Spatialization of GDP in Beijing using NPP-VIIRS data

doi:10.6046/gtzyyg.2016.03.04

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Abstract

In order to analyze spatial distributions of socioeconomic activities at pixel scale, the authors used Landsat8 and NPP-VIIRS night-time light images as data sources and produced spatialization maps of primary industry GDP and the secondary, tertiary industry GDP in Beijing. The land use map of Beijing for the spatialization was produced from Landsat8 image with CART decision-tree algorithm. According to the correlation results between the primary industry GDP and areas of land use, a linear regression model was built based on the primary industry GDP and areas of plough. By analyzing the correlation relationships between five light indexes and the secondary, tertiary industry GDP, compounded night light index (CNLI) and the secondary, tertiary industry GDP presented apparent power function's correlation relationship. Using linear corrections and summation of two types of pixel level's GDP density maps produced both modes listed above, and a total GDP density map was generated with the resolution of five hundred meters in Beijing. The results of GDP relative errors show that the primary industry GDP and the secondary, tertiary industry GDP were 0.86%, 0.61% and 1.37% respectively. This suggests that this approach of pixel level's GDP spatialization can be applied to estimate Beijing's GDP and reflect characteristics of its economic distribution.

Keywords Northern hemisphere of Mars OMEGA images HiRISE images seasonal ice cap melting curve

TP79

Issue Date: 01 July 2016

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	ZHAGN Dingkai
	LIU Zhaoqin
	DI Kaichang
	YUE Zongyu
	LIU Feng
	GOU Sheng

Cite this article:

ZHAGN Dingkai,LIU Zhaoqin,DI Kaichang, et al. Spatialization of GDP in Beijing using NPP-VIIRS data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 19-24.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.03.04 OR https://www.gtzyyg.com/EN/Y2016/V28/I3/19

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