中国城市住宅价格的空间分异格局及影响因素

分别研究2009年中国286个地级以上城市住宅均价和房价收入比的空间分异格局、总体趋势、空间异质性和相关性;根据供需理论和城市特征价格理论建立了影响中国城市住宅价格空间分异的初选因素,并根据半对数模型分析主要影响因素。结果表明：① 中国城市住宅价格空间分异显著,呈现出空间集聚性分异（东南沿海三大城市群与内陆城市之间）和行政等级性分异（省会与地级市之间）的双重格局;② 房价收入比较高的城市数量更多,分布范围更广,购房难度较大的城市已超过一半;③ 住宅均价的总体分异趋势和空间异质性都强于房价收入比;④ 城市居民收入与财富水平和城市区位与行政等级特征是住宅价格空间分异的两大核心影响因素。     

Amenity value in post-industrial Chinese cities: the case of Nanjing

Many Chinese cities are in a transition from industrial to post-industrial urban economies. In this process of urban restructuring, land use becomes polycentric and fragmented. More sophisticated models are needed to estimate the amenity effects of this complex residential environment. This article assesses the relative housing price effects of neighborhood characteristics and accessibility in Nanjing, China. This is achieved with a hedonic price model that incorporates detailed spatial measures, geographical contingency, and a modified version of Alonso’s (1964) general theory of land rent. A crucial finding is that the effect of job accessibility on house price varies depending upon the specific sector of employment. Accessibility to jobs in the public and private service sectors has strong positive effects. However, housing proximity to heavy industries has a spatially nonlinear effect: negative in close proximity, but positive at a larger distance. Second, when we control for job accessibility, access to public transport has an added positive effect. Finally, neighborhood “quality” (defined in terms of nearby amenities) is also relevant, but far less than access to service employment. This research shows that Nanjing’s housing prices are affected by different residential characteristics than those with dominant price effects in Western cities.     

The design and implementation of SPIRIT: a spatially aware search engine for information retrieval on the Internet

Much of the information stored on the web contains geographical context, but current search engines treat such context in the same way as all other content. In this paper we describe the design, implementation and evaluation of a spatially aware search engine which is capable of handling queries in the form of the triplet of ?theme??spatial relationship??location?. The process of identifying geographic references in documents and assigning appropriate footprints to documents, to be stored together with document terms in an appropriate indexing structure allowing real‐time search, is described. Methods allowing users to query and explore results which have been relevance‐ranked in terms of both thematic and spatial relevance have been implanted and a usability study indicates that users are happy with the range of spatial relationships available and intuitively understand how to use such a search engine. Normalised precision for 38 queries, containing four types of spatial relationships, is significantly higher (p<0.001) for searches exploiting spatial information than pure text search.     

中国城市房价、收入与房价收入比的时空分异格局

中国城市房价快速增长背景下,城市房价、收入与房价收入比空间格局既有相似性,也表现出差异性,其空间异质性与空间依赖性特征显著。本文以中国337个地级行政单元为研究对象,运用泰尔指数、位序-规模和空间马尔科夫链等方法,对2009—2018年中国城市房价、收入和房价收入比的时空分异格局、整体稳定性和空间依赖性特征进行分析发现:(1)中国城市房价增长呈现出波动性特征,整体分异程度增强,房价城市体系呈现"金字塔型"结构,收入则表现出平稳增长态势,整体分异度降低,城市体系呈现"橄榄型"结构,在房价与收入共同影响下,房价收入比整体差异性显著加强;(2)城市房价空间格局表现出"地带性"与"等级性"差异并存,而收入更多表现出"地带性"差异,房价收入比则以"等级性"差异为主;(3)城市房价和收入类型的稳定性和空间依赖性较强,高、低水平城市存在两极分化与"俱乐部收敛"现象,房价收入比稳定性相对较弱。对中国城市房价、收入和房价收入比时空分异格局和空间关联效应的分析,可以为探索中国城市房价收入比空间分异模式与机理提供必要研究基础。     

Effect of land prices on the spatial differentiation of housing prices: Evidence from cross-county analyses in China

This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014. Multiple theoretical perspectives on housing demand, supply, and market, are combined to establish a housing price model to explore the impact of land prices on housing prices. The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique. Finally, the influencing mechanism of land prices on housing prices is discussed. The main conclusions are as follows. (1) Housing prices have a pyramid- ranked distribution in China, where higher housing prices are linked to smaller urban populations. (2) Land prices are the primary driver of housing prices, and their impacts on housing prices vary over different administrative levels. To be specific, the effect of land prices is the strongest in the urban districts of provincial capital cities. (3) The internal influence mechanisms for land prices driving housing prices are: topographic factors, urban construction level, the agglomeration degree of high-quality public service resources, and the tertiary industrial development level. The urban land supply plan (supply policies) is the intrinsic driver that determines land prices in cities; through supply and demand, cost, and market mechanisms, land prices then impact housing prices.     

