重庆市房价与地价影响因素实证研究

房价与地价的影响因素多且因素之间相关关系复杂,本次研究通过收集整理重庆市房价与地价的相关数据,采用政策因素、宏观区位因素、微观区位因素、平均容积率因素、规划因素、路网密度因素来研究房价与地价之间的关系,通过建立因素间的通径图构建房价地价的结构方程模型,详细分析了各因素之间的影响关系.     

经济适用住房在城市中的空间分布——基于DEM的武汉市实例分析

经济适用住房作为具有保障性质的政策性住房,其在城市中的空间分布决定了居住其中的中低收入家庭在城市中的空间位置和聚散程度,这不仅是一个建设选址问题,也关系城市经济社会的发展。基于经济适用住房的特点,分析了经济适用住房在城市中空间分布的“两阶段性”,分布过程中面临的问题,并提出经济适用住房“空间福利”概念和计算方法;选取武汉市作为分析实例,基于GIS 平台和构建DEM的方法对武汉市经济适用住房的空间分布概况、空间福利比较以及微观面上的建设选址和空间质量分配问题进行了分析和探讨。     

THE MOST PERFECT EXAMPLE OF AN ALIEN ECOLOGY EVER CONSTRUCTED

Much science-fiction literature is based upon the creation and exploration of alternative environments. Stanley G. Weinbaum's short story, “Parasite Planet,”introduces an unusual environment that may be wrong in the light of recent evidence on Venus but still stimulates the geographical imagination.     

北京市居民住房需求结构分析

住房需求结构分析是制定住房政策和相关技术标准的基础。根据家庭收入、当前居住条件等指标来界定具有不同需求的居民群体, 以及确定适合各个层次的合理的住宅供给目标, 是住房政策中的一个具有重大现实意义的课题。为此, 从住房消费行为的微观视角出发, 对城市住房需求层次的定量划分以及需求结构的定量模拟问题进行了研究。首先, 分析了家庭人口、收入、当前住房面积、职业、住房区位、投资倾向和家庭结构变更预期等住房需求的影响因子及其相互作用关系。在此基础上, 提出了由住房需求层次模型和住房面积需求模型 相互嵌套而构成的住房需求结构的空间相互作用模型。其次, 运用北京市家庭住房需求的调 查数据, 对模型进行了检验分析。分析结果较好地再现了居民的住房需求, 不仅定量地给出了划分住房需求层次的适当门槛, 还揭示了不同需求层次的家庭在期待住房面积方面的数值差异。由此证明了通过住房需求结构的微观分析来确定相关需求主体的划分标准和住房面积 标准的可行性, 为住房政策研究提供了新的方法。     

代际传递视角下中国城市家庭住房产权获得——基于上海的实证研究

随着中国城市住房价格大幅上涨,住房可支付性成为青年面临的严峻挑战。尽管越来越多的研究开始关注中国城市住房不平等问题,但大多侧重住房资源分配由国家向市场的转移,相对而言,家庭在住房资源获取中的作用被忽视。本文选取上海市作为研究区域,使用2013年长三角社会变迁调查数据,以上海“80后”青年家庭为研究对象,重点关注夫妻双方父母的住房状况和社会经济属性对青年家庭住房产权获得的影响及性别差异。研究发现,父母户口很大程度上影响着青年家庭的住房结果;不同户口状况的父母住房财富存在较大分化,其影响着年轻家庭可获得的家庭购房资助的数额。与妻子父母相比,丈夫父母的户口状况对青年家庭住房结果的影响更大;而妻子父母在本地且拥有住房产权的双重优势与青年家庭住房产权获得有更强的正向联系。家庭背景对子代住房的影响结合婚姻匹配机制使住房优势或劣势在青年家庭内部累积,或会加剧住房分化现象。     

房产测绘中几个问题的探讨

房产测绘是房地产产权户籍管理中一项非常重要的工作,房产测绘应结合新的建筑设计规范和建筑施工新工艺、测绘新技术的要求,逐步完善房产测绘技术标准,使其更具可操作性,以解决房产测绘中实际可能出现的新问题。本文对房产测量中房屋面积测算过程中经常碰到的几个问题进行探讨,并提出一些自己的意见建议。     

房产测量规范在各地方实际应用中的差异

目前,全国许多地方的房产测绘工作在执行《房产测量规范》GB/T 17986.1-2000基础上,还额外执行地方发布的房屋建筑面积测绘计算规范,本文通过研究和分析房产测量规范和北京、上海、广州、深圳四个城市制定的房屋建筑面积计算方法,发现上述地方在执行房产测量规范中存在较大差异。     

Modelling housing unit density from land cover metrics: a Midwestern US example

Geographic applications frequently require the gathering and analysis of socioeconomic data. For many nations, these data are normally collected through a census. However, during the intercensal period (5–10 years), these data lose their currency and must be updated. The objective of this project was to estimate housing unit density from Landsat ETM+ imagery in the Terre Haute, IN, USA, region. Modelling was done for 1945 census blocks in the study area containing 30 972 housing units. Landtype, as represented by six cluster classes, was used as the primary surrogate for housing unit density. The percentage of each landtype within the census blocks was calculated. Other landscape metrics representing landtype patch dominance and diversity were also calculated on a per-block basis. Housing unit density within the census block was then modelled as a function of those percentages and metrics using discriminant analysis and multiple regression. The simple correlation between the observed and modelled housing unit density was 0.79. The mean residual error produced by the model was 0.37 housing units per hectare.     

An Analysis of the Relationship Between Housing Foreclosures,Lending Practices,and Neighborhood Ecology: Evidence from a Distressed County

Residential foreclosures increased sharply during the 1990s and in the first years of the twenty-first century. These foreclosures have profound impacts on the households and neighborhoods involved. Although foreclosures occur everywhere, the geography of foreclosures displays a pattern tied to a metropolitan area's social, fiscal, and economic geography. We examine these correspondences as they exist within Summit County (Akron), Ohio, between 2001 and 2003. Foreclosures themselves often result from unfortunate financial events that can affect any household, but we found that the geography of foreclosures corresponds primarily to Summit County's racial distribution, above and beyond any correspondence with income levels and housing fiscal stress. There also exists a clear coincidence of foreclosures with subprime lending, itself associated with Summit County's racial patterns. Concentrations of foreclosures in particular neighborhoods can be tremendously harmful to the social and economic health of the neighborhood. These comparisons help us to better understand the neighborhood ecology of foreclosure rates and subprime lending.     

Interdisciplinary,Cross-Cultural Research: Double Trouble∗

U.S. housing policy strengthens the local specificity of capital through support for homeownership and the mortgage lending industry. As access to capital and homeownership rates have grown, predatory lending has emerged as a significant danger to homeowners and their surrounding communities. The geographic distribution is not well understood, likely due to the unavailability of mortgage data to identify instances of predatory lending. This article examines the spatial distribution of predatory lending in Philadelphia, Pennsylvania, using public mortgage and property data. Predatory lending is spatially clustered within the city, suggesting a spatial component of abusive lending patterns not previously addressed. U.S. housing policy and intervention strategies designed to prevent and reduce the incidence of predatory lending should address the spatial aspects of predatory lending to target efforts and prevent weakening local connections between capital and communities.