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广州市居民住房条件的空间分异格局与形成机制
引用本文:王洋,金利霞,张虹鸥,吴旗韬,吴康敏.广州市居民住房条件的空间分异格局与形成机制[J].地理科学,2017,37(6):868-875.
作者姓名:王洋  金利霞  张虹鸥  吴旗韬  吴康敏
作者单位:1. 广州地理研究所, 广东 广州 510070
2. 广东省地理空间信息技术与应用公共实验室, 广东 广州 510070
3. 广东省创新发展研究院, 广东 广州 510070
4. 中国科学院南海海洋研究所, 广东 广州 510301
基金项目:国家自然科学基金项目(41401164、41571128)、广州市科技计划项目(201609020002,201510020011)、广东省自然科学基金项目(2014A030313740)资助
摘    要:以广州都市区1 361个社区的第六次人口普查住房数据为基础,从住房的建成年代、建筑结构、户均建筑面积、住房生活设施4个方面构建居民住房条件评价体系,分析其空间分异格局与形成机制。结果表明: 广州市居民住房条件由中心向外围逐渐提升,具有“圈层基础上的多核心”式空间分异结构; 户均建筑面积和建成年代是决定其住房条件差异的2项重要指标,旧城的住房条件异质性最高; 城市发展的历史进程、互换效应和过滤效应、高房价和高地价影响和强化了住房条件分异格局,制度性因素、政府决策和市场力量同时起到了引导和推动作用。

关 键 词:住房  住房条件  社区  居住空间  广州  
收稿时间:2016-09-01
修稿时间:2016-11-12

The Spatial Differentiation Pattern and Formation Mechanism of Housing Conditions in Guangzhou City,China
Yang Wang,Lixia Jin,Hong’ou Zhang,Qitao Wu,Kangmin Wu.The Spatial Differentiation Pattern and Formation Mechanism of Housing Conditions in Guangzhou City,China[J].Scientia Geographica Sinica,2017,37(6):868-875.
Authors:Yang Wang  Lixia Jin  Hong’ou Zhang  Qitao Wu  Kangmin Wu
Institution:1. Guangzhou Institute of Geography, Guangzhou 510070, Guangdong, China
2. Guangdong Public Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, Guangdong, China
3. Guangdong Academy of Innovation Development, Guangzhou 510070, Guangdong, China
4. South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, Guangdong, China
Abstract:The housing issues of China’s urban residents have always been the focus of academic circles. The issues regarding housing conditions in China's megalopolises are important topics of research for building livable cities, resolving the housing shortage, and solving the urban problem. The inequality of urban housing conditions is also an indispensable issue. However, to date, specific research on the differentiation pattern and spatial structure of housing conditions in China's cities is rare. Therefore, based on housing data from the newly available sixth census of 2010 for Guangzhou’s metropolitan areas, we established a comprehensive system for evaluating housing conditions that is composed of housing years, building structure, building area per household, and housing facilities and explored the spatial differentiation pattern of housing conditions. Furthermore, we analyzed the spatial cluster and heterogeneity of housing conditions by using the ESDA and GDI index. Finally, we summarized the spatial differentiation model and formation mechanism. The results are as follows: 1) The housing conditions of Guangzhou, gradually improving from the center to periphery, show significant imbalance and spatial cluster characteristics. Regions with better and worse housing conditions have specific location directions. Housing years and building area per household are two core indicators that decide the differentiation of housing conditions. 2) The housing conditions of the evaluation subsystem are distinct among different urban circles. In the old city, the scores of housing years, architectural structure, and building area per household are lower. In the core area, scores of the building area per household and housing infrastructure are higher than in other regions. In the central area, the level of the architectural structure is highest. In the suburbs, the housing years are the lowest. In addition, the heterogeneity of housing conditions in the old city is the highest. 3) The historical process of urban development, housing exchange and filtering effects, and high housing and land prices influence and enhance the spatial differentiation pattern of housing conditions in Guangzhou. Institutional factors, government decision making, and market forces also play a role in guiding and promoting the pattern. Thereto, institutional factors include the urban-rural dual-land system, housing dual-supply system, and housing demolition requisition system. Government decision making mainly refers to the urban development strategy and urban planning. Market forces reflect relationships between housing price, housing conditions, location, and household income.
Keywords:house  housing conditions  community  residential space  Guangzhou City  
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