扬州市住宅价格空间分异的影响因素与驱动机制

构建包含20个评价因子、4 个影响因素和4 个预期修正因素在内的城市住宅价格空间分异影响因素评价体系,基于评价因子和预期修正,分别得出单户住宅档次与水平、小区建设档次与水平、区位与生活便利性、周边景观与环境等4 个影响因素强度的得分,并分析其空间分异格局。以2012 年扬州市1305 个小区的平均住宅单价为因变量,4 个基本影响因素得分为自变量,进行回归分析,探索所有住宅及各子市场价格分异的主要因素,并分析其驱动机制。结果表明：① 4 个影响因素强度格局明显不同,住宅自身因素的格局呈现中心低外围高的圈层式分异,而外部作用因素强度呈现中心高外围低、西高东低的扇型与圈层相结合式空间分异格局;② 扬州市总体住宅价格空间分异的核心影响因素是小区建设档次与水平,不同类型住宅子市场的价格影响因素各不相同;③ 扬州市住宅价格空间分异的主要驱动力是特定住宅类型与档次建设的区位指向、特定收入阶层的空间集聚、公共物品投资的空间差异、城市居住用地扩展与城市更新的区位指向。     

中国县域住宅价格的空间差异特征与影响机制

以2014年中国2872个县级单元的住宅平均单价为基本数据,通过空间自相关和核密度函数分析中国住宅价格的差异格局、空间关联特征和分布形态,构建“住宅价格等级金字塔”;根据“需求+供给+市场”的三维理论视角建立包括5大住宅价格差异影响因素在内的价格模型,采用地理探测器分析全国及其区域子市场的影响因素强度差异,并探索其影响机制。结果表明：① 中国区域住宅价格呈现以行政等级性为主、空间集聚性为辅的双重差异格局,其空间关联与集聚性显著;② 中国住宅价格呈现出房价越高,区域越少,所居住城镇人口越少的“金字塔式”等级分布特征。③ 租房户比例、流动人口规模、住房支付能力、住房市场活跃度、土地成本是中国住宅价格差异的5个核心影响因素,不同行政等级子市场的影响因素作用强度各异。     

长三角一体化区域城市商品住宅价格分异机理研究

城市住宅价格及其空间差异是21世纪以来引起城市地理学者持续关注的热点问题。以长三角135个区县为研究对象,在通过分异度指数测度发现2014-2016年各区县商品房价差异增大的基础上,以商品房单位面积成交均价为因变量,提取16项房价影响因素为自变量,通过逐步回归和地理加权回归进行定量分析。研究发现：高校资源、经济密度、房产政策、经济实力、公共服务投入、高端从业者占比和产业结构7项指标对房价分异的影响最显著,而各因素对区域内房价的影响程度均具有显著的空间不稳定性。进而,提出房价是城市经济、人力、社会和行政等资源丰度的货币化表达,区域房价分异是城市支配资源能力差异的综合反映,其中行政资源在各类资源中占据主导地位。由此判断,长三角各区县房价在短时期内较难实现“俱乐部收敛”,沪宁杭等核心城市与外围地区的房价差距可能会继续扩大。     

邻避设施空间分布特征及其与周边住宅价格的关系——广州案例

随着中国城镇的快速发展以及市民环境意识的提高,由邻避设施引发的矛盾日益增多。合理规划邻避设施,是促进环境正义、推动社会和谐的重要课题。论文从“规划云平台”获取广州主城区邻避设施的地理信息数据,通过Python语句编码收集广州主城区小区平均房价数据,运用克里金插值法分析邻避设施的空间分布特征,构建多元线性回归模型和地理加权回归模型研究邻避设施与周边住宅价格的关系。研究发现,广州主城区邻避设施的布局与低收入住宅区的分布在空间上具有一致性,邻避设施主要分布在房价较低的住宅区周边;邻避设施对周边小区房价的影响与邻避设施的类型和所在区位相关,城市边缘区的邻避设施对房价造成了显著的负面影响,而城市中心良好的区位条件、基础设施与公共服务配套一定程度上抵消了邻避设施的负外部性;污名化类的邻避设施对房价的影响程度明显小于污染类、风险聚集类和心理不悦类邻避设施。本研究对有关城市邻避设施的科学规划布点具有一定的借鉴和指导意义。     

