摘要
国内生产总值(GDP)是衡量地区经济发展水平的重要指标,GDP的空间化可以为灾害风险分析等多学科交叉研究提供基础数据。空间化代用数据的选择是社会经济统计数据空间化的关键,本文以京津冀地区作为研究区,将夜间灯光、全球人口密度(Land Scan)和亚洲人口密度(Asia Pop)空间分布信息作为代用数据,将市级GDP统计数据空间展布到栅格单元,以绝对误差、相对误差和均方根误差为指标,利用县级统计数据对展布结果进行误差分析,并对比3种数据对GDP空间模拟的表达效果。结果表明:相对于夜间灯光和Land Scan数据,Asia Pop模拟得到的综合误差最小;基于夜间灯光和Land Scan的GDP空间展布误差格局比较接近,即存在经济较发达的市辖区GDP值被低估、市郊区县GDP被高估的误差"两极区"倾向,而基于Asia Pop的GDP空间展布误差格局与经济发展水平关系不密切。因此,利用单一代用数据很难合理地反映经济活动的空间分布,综合夜间灯光、人口密度、道路和建筑物等多源空间数据是提高GDP空间展布精度的发展趋势。
As an important indicator in measuring the economic development level of a region, GDP spatialization is of great significance to study the socio-economic heterogeneity. The ancillary spatial density data selection is the key technique in controlling the GDP spatialization′s accuracy. In this paper, the prefectural GDP statistics is distributed to grid cells according to the spatial distribution information of GDP such as the population density（Land Scan, Asia Pop） and night light data in Beijing-Tianjin-Hebei. Moreover, the absolute errors and relative errors of the GDP disaggregation at county-level are both calculated in order to compare the errors among the three different ancillary data as mentioned above. These results can provide a reasonable reference to ancillary spatial density data selection in GDP disaggregation. The results show that, the spatial distributions of the three types of ancillary spatial density data for GDP have revealed their own advantages and disadvantages. Comparing with both of the night light and the Land Scan data, the Asia Pop simulation generally has the smallest error, especially in the suburban districts and rural areas of Beijing where the GDP tends to be overestimated, while the GDP is often underestimated in the economically developed city centers.For the Land Scan simulation, six counties have presented a relative error of more than 200%, as the Land Scan data are concentrated in Beijing and Tianjin, while the suburban districts and counties have also been overestimated. The Asia Pop simulation has only three counties（which locate in Tianjin） presenting a relative error being more than 200%. Because of the spatial heterogeneity of the economic activities, the GDP disaggregation error will increase with respect to the refinement of the administrative units, therefore, using the single-generation data to reasonably reflect the spatial distribution of economic activities is difficult, we need to take advantage of the distribution data such as the night light, roads,
出处
《地球信息科学学报》
CSCD
北大核心
2016年第7期969-976,共8页
Journal of Geo-information Science
基金
国家重大科学研究计划项目(2012CB955402)
国家自然科学基金项目(41571492)
教育部-国家外国专家局高等学校创新引智计划(B08008)
关键词
GDP空间化
京津冀
夜间灯光
人口密度
GDP spatialization
Beijing-Tianjin-Hebei
night light
population density
