的交通设施主导区、城区正北和正南面呈扇形分布的医疗设施主导区、一环和经开区商业设施主导区、会展片区和骑马山片区的文体设施主导区、零星分布的金融设施主导区等。
Other AbstractHousing is a necessity for residents. The factors that affect its price are not onlythe building structure, but also the differences of location and surrounding environment.At the same time, as a heterogeneous product, the price distribution of housing hasspatial heterogeneity. In other words, houses which have different locations are affectedby the same factors but the intensity are different. Such as hospitals, schools, and busstations, have a significant role in promoting the price, but the impact degree is differentdue to the location difference.Based on relevant research, this article selects public facilities in 6 categories(including 12 types such as primary schools, hospitals, and bus stations), includingeducation and research, healthcare, transportation, cultural and leisure, financial, andcommercial facilities. Firstly, spatial analysis method is used to identify the spatialdistribution pattern, direction and shape characteristics of 12 types of public facilitiesand residential areas, as well as the spatial differentiation characteristics of housingprice. Secondly, cost grid method based on the difference of road network, slope andterrain fluctuation is used to calculate the accessibility of residential districts to itsnearest public facilities. Finally, the influence of different types on the overall space arecalculated by geo-detector. Based on this, take it as a weight to comprehensivelycalculate the influence of the accessibility of six types on the housing price in differentcircles and directions, and then summarize the pattern of impact heterogeneity. Themain conclusions are as follows:(1) The spatial distribution of public facilities is not balanced, and their distributionmodes, directions, and forms are different from whether such facilities are focused onefficiency or fairness. Most facilities are clustered. Medical and health facilities,cultural and leisure facilities and commercial facilities which are efficiency orientedhave significant directionality, and the space form of fair facilities such as education,scientific research and financial services basically assumes the "T" shape.(2) The spatial distribution of residential districts has the characteristics ofagglomeration, density decreasing from inside to outside, and a "T" -shaped distribution.The living space is well matched with the space of public facilities. The house price hassignificant spatial differentiation, which shows that the east-west direction decreasesfrom the center to the outside, and the north-south direction is "high in the south andlow in the north". Also, it has significant spatial autocorrelation (low and lowconcentration in ancient pastoral areas, high and high concentration in high-speed railand railway areas).(3) The accessibility level of facilities presents a circle pattern of decreasing fromthe center to the outside. Due to the high accessibility of the urban center, the smallservice scope and the large number of service communities, the pressure of publicfacilities service is high.(4) The factor detection results show that the impact of efficient facilities onhousing prices is greater than that of fair facilities. The influence between differentzones is represented by the third ring> the whole> the second ring> the first ring, andthe influence in different directions is greater in the north than the south. Farther awayfrom the center of Urumqi, the greater the dependence of residents on public facilities.And interactive detection results show that there are interactions between differentfactors, especially healthcare and leisure facilities with strong interaction.(5) The impact of accessibility of public facilities on housing prices is representedby a "multi-core + fan-shaped" with a T-shaped space structure. Different types offacilities play a leading role in housing prices in different regions. It has formed acomprehensive area affected by multiple facilities, a belt-shaped educational facilitydominated area distributed along the River Beach Expressway, a transportation facilitydominated area located in the Second Ring and Midong district, a medical facilitydominated area distributed north and south of the city, a business facility leading areain the first ring and Technological Development Zone, a cultural facility leading area inthe exhibition area and Qimashan district, and a scattered financial facilities leadingarea.
Subject Area人文地理学
Language中文
Document Type学位论文
Identifierhttp://ir.xjlas.org/handle/365004/15435
Collection中国科学院新疆生态与地理研究所
研究系统
Affiliation中国科学院新疆生态与地理研究所
First Author Affilication中国科学院新疆生态与地理研究所
Recommended Citation
GB/T 7714
刘韬. 公共设施可达性对住宅价格影响的空间异质性分析——以乌鲁木齐市为例[D]. 北京. 中国科学院大学,2020.
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