土地价格对住房价格空间分异的影响——基于中国县域单元的实证分析（英文）

This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014.Multiple theoretical perspectives on housing demand,supply,and market,are combined to establish a housing price model to explore the impact of land prices on housing prices.The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique.Finally,the influencing mechanism of land prices on housing prices is discussed.The main conclusions are as follows.(1) Housing prices have a pyramid-ranked distribution in China,where higher housing prices are linked to smaller urban populations.(2) Land prices are the primary driver of housing prices,and their impacts on housing prices vary over different administrative levels.To be specific,the effect of land prices is the strongest in the urban districts of provincial capital cities.(3) The internal influence mechanisms for land prices driving housing prices are:topographic factors,urban construction level,the agglomeration degree of high-quality public service resources,and the tertiary industrial development level.The urban land supply plan(supply policies) is the intrinsic driver that determines land prices in cities;through supply and demand,cost,and market mechanisms,land prices then impact housing prices.     

基于Tripadvisor 的中国旅游地国际关注度及空间格局

用户贡献内容(UGC)已逐渐成为旅游行为与感知研究的重要数据源.区别于通常利用搜索引擎关键词数量描述网络关注度的方法,本文引入电子社区层次结构为权重因子,建立了基于社区UGC的旅游关注度模型,能够灵活调节模型表达的重点,优化计算结果.针对著名旅游电子社区Tripadvisor 的研究发现,国外社区用户对中国旅游的关注呈现3 个典型特征:①旅游关注集中在“长城、泰山、黄山、九寨沟、张家界”等少数旅游吸引物,和“北京、香港、上海、桂林”少量目的地城市;大量吸引物和目的地关注度较低,呈现“长尾现象”与极化特征.②吸引物与目的地城市的关注空间具有明显耦合性,关注度较高的吸引物多邻近或隶属于关注度较高的城市,如桂林阳朔、北京长城、成都都江堰和九寨沟、杭州西湖等.③旅游关注空间整体呈现出由高到低的“东—中—西”格局,与中国区域经济的“东—中—西”梯度格局基本耦合;北京、香港、广州、深圳、上海、成都等关注中心也与区域经济中心一致.旅游资源禀赋、电子口碑传播模式、地理区位、经济水平和关注者国家的文化背景、经济发展状况、地理区位等是影响旅游者关注度及其空间格局变化的主要因素.旅游关注度模型旨在解决互联网用户对区域旅游关注的定量计算问题,为基于互联网UGC的旅游地理学研究提供新思路.     

基于ICT的中国城市间人口日常流动空间格局——以百度迁徙为例

随着互联网时代的来临,网络数据已越来越成为表征居民地理行为的重要载体,用户迁移、社交网络、移动通信等地理行为大数据成为城市联系研究的重要数据来源。“百度迁徙”大数据通过LBS技术,全程、动态、即时和直观地记录了城市之间的人口日常流动轨迹。通过采集“百度迁徙”数据库中2015年一季度（2月7日至5月16日）国内369个城市之间的逐日的人口流动数据,分“季度平均、春运期间（春节前）、春运期间（春节后）、劳动节、周末和工作日”6个时间段,从人流集散层级、人流集散网络体系的分层集聚、人口日常流动空间格局及其与“胡焕庸线”之间的关系等角度分析各时间段的城市之间的人口日常流动相关特征与空间格局。研究发现,“百度迁徙”大数据清晰地显示了春运期间中部和沿海地区之间的人口流动格局。人流集散中心主要分布在京津冀、长三角、珠三角和成渝4大城市群中,并与其城市等级有较强的一致性。人口日常流动集散体系呈明显的分层集聚,京津冀、长三角、珠三角、成渝和乌鲁木齐5大集散体系在各时间段基本得到体现,而华中、东北、西南和福建沿海等地区并未出现高层级集散城市和高等级集散体系,与这些区域在国家区域发展战略中的地位在一定程度上不相匹配。“胡焕庸线”能较好地反映国家层面的城市之间人口日常流动格局,反映了地理环境对城市间人口日常流动的深刻影响。城市之间的人口流动强度是体现区域经济联系强度、城市等级和网络结构等的重要指标,此项研究可为形成国家区域经济发展新格局和促进区域平衡发展提供参考。     

