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

Kaifang Shi,Jianping Wu,Bailang Yu,Liujia Chen,Yixiu Huang,Bing Yin,Zuoqi Chen,Yingjie Hu

doi:10.3390/rs6021705

Kaifang Shi, Jianping Wu + Show 6 more

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https://doi.org/10.3390/rs6021705

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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.

Highlights

Obtaining accurate and up-to-date information on the spatial dimensions of gross domestic product (GDP) and electric power consumption (EPC) is important to understanding a country’s social and economic status
The R2 value of the total nighttime light (TNL) from corrected NPP-VIIRS data with EPC was 0.8961 (Figure 5b), which was higher than that value from DMSP-OLS data with EPC
The results showed that the corrected NPP-VIIRS data could better reflect GDP and EPC in the provincial units than both

Summary

Introduction

Obtaining accurate and up-to-date information on the spatial dimensions of gross domestic product (GDP) and electric power consumption (EPC) is important to understanding a country’s social and economic status. Previous studies on GDP and EPC have mainly used statistical data for administrative units [1,2,3,4]. GDP, electricity production and coal consumption in mainland China from 1971 to 2009. Statistical data only provide numeric records for the socioeconomic situation of a specific region (e.g., census or administrative region), and the spatial distribution of those records is not explicitly represented. Appropriate approaches should be used as complements to the statistics data for estimating and mapping the spatial patterns of those socioeconomic indicators, such as GDP and EPC, in a statistical area [7]

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