基于夜间灯光数据的天山北坡城市群第二、三产业GDP空间化模拟

doi:10.3969/j.issn.0255-8297.2019.01.009

摘要/Abstract

摘要：

针对城市群中小尺度资源环境研究领域对空间型社会经济数据的需求，对天山北坡城市群10个主要县市的第二、三产业国内生产总值（gross domestic product，GDP）进行空间化模拟.采用相关分析与回归分析方法，定量分析2002年和2012年DMSP/OLS（defensemeteorological satellite program/operational line scan system）夜间灯光数据与天山北坡城市群统计型数据的关系，建立天山北坡城市群1 km的GDP密度图，GDP空间分布模拟结果在分产业水平上拥有较高精度.结果表明：1）两期夜间灯光指数与第二、三产业值具有明显相关性，第二产业相关系数为0.75、0.83；第三产业相关系数为0.86、0.87；2）从GDP空间分布来看，高值区主要集中在乌鲁木齐-昌吉-石河子-奎屯-克拉玛依一线；各县市GDP密度由城市核心区向周围区域辐射递减，城郊和农村地区的GDP密度显著低于建成区的GDP密度；3）基于夜间灯光数据模拟的GDP空间分布结果十分可信，尤其是第二产业2002年和2012年的GDP模拟结果与统计值的相对误差分别为0.58%、0.01%.通过对比两期的GDP空间化模拟结果发现：该方法在一定程度上反映了天山北坡城市群经济发展的动态变化，对后期更加准确地预测此区域经济走势具有实用价值.

关键词: 夜间灯光数据, 天山北坡城市群, 第三产业, 第二产业, 国内生产总值, 空间化模拟

Abstract:

For the demand of small scale resources and environment of research on spatial model of social and economic data,a spatial simulation is conducted on the secondary and tertiary industry gross domestic product (GDP) of the 10 major cities and towns in the city cluster on northern slope of Tianshan Mountains. By using correlation and regression analysis methods, we quantitatively analyze the relations between DMSP/OLS (defense meteorological satellite program/operational line scan system) night light data and the urban agglomeration census data of northern slope of Tianshan Mountain in 2002 and 2012. And we build a 1 km GDP density map of the urban agglomeration of northern slope of Tiashan Mountain. The simulated spatial GDP distribution consistent precisely with the distribution of industry level of the region. First, it is indicated that the night light exponent of the two periods has obvious dependency on secondary and tertiary industries. The correlation coefficients are 0.75 and 0.83 for secondary industry, and 0.86 and 0.87 for tertiary industry. Second, it is seen that high value areas mainly gather in the line of Urumqi-Changji-Shihezi-Kuytun-Karamay. The interior GDP density of each county or city radiates decreasingly from the center to surroundings. The GDP density of suburban and rural areas are significantly lower than that of established districts. Third, the GDP distribution based on DMSP/OLS night light data simulation is reliable. The relative errors between GDP spatial simulations and statistical values of secondary industry in 2002 and 2012 are only 0.58% and 0.01% respectively. The comparison of GDP spatial simulations of the two periods reflects the dynamic change of the economic development of the urban agglomeration of northern slope of Tianshan Mountain, which is of practical value for more accurate prediction of the regional economic trend.

Key words: spatial simulation, northern slope of Tianshan Mountains urban agglomeration, secondary industry, tertiary industry, night light data, gross domestic product (GDP)

中图分类号:

F301.24

阿孜古丽·合尼, 高倩, 阿里木江·卡斯木. 基于夜间灯光数据的天山北坡城市群第二、三产业GDP空间化模拟[J]. 应用科学学报, 2019, 37(1): 87-98.

AZIGULI Heni, GAO Qian, ALIMUJIANG Kasimu. On Spatial Simulation of Secondary and Tertiary Industrial GDP in Northern Slope Tianshan Mountains Urban Agglomeration Based on Night Light Data[J]. Journal of Applied Sciences, 2019, 37(1): 87-98.

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