Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area

CORC > 烟台海岸带研究所 > 中国科学院烟台海岸带研究所 > 中科院海岸带环境过程与生态修复重点实验室 > 海岸带信息集成与综合管理实验室

	Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area
	Chen, Qing 1,2,3; Hou, Xiyong1,3 ; Zhang, Xiaochun 4; Ma, Chun 4
刊名	INTERNATIONAL JOURNAL OF REMOTE SENSING
	2016
卷号	37 期号:19 页码:4610-4622
关键词	SATELLITE IMAGERY POPULATION-DISTRIBUTION ECONOMIC-ACTIVITY CONSUMPTION EMISSIONS
ISSN号	0143-1161
其他题名	Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area
通讯作者	Hou, XY (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China. Email:xyhou@yic.ac.cn
产权排序	[Chen, Qing; Hou, Xiyong] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China; [Chen, Qing] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China; [Chen, Qing; Hou, Xiyong] Chinese Acad Sci, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai, Peoples R China; [Zhang, Xiaochun; Ma, Chun] Stanford Univ, Carnegie Dept Global Ecol, Stanford, CA 94305 USA
英文摘要	Gross domestic product (GDP) reflects a nation or region's economic growth as a whole, and is the sum of product in the primary, secondary, and tertiary sectors of the economy in the area. However, statistical GDP data is problematic in integrated application with geographical data. The GDP spatialization data, which shows the GDP in grid cells and often is obtained by operating a spatialization model, is more useful than its officially published statistical data recorded by administrative units in both spatial representation and application. Thus, there is a need to improve the GDP spatialization models, and to present these models in a way as clear and transparent as possible. In this article, by taking China's continental coastal area as a case study area, we combined economic census data, land-use data, and night-time light data together, and developed a technique that we call the 'dynamic regionalization' method to improve the GDP spatialization products. We then created GDP spatialization models for three sectors of the economy (i.e. the primary, the secondary, and the tertiary sector) in 2000, 2005, and 2010, respectively. We find the following. (1) Because the 'overglow' effect of night-time light data has a bad influence on spatialization models, we used land-use data to distinguish the distribution plots of the tertiary sector on night-time light images. Compared with setting a threshold merely, land-use data can more effectively remove the 'overglow' effect. (2) Owing to the prominent spatial heterogeneity of GDP distribution in China's continental coastal area, building one spatialization model for the whole area would probably produce the estimated products with poor accuracy, so the 'dynamic regionalization' method was adopted to dynamically divide the whole study area into several subregions, and build separate spatialization models for each subregion. The accuracy assessment showed that the new method improved the accuracy of GDP spatialization data, especially in the area with high spatial heterogeneity.
学科主题	Remote Sensing ; Imaging Science & Photographic Technology
研究领域[WOS]	Remote Sensing ; Imaging Science & Photographic Technology
关键词[WOS]	SATELLITE IMAGERY ; POPULATION-DISTRIBUTION ; ECONOMIC-ACTIVITY ; CONSUMPTION ; EMISSIONS
收录类别	SCI
语种	英语
WOS记录号	WOS:000383576800006
内容类型	期刊论文
源URL	[http://ir.yic.ac.cn/handle/133337/17491]
专题	烟台海岸带研究所_海岸带信息集成与综合管理实验室
作者单位	1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 3.Chinese Acad Sci, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai, Peoples R China 4.Stanford Univ, Carnegie Dept Global Ecol, Stanford, CA 94305 USA
推荐引用方式 GB/T 7714	Chen, Qing,Hou, Xiyong,Zhang, Xiaochun,et al. Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2016,37(19):4610-4622.
APA	Chen, Qing,Hou, Xiyong,Zhang, Xiaochun,&Ma, Chun.(2016).Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area.INTERNATIONAL JOURNAL OF REMOTE SENSING,37(19),4610-4622.
MLA	Chen, Qing,et al."Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area".INTERNATIONAL JOURNAL OF REMOTE SENSING 37.19(2016):4610-4622.