Remote Sens. 2014, 6(2), 1705-1724; doi:10.3390/rs6021705
Article

Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data

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Received: 9 December 2013; in revised form: 5 February 2014 / Accepted: 14 February 2014 / Published: 20 February 2014
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The nighttime light data records artificial light on the Earth’s surface and can be used to estimate the spatial distribution of the gross domestic product (GDP) and the electric power consumption (EPC). In early 2013, the first global NPP-VIIRS nighttime light data were released by the Earth Observation Group of National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAA/NGDC). As new-generation data, NPP-VIIRS data have a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. This study aims to investigate the potential of NPP-VIIRS data in modeling GDP and EPC at multiple scales through a case study of China. A series of preprocessing procedures are proposed to reduce the background noise of original data and to generate corrected NPP-VIIRS nighttime light images. Subsequently, linear regression is used to fit the correlation between the total nighttime light (TNL) (which is extracted from corrected NPP-VIIRS data and DMSP-OLS data) and the GDP and EPC (which is from the country’s statistical data) at provincial- and prefectural-level divisions of mainland China. The result of the linear regression shows that R2 values of TNL from NPP-VIIRS with GDP and EPC at multiple scales are all higher than those from DMSP-OLS data. This study reveals that the NPP-VIIRS data can be a powerful tool for modeling socioeconomic indicators; such as GDP and EPC.
Keywords: NPP-VIIRS; DMSP-OLS; gross domestic product; electric power consumption; linear regression; nighttime light data; China
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MDPI and ACS Style

Shi, K.; Yu, B.; Huang, Y.; Hu, Y.; Yin, B.; Chen, Z.; Chen, L.; Wu, J. Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data. Remote Sens. 2014, 6, 1705-1724.

AMA Style

Shi K, Yu B, Huang Y, Hu Y, Yin B, Chen Z, Chen L, Wu J. Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data. Remote Sensing. 2014; 6(2):1705-1724.

Chicago/Turabian Style

Shi, Kaifang; Yu, Bailang; Huang, Yixiu; Hu, Yingjie; Yin, Bing; Chen, Zuoqi; Chen, Liujia; Wu, Jianping. 2014. "Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data." Remote Sens. 6, no. 2: 1705-1724.

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