统计研究 ›› 2022, Vol. 39 ›› Issue (7): 101-113.doi: 10.19343/j.cnki.11–1302/c.2022.07.008

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基于空间分布的房屋配套资源指数

“基于大数据的租赁房屋资源禀赋指数研究”课题组   

  • 出版日期:2022-07-25 发布日期:2022-07-25

Housing Supporting Facilities Index Based on Spatial Distribution

“Research on the Resource Endowment Index of Rental Housing Based on Big Data” Research Group   

  • Online:2022-07-25 Published:2022-07-25

摘要: 针对生活圈理论中配套设施的空间布局问题,本文结合专家经验与配套设施资源点空间分布信息,给出配套设施资源有效距离的确定方法,进而在构建房屋配套资源指数指标体系的基础上计算有效距离内的房屋配套资源指数。该指数不仅借助贝叶斯(Bayesian)思想使得有效距离的确定有了客观数据支撑,而且使用距离分位数和数量差异加强了具有相似配套资源小区间的区分度。本文以厦门市租赁房屋及其周边配套设施资源的兴趣点数据进行实证分析,结果表明:确定的有效距离使得有效距离内房屋配套资源指数的空间分布更接近正态分布,能更合理地评价各个小区的房屋配套资源丰富程度;该指数能够较好地体现对不同等级和不同类型配套设施的需求频率和需求偏好上的差异,更为准确地评价房屋所在小区周边可得的配套设施资源;厦门市思明区与湖里区租赁房屋周边的配套资源平均水平优于另外4个行政区,但均等化水平上湖里区与集美区较高。本文研究结果可为城市小区区位与配套设施的科学规划提供依据。

关键词: 生活圈评价, 配套资源指数, 贝叶斯推断, 秩效应权重, 兴趣点数据

Abstract: Aiming at the spatial arrangement of supporting facilities in the life circle theory, this paper combines expert experience and the spatial distribution information of supporting facilities resource points to give a method for determining the effective distance of supporting facilities. On the basis of constructing the index system of supporting resources for houses, the housing supporting facilities index within the effective distance is calculated. The index not only uses the Bayesian theory to determine the effective distance with objective data, but also uses distance quantiles and number differences to strengthen the discrimination between communities with similar supporting resources. An empirical analysis based on the Points of Interests data of Xiamen’s rental houses and their surrounding facilities resources shows that, the determined effective distance makes the spatial distribution of housing supporting resources index within the effective distance more like the normal distribution, and evaluates the abundance of supporting resources in each community more reasonably. The index could show the differences in demand frequency and demand preferences for different levels and types of supporting facilities better, and more accurately evaluate the available supporting facilities resources around the community where the house is located. The average levels of supporting resources around rental houses in Siming District and Huli District of Xiamen are better than those of the other four districts, but the level of equality is higher in Huli District and Jimei District. The research results could provide a basis for the scientific planning of locations and supporting facilities for the urban communities.

Key words: Life Circle Evaluation, Supporting Facilities Index, Bayesian Inference, Rank Effect Weights, POI Data