空间功能视角下的公共服务对房价的影响——以成都市为例

房价的快速上涨和城市内部房价的巨大差异引起社会广泛关注,调控房价,防止局部区域房价过热势在必行。本文从城市空间功能的视角出发,以成都市2016年房价为例,基于地理探测器分析公共服务对房价的影响。结果表明：成都平均房价为8480元/m²,并从市中心沿交通环线和放射状干线同时向郊区递减,形成圈层加放射格局,总体上呈现西高东低、南高北低的特点。公共服务(主要包括医疗、金融和教育服务)对房价的影响以第三圈层和西南方最为显著,且高于城市层面上整体的影响。公共服务对房价的影响显著受不同区域的空间功能差异的影响,公共服务和空间功能差异会加剧房价的分异格局,并推动局部房价过热。因此,显著地受到在房价调控中,不仅要有传统的金融、经济政策,还要注重空间功能和公共服务的优化。     

The economic value of streets: mix-scale spatio-functional interaction and housing price patterns

Location factors are vital elements for describing housing price variation. However, limited studies have explicitly illustrated the relationship between urban design and the heterogeneity of housing price patterns. This article specifically evaluates how the interactions between the spatial layouts and land-use system at various scales through street network affect the valuation of the residential properties and the segmentation of housing markets in a network-based Mixed-scale Hedonic Model (MHM) where the submarkets pattern are determined and annotated by the spatially varying estimates on streets. The application of the delivered method in the case of Shanghai City, China, confirms the necessity of using the non-Euclidean distance metric and represent the coexistence between the stationarity and the non-stationarity of the introduced street accessibility variables. The results provide evidence that the impacts of street accessibility measures on the local levels showcase significant spatial variation. It is common for all the places that the properties located on the streets with the higher levels of angular closeness, smaller values of angular betweenness and longer angular distance to the nearby land-uses at the larger scales will be bided higher. It is proven that our delineation of submarket performs better in prediction accuracy than the traditional submarket specifications. The detected submarkets pattern yields that reachable land-use diversity at the pedestrian level is not a preferred factor in the housing submarkets located in the developed city centres. The signs of the price effects of the angular distance to local land-uses distinguish the developing submarkets as two main groups with different degrees of geometrical walkability. It is suggestive that continuously developing pedestrian-oriented neighbours in the walkable areas could contribute to decelerating the growth of house price in Chinese cities. The productions of this study can enrich the understanding of the socioeconomic effects of urban design with greater spatial precision across submarkets.     

长春市区新建住宅价格的空间格局分析

利用GIS技术对长春市住宅价格空间格局进行了研究,发现长春市住宅价格空间格局整体呈现单中心圈层分布,在长春市动植物公园与南湖广场附近分别出现了2个价格极核;住宅价格次高区域位于城市中心,包含了南湖与伊通河部分段;住宅价格变化幅度区域差异明显,东北—西南方向价格降低速度快,东南—西北方向价格降低慢,并且在城市西部和南部出现了局部高价格区域。在此基础上,分析了长春市住宅价格空间格局的驱动因素,发现住宅价格空间格局主要受到居住环境优势、城市发展战略、交通条件、用地布局及购买主体收入水平等几个方面因素的影响。结合研究结果,对长春市房地产开发格局优化提出了几点建议。未来长春市住宅开发的重点区域将集中在南部、西部和东北部。南部和长东北地区适宜进行中高端生态社区的开发,西部新城应以普通住宅与生态社区开发相结合,铁北地区应以低端住宅建设为主。     

北京经济适用房布局特征及影响因素研究

20 世纪90 年代,中国开始实施经济适用住房政策。然而,在政策的实施过程中,由于不合理的布局,经济适用住房并没有切实解决中低收入家庭的住房问题。学者们通过研究发现,大多数经济适用住房被安排在城市边缘地区,缺乏配套公共设施。目前,相关研究较多关注经济适用住房的空间布局及其引发的社会问题,少有学者关注影响经济适用住房布局的因素。因此,本文试图从地方政府的视角解答影响经济适用住房布局的因素。研究提出假设,地方政府受到土地财政收入的驱动,将经济适用住房项目布置在对土地收益损失最小的地方,同时兼顾政策实施过程中的拆迁压力、住房市场结构以及公共交通便利性等。在假设基础上,对北京经济适用住房空间布局的时空特征进行分析,并构建经济适用住房布局的影响因素模型。结果发现：1999-2009 年间北京经济适用住房建设速度放慢,同时呈现向五环以外扩散及向某些点集聚的趋势;模型结果证实土地价格是政府在落实经济适用住房项目时考虑的重要因素。     

