芜湖市就业与居住空间匹配研究

借助偏离度指数分析法从宏观层面研究了芜湖市辖区的就业—居住空间匹配状况的变化特点,利用问卷调查数据,从微观角度分析了市区居民通勤的时间、距离、方式及费用。研究结果表明:芜湖市就业—居住空间匹配度趋于下降,核心区为服务业就业主导区,北部以制造业就业为主导功能,南部居住功能占主导,带来各区居住人口和就业人口的空间流动。居民通勤平均距离约为4km,平均时间约为25min,通勤方式以电动车、公交车为主。目前,居民对就业—居住地匹配状况的满意程度总体尚好,还需要采取措施以进一步提高满意度。     

龙岩地区商品房共有建筑面积分摊模型的探讨

针对共有建筑面积的分摊问题,依据《房产测量规范》(GB/T17986-2000)和国家、地方相关规定,通过规划行政审批的房屋结构功能和共有建筑面积分摊的级别,提出了共有建筑面积计算分摊的方法及其模型,并通过一个综合楼分摊实例进行了详细阐述。     

兰州市主城区房价分异及驱动因素研究

以2021年兰州市主城区678个居住小区房价数据为基础,引入地理场模型量化影响房价的外部因素,通过空间自相关分析、多尺度地理加权回归等模型对房价分异的空间格局及驱动因素的作用机理、带宽差异展开研究,以期为推动河谷型城市房产市场的公平发展提供参考。结果表明:(1)兰州市主城区平均房价为13739元·m^-2,空间上呈现“一主三副”的带状多中心组团式分布格局,房价由多中心向四周递减,价格相似的小区在地理空间上邻近分布,具有“小集中、大分散”的局部空间特征。(2)房价分异是多种驱动因素共同作用的结果,区位特征中的主商圈对房价的影响居于首位,建筑特征中的房龄、容积率和邻里特征中的中学数量、绿化率等对房价的影响较大,城市地理特征对房价具有显著影响,愈靠近黄河的小区、房价越高。(3)各驱动因素的带宽差异明显,主商圈、医院等小尺度变量存在高度空间异质性,而容积率、黄河等全局变量基本不存在空间异质性。     

北京市房价与地价的动态关系——基于结构方程模型的实证分析

城市房价与地价之间的关系错综复杂,不仅受多种因素的交织影响,相互之间也存在动态关系。研究房价与地价关系的传统方法,如Granger因果检验和回归分析等,无法刻画房价与地价之间多维的网络状关系,相比之下,结构方程模型能同时处理多个内生潜变量,且不受观测指标共线性的影响,为刻画地价与房价的交互作用提供了新的工具。从住房与土地市场的供需传导机制出发,推导出房价与地价的结构模型,以北京市为例,运用2003-2013年居住用地价格和2014年在售楼盘价格,与北京市GIS电子地图相匹配,提取商服中心可达性、公共交通可达性、道路可达性、商服繁华度、设施便利性等解释变量,构建地价与房价结构方程模型,分析二者之间的结构关系。     

Unraveling the multi-scalar residential segregation and socio-spatial differentiation in China: A comparative study based on Nanjing and Hangzhou

Residential segregation is a dual process of socio-spatial differentiation in residents and spatio-temporal heterogeneity in dwelling.However,most of the existing studies are es-tablished from the single perspective of urban residents based on demographic data,which is difficult to reveal the dynamics and complex spatial reconstruction within and between cities.With the characteristics of both stability and timeliness,the rapidly changing housing market is one of the processes and results of socio-spatial reconfiguration,and it is undoubtedly a better lens to observe residential segregation.This paper adopts methods such as multi-group segregation index,multi-scalar segregation profiles,and decomposition of segregation index,with Nanjing and Hangzhou as case cities,and establishes multi-scalar segregation profiles and comparative models based on three geographical scales of census tract,block and grid,and different residential types.A quantitative study was conducted on the degree and pattern of multi-scalar residential segregation in Nanjing and Hangzhou from 2009 to 2018.The pa-per found that the spatial segregation index is an improvement of the non-spatial segregation index.There are differences between Nanjing and Hangzhou in the evolution process of residential segregation.Nanjing has a higher degree of spatial differentiation as a whole,among which spatial components have a more significant impact.     

