The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels

doi:10.3390/su9020305

	The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels
	Dai, Zhaoxin 1,2,3; Hu, Yunfeng 1,2; Zhao, Guanhua 1,2,3
刊名	SUSTAINABILITY
	2017-02-01
卷号	9 期号:2 页码:15
关键词	NPP/VIIRS DMSP/OLS GDP spatial scale suitability regression model suitability regional suitability
ISSN号	2071-1050
DOI	10.3390/su9020305
通讯作者	Hu, Yunfeng(huyf@lreis.ac.cn)
英文摘要	Nighttime light data offer a unique view of the Earth's surface and can be used to estimate the spatial distribution of gross domestic product (GDP). Historically, using a simple regression function, the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) has been used to correlate regional and global GDP values. In early 2013, the first global Suomi National Polar-orbiting Partnership (NPP) visible infrared imaging radiometer suite (VIIRS) nighttime light data were released. Compared with DMSP/OLS, they have a higher spatial resolution and a wider radiometric detection range. This paper aims to study the suitability of the two nighttime light data sources for estimating the GDP relationship between the provincial and city levels in Mainland China, as well as of different regression functions. First, NPP/VIIRS nighttime light data for 2014 are corrected with DMSP/OLS data for 2013 to reduce the background noise in the original data. Subsequently, three regression functions are used to estimate the relationship between nighttime light data and GDP statistical data at the provincial and city levels in Mainland China. Then, through the comparison of the relative residual error (RE) and the relative root mean square error (RRMSE) parameters, a systematical assessment of the suitability of the GDP estimation is provided. The results show that the NPP/VIIRS nighttime light data are better than the DMSP/OLS data for GDP estimation, whether at the provincial or city level, and that the power function and polynomial models are better for GDP estimation than the linear regression model. This study reveals that the accuracy of GDP estimation based on nighttime light data is affected by the resolution of the data and the spatial scale of the study area, as well as by the land cover types and industrial structures of the study area.
资助项目	National Key Research and Development Plan Program of China[2016YFB0501502] ; National Key Research and Development Plan Program of China[2016YFC0503701] ; National Science and Technology Major Project of China[00-Y30B14-9001-14/16]
WOS关键词	ELECTRIC-POWER CONSUMPTION ; GROSS DOMESTIC PRODUCT ; REMOTE-SENSING DATA ; URBANIZATION DYNAMICS ; ECONOMIC STATISTICS ; SATELLITE IMAGERY ; CHINA ; POPULATION
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	MDPI AG
WOS记录号	WOS:000395590500147
资助机构	National Key Research and Development Plan Program of China ; National Science and Technology Major Project of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/64761]
专题	中国科学院地理科学与资源研究所
通讯作者	Hu, Yunfeng
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Dai, Zhaoxin,Hu, Yunfeng,Zhao, Guanhua. The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels[J]. SUSTAINABILITY,2017,9(2):15.
APA	Dai, Zhaoxin,Hu, Yunfeng,&Zhao, Guanhua.(2017).The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels.SUSTAINABILITY,9(2),15.
MLA	Dai, Zhaoxin,et al."The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels".SUSTAINABILITY 9.2(2017):15.