南京城市住宅“售租比”时空格局与分异机理

“售租比”是国内外学者测度房价健康水平或泡沫风险的关键指标之一。利用中国房价行情平台提供的南京居住小区2009~2017年期间分季度平均售租价格信息,采用GIS空间分析等方法,考察南京中心城区“售租比”空间格局与演变过程。研究发现：① 城市整体“售租比”随房价波动变化明显,2016~2017年间快速增长;② 分异度先降后升,以城区内部差异为主,城区间差异越来越小;③ 高“售租比”小区多集聚于河西新城、江北新区等房价增速较快的投资热点区域。南京住宅“售租比”过快上升和空间离散加剧,意味着城市房价快速增长的合理性在降低。从地租视角解读,绝对地租决定着城市整体“售租比”的高低,级差地租和垄断地租则影响着城市内部“售租比”的空间分异。“售租比”可为判断城市内部房价相对合理性提供重要依据,但能否通过该指标准确预判城市房价风险程度及空间格局尚有待深入研究。     

Housing submarket classification: The role of spatial contiguity

Understanding housing submarket structure is of crucial importance to both public and private agencies. It can also help current and future homeowners make informed decisions on their residential choices. Current research on submarket focuses on comparative analyses of different classification techniques. Few studies, however, have examined the function of spatial contiguity on housing submarket classification. To address this issue, this paper developed a spatially constrained data-driven submarket classification methodology to obtain spatially integrated housing market segments. Specifically, a data-driven model based on principal component analysis and cluster analysis was developed for delineating housing submarkets. Within the model, a number of location attributes were used for principal component analysis, and the geographic locations of houses were also incorporated in the cluster analysis. The performance of this method was compared with other unconstrained data-driven techniques and a priori classifications using three measurements: substitutability, spatial integrity, and similarity. Results indicate that spatially contiguous submarkets can be obtained without compromising housing hedonic model accuracy and attribute homogeneity.     

Metropolitan Area Job Accessibility and the Working Poor: Exploring Local Spatial Variations Of Geographic context

Critical geographic perspectives argue that employment access in U.S. metropolitan areas is more complex than traditional understandings, calling for research utilizing approaches that reflect the spatially dynamic structure of cities. This study uses a job proximity indicator of employment access among the working poor, with cluster analysis and spatial regimes modeling, to explore the spatial dimensions of geographic context (neighborhood characteristics) at a localized scale. The findings indicate that: (1) patterns of high or low employment access are not consistent with neoclassical conceptualizations of metropolitan areas; and (2) the statistical relationship between geographic context indicators and the measure of job accessibility were not spatially constant, but varied across the urban landscape. This supports the critical geographic arguments that a high degree of complexity underlies the employment access problem. To better inform public policy, future empirical research needs access to more sophisticated data and methodological approaches to analyze this complex sociospatial phenomenon.     

城市道路与公共交通网络中心性对住宅租赁价格的影响研究——以北京市为例

住房市场化与较高住房需求带来住房价格的迅速提升,进而引发住房可负担性下降等问题,租赁住房逐步成为居民的另一主要择居方式。城市交通作为重要因素之一,对住宅租赁价格的影响仍需深入探讨。论文以北京市为例,运用交通网络中心性指标,研究道路网络及公共交通网络对住宅租赁价格影响的空间差异。结果表明：① 以出行时间为基础构建交通网络,公交网络总体拟合程度高于道路网络;公交网络中邻近中心性即相对可达性拟合程度最高,而道路网络中介中心性即中转功能拟合程度最高;② 城市中心-城市中部-城市外围的环状结构中,中心性影响程度存在空间差异,道路邻近中心性及公交各类中心性对城市中心及中部具有重要影响,城市外围主要受道路邻近中心性及介中心性影响;③ 基于拟合程度最高的公交网络邻近中心性的影响模式分析,综合交通枢纽、轨道交通换乘站点、轨道交通站点、重要地面公交站点等在城市中心及中部对租赁价格影响较高,而城市外围仅轨道交通站点及换乘站点影响较高;④ 道路设施网络与公交组织网络结构特性导向下的驱动力差异、交通网络各功能空间效应的区位指向、城市不同空间重要基础设施建设的外部效应差异促进了道路与公交网络中心性对租赁价格影响的空间分异。