Analyzing Accessibility Using Parcel Data: Is There Still an Access–Space Trade-Off in Long Beach,California?

This article analyzes the impact of changing housing and neighborhood characteristics on the accessibility of neighborhood businesses using Long Beach, California, as a case study. Although advocates of smart growth and New Urbanism encourage land use mixing, aggregate-level analysis can be too coarse to pick up on fine-grained aspects of urban streetscapes. This study uses assessor parcel records and a point-based business establishment data set to analyze city-wide patterns of accessibility from individual dwelling units to thirty-one types of neighborhood businesses, including grocery stores, service shops, drug stores, doctor's offices, and banks. Regression results compare parcel-level and neighborhood-level drivers of accessibility between 2006 and 2015 to gauge the aggregated effect of recent economic, demographic, and built environment changes on this aspect of urban spatial structure. Larger homes in older, multiunit buildings and higher income neighborhoods show substantial increases in accessibility to most establishment types, suggesting a trend toward both greater accessibility and larger dwelling units—despite the traditional trade-off between access and space. Although gradual increases in home and business density increased overall accessibility over this period, weaker neighborhood-level results indicate that this trend is less pronounced in high-poverty and non-white areas.     

Housing differentiation and housing poverty in Chinese low-income urban neighborhoods under the confluence of State-market forces

ABSTRACT

Based on a large-scale household survey conducted in six large Chinese cities, this study is among the first attempts to juxtapose factors related to institution, market, and demography to examine the complex patterns and mechanisms of housing differentiation and housing poverty in low-income neighborhoods, which are conventionally conceived as homogenous substandard settlements. Results of Theil indices and multivariate regression models convey several interesting findings. First, the forces of the market and the State have projected different impacts on various aspects of housing status. Institutional factors had significant impacts on some costly and durable housing indicators such as housing tenure and housing area, while market forces have swiftly transformed the most malleable aspects of housing conditions, such as housing facilities, and will eventually replace some institutional legacies. Second, within-group housing differentiation is more palpable than between-group housing differentiation, suggesting that low-income neighborhoods in large Chinese cities are fluid and heterogeneous. Third, different institutional elements have different impacts on housing poverty. The well-functioning market remuneration system helps reduce the risk of housing poverty, yet working poor remains a severe problem. These findings can inform policies promoting social mix and housing affordability.     

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。     

London: a sustainable city?

Observations include:
Ian Livingstone, London: a sustainable city?, p.77
Michael Parkinson, Key challenges for European cities: achieving competitiveness, cohesion and sustainability, p.78
Chris Hamnett, London's housing, p.80
Sarah Curtis, Health in London, p.84
Martin Frost, London's transport—investing for sustainability, p.92
Chris Birks, Mike Owen and Brian Arkell, London's water resources: threat or opportunity, p.92
Sean D Beevers, David C Carslaw and Gary W Fuller, London's air quality: nitrogen dioxide and particles (PM10) in London's air—present and future, p.97
Adam D Read, Where there's muck there's brass—the 'cost' of London'swaste?, p.103     

Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices

Understanding scale effects is important and indispensable for geography studies. However, spatial and spatiotemporal statistical tools for measuring the operational scales of different processes are rather limited. This article extends the popular geographically and temporally weighted regression (GTWR) model to consider operational scale effects by proposing multiscale GTWR (MGTWR), which offers a flexible and scalable framework for identifying and analysing multiscale processes by specifying flexible bandwidths for various covariates. Then, MGTWR is employed to explore spatiotemporal variations and how influential factors are associated with housing prices in Shenzhen. This article attempts to extend GTWR to MGTWR in consideration of scale effects, thereby highlighting the importance of different levels of spatiotemporal heterogeneity. Furthermore, the empirical results of this study can provide valuable policy implications for real estate development in areas where urban planning should address multiscale effects in both temporal and spatial dimensions.