地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (5): 646-652.doi: 10.3724/SP.J.1047.2017.00646

• 地理空间分析综合应用 • 上一篇    下一篇

基于夜光遥感和小区POI的住宅发展与经济增长的空间耦合研究

潘思东()   

  1. 中国地质大学(武汉) 资源学院, 武汉 430074
  • 收稿日期:2016-08-04 修回日期:2016-11-08 出版日期:2017-05-20 发布日期:2017-05-20
  • 作者简介:

    作者简介:潘思东(1965- ),女,博士生,高级工程师,主要从事空间数据分析、矿产普查、经济调查研究及实验教学工作。E-mail:pansd65@163.com

  • 基金资助:
    江西省省直项目(2014085041);武汉市第三次全国经济普查项目(2015086013)

Spatial Coupling between Housing Development and Economic Growth Based on Night Light Remote Sensing and Residential POI

PAN Sidong*()   

  1. College of Resource, China University of Geosciences, Wuhan 430074, China
  • Received:2016-08-04 Revised:2016-11-08 Online:2017-05-20 Published:2017-05-20
  • Contact: PAN Sidong E-mail:pansd65@163.com

摘要:

针对城市住宅业发展与其经济增长之间的单向或双向因果关系问题,有关学者利用宏观统计分析的方法得到了不同的结论。本文通过构建二者的时空数据集,在城市内部微观层面上剖析了二者的耦合联系及其空间差异性,以期在细尺度上解释二者之间的关系。本文选取郑州市作为研究区,提出了一种基于夜光遥感数据的GDP空间化估算方法,进而生成GDP时空数据集;基于住宅小区POI点数据对城市住宅进行空间密度估计,得到住宅小区的时空分布数据集;最后对GDP和住宅建设密度进行了空间互相关分析,探究住宅发展与经济增长像元尺度上的共变趋势。结果表明:与前人的宏观研究论断不同,耦合分析结果显示住宅业发展与经济增长之间的关系在城市内部具有空间差异性,两者既存在相互影响的区域,也存在无相关的区域;耦合协调关系极显著的区域约占两成,且主要位于市属区和县域中心区;耦合不显著和不相关的区域超过七成,大部分位于市属县域。

关键词: 住宅发展, 经济增长, 空间耦合, 夜光遥感, 兴趣点

Abstract:

Against the one-way or two-way causality between urban housing development and economic growth, different conclusions are obtained by the relevant scholars via macro statistical analysis methods. In this paper, I explained the relationship between the two mentioned above at the fine scale, through construction of their temporal and spatial data sets and I analyzed their coupling relation and spatial difference at micro level of the city. Taking Zhengzhou City as an example, I proposed an estimation method of grid GDP (Gross Domestic Product) based on luminous index data to generate the spatial-temporal GDP data sets. Also, the spatial correlation analysis is carried out between the spatial-temporal GDP data sets and the spatial-temporal residential quarter data sets which are estimated by the Point of Interest (POI) of residential quarters. Different from previous macro studies, coupled analysis shows that the relationship between the development of housing industry and economic growth has spatial differences in the inner city. There are mutual influence areas in some places and uncorrelated areas in some other places. The grids of significant coupling coordinative relationship account for about 20%, and mainly are located in the municipal district and county central district while the grids that is not significant and not related account for over 70%, and are located in the counties mostly. In this paper, the spatial distribution of urban residence was made by the density estimation of the residential POI with construction area attribute, which is not available in the traditional social economic statistical data. I found that this kind of spatial distribution data of real estate can be used to study the spatial and temporal changes of urban housing, and make up for the deficiency of macro analysis.

Key words: residential development, economic growth, spatial coupling, luminous remote sensing, POI