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。
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.
出处
《地球信息科学学报》
CSCD
北大核心
2017年第5期646-652,共7页
Journal of Geo-information Science
基金
江西省省直项目(2014085041)
武汉市第三次全国经济普查项目(2015086013)
关键词
住宅发展
经济增长
空间耦合
夜光遥感
兴趣点
residential development
economic growth
spatial coupling
luminous remote sensing
POI
