多源信息耦合的GDP空间化研究—以北京市为例

针对统计数据对G D P空间分布信息表达存在的局限性,耦合G D P统计数据、城市兴趣点数据、夜间灯光数据以及土地利用数据,提出了一种G D P空间化方法.以北京市为实验区,首先,利用土地利用类型与GDP的关系,实现了第一产业GDP的100 m网格空间化;其次,通过计算兴趣点密度分布情况,并耦合夜间灯光指数以及土地利用...

Research of GDP Spatialization based on Multi-source Information Coupling:A Case Study in Beijing

Aiming at the limitations of statistical data on the spatial distribution information of GDP， a method of GDP spatialization was proposed by coupling GDP statistics， urban Point Of Interest（POI）， nighttime lighting data and land use data. First， taking Beijing as an experimental area， using the relationship between land use type and GDP， the 100m grid of the first industry GDP will be spatialized. Secondly， establishing the spatialized expression model of GDP in the second and third industries by determining coupling the POI kernel density， the nighttime lighting index and land use data. Spatially integrate the results of sub-industry and complete the GDP distribution results of Beijing with 100 m resolution finally. The results show that the multi-source coupling model with the POI is higher than the general nighttime light index single factor model. R² is increased from 0.84 to 0.92. The generated results can better reflect the spatial difference of regional GDP. The results show that multi-source coupling model can improve the spatialization accuracy of GDP. POI can effectively reflect the spatial distribution of GDP and provide data support for GDP spatialization.