基于夜间灯光与土地利用数据的山东省乡镇级人口数据空间化

doi:10.12082/dqxxkx.2019.180497

地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (5): 699-709.doi: 10.12082/dqxxkx.2019.180497

• 地理空间分析综合应用 • 上一篇下一篇

基于夜间灯光与土地利用数据的山东省乡镇级人口数据空间化

王明明^1,²(), 王卷乐^2,^3,^*()

1. 山东理工大学建筑工程学院,淄博 255049
2. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101
3. 江苏省地理信息资源开发与利用协同创新中心,南京 210023

收稿日期:2018-09-29 修回日期:2019-02-25 出版日期:2019-05-25 发布日期:2019-05-25
通讯作者: 王卷乐 E-mail:wangmm@lreis.ac.cn;wangjl@igsnrr.ac.cn
作者简介:
作者简介：王明明（1993-）,男,河北沧州人,硕士生,主要从事人口数据空间化研究。E-mail: wangmm@lreis.ac.cn
基金资助:
中国科学院战略性先导科技专项（A类）（XDA19040501）;中国科学院“十三五”信息化专项科学大数据工程项目（XXH13505-07）

Spatialization of Township-level Population based on Nighttime Light and Land Use Data in Shandong Province

Mingming WANG^1,²(), Juanle WANG^2,^3,^*()

1. School of Civil and Architectural Engineering,Shandong University of Technology,Zibo, 255049, China
2. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

Received:2018-09-29 Revised:2019-02-25 Online:2019-05-25 Published:2019-05-25
Contact: Juanle WANG E-mail:wangmm@lreis.ac.cn;wangjl@igsnrr.ac.cn
Supported by:
the Strategic Priority Research Program of the Chinese Academy of Sciences, No.XDA19040501;the Specific Informatization Scientific Research Science Program of the Chinese Academy of Sciences, No.XXH13505-07.

摘要/Abstract

摘要：

格网化人口数据能够刻画实际人口空间分布状况,是实现人口数据更好地与自然、社会、经济等要素融合分析的有效途径。本文面向精细尺度格网人口数据的需求,以中国东部人口稠密的山东省为例,基于乡镇级人口统计数据,研究了结合夜间灯光和土地利用数据的空间化方法。其中以EVI修正DMSP/OLS夜间灯光数据来增加城镇用地内部人口分布的差异性,以城乡二级分区方法避免夜间灯光数据在农村低辐射亮度区模拟人口的缺点,提高了建模精度。利用其余地区的人口统计值检验建模精度,结果有78%的行政单元的相对误差绝对值小于20%。最终在2000年首次公布的乡镇级人口统计数据的基础上,生成了山东省100 m格网人口分布数据SDpop2000。通过与精度较高的全球WorldPop人口数据产品对比可见,SDpop2000和WorldPop在10 km网格尺度上的相关性系数高达0.93;SDpop2000在鲁中部、泰安西南部、济宁南部、临沂南部、枣庄北部和鲁北沿海等地的人口分布明显比WorldPop更准确;且SDpop2000较好地刻画了山东省在鲁西、鲁北平原区的人口较鲁中南山地丘陵区、鲁北沿海和山东半岛丘陵区的人口更为稠密的人口分布趋势。本文构建的基于DMSP/OLS与土地利用的乡镇级人口数据空间化方法明显提高了空间化精度,适用于乡镇尺度的人口精细模拟。

关键词: 人口, 空间化, 夜间灯光数据, 土地利用数据, 乡镇级, 山东省

Abstract:

Gridded population data can be used to describe the actual spatial distribution of populations and is an effective way to achieve better integration of population data with natural, social, and economic factors. This study analyzed the demand of fine-scale gridded population data. Taking the densely populated Shandong Province in eastern China as an example, the spatialization method of township-level demographic data was investigated using nighttime satellite data and land use data fusion modeling. In this process, EVI was used to reduce saturation of DMSP/OLS nighttime satellite data to increase the difference of population distribution within the urban land. The urban and rural two-level partition method was used to avoid the shortcomings of nighttime data in the low radiance area of rural areas. The demographic values from the rest region were used to evaluate the modeling accuracy, and the results showed that 78% of the administrative units had an absolute relative error of less than 20%. Finally, based on the population data of the township-level which was first published in the fifth census in 2000, the gridded population data SDpop2000 at 100 m- resolution in Shandong Province was generated. The SDpop2000 was compared with the global WorldPop population data product with higher precision. The results showed that the correlation coefficient between SDpop2000 and WorldPop on the 10 km grid scale was as high as 0.93, and the population distribution of SDpop2000 was obviously more accurate than that of WorldPop in the central Shandong, southwestern Taian, southern Jining, southern Linyi, northern Zaozhuang, and the northern Shandong coastal areas. In addition, the SDpop2000 better described the population distribution trend in Shandong Province, which was denser in western Shandong and the plains of northern Shandong than in the mountainous hilly areas in the central and southern Shandong, the coast of northern Shandong, and the hilly area of Shandong Peninsula. Overall, the spatialization method of township-level population data developed in this study significantly improved spatialization precision and is suitable for township-level population spatialization.

Key words: population, spatialization, nighttime light data, land use data, township-level, Shandong Province

王明明, 王卷乐. 基于夜间灯光与土地利用数据的山东省乡镇级人口数据空间化[J]. 地球信息科学学报, 2019, 21(5): 699-709.DOI:10.12082/dqxxkx.2019.180497

Mingming WANG, Juanle WANG. Spatialization of Township-level Population based on Nighttime Light and Land Use Data in Shandong Province[J]. Journal of Geo-information Science, 2019, 21(5): 699-709.DOI:10.12082/dqxxkx.2019.180497

图/表 10

图1

图2

表1

各地区分区和建模结果"

分区		行政单元数/个	建模结果	方程拟合优度系数
城镇地区	$A 1$	31	$po p c = 0.165 × EANTLI + 8399.931$	0.992
农村地区	$A 2$	181	$po p v 2 = 0.0025 × are a v 2 + 3210.143$	0.778
	$A 3$	724	$po p v 3 = 0.004 × are a v 3 + 6403.842$	0.763
	$A 4$	181	$po p v 4 = 0.006 × are a v 4 + 8873.137$	0.838
其余地区	$A 5$	322	—	—
	$A 6$	177	—	—
	$A 7$	210	—	—

表1

表2

各建模区域行政单元人口统计值同各要素之间的相关性"

分区		耕地	林地	草地	水系用地	未利用地	城镇用地	农村居民点	其他建设用地	EANTLI
城镇地区	$A 1$	0.294	0.093	0.092	0.204	0	0.819**	0	-0.095	0.996**
农村地区	$A 2$	0.524**	0.022	-0.133	-0.160*	-0.184*	0	0.883**	-0.216**	0.228**
	$A 3$	0.635**	0.015	0.09*	0.025	-0.027	0	0.873**	0.034	0.279**
	$A 4$	0.595**	-0.227	-0.068	0.053	0.045	0	0.915**	0.112	0.143

表2

图3

图4

图5

图6

图7

图8

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基于夜间灯光与土地利用数据的山东省乡镇级人口数据空间化

Spatialization of Township-level Population based on Nighttime Light and Land Use Data in Shandong Province

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