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

Abstract

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 OPEN ACCESSRemote Sens. 2014, 6 1706 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 R 2 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.

Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review

“…Although nighttime images collected from the VIIRS sensor have been released, empirical research based on these datasets is rare. Comparing results of studies on the same research topic between the old OLS images and the new VIIRS images will allow us to further understand the advancement and intrinsic limitations of the new database [80][81][82][83][84]. Therefore, it can answer a series of research questions, such as how does the VIIRS images perform in overcoming the saturation and blooming phenomena in OLS images; does the improved quality of VIIRS images contribute to better estimations of social-economic parameters, and how to fuse the data from the two sensors?…”

Implementation

“…See Methods for further information 4.3 Economic Disparity light emitted by Earth's surface at wavelengths between 500 and 900 nanometer (nm), 14 at extremely high spatial resolution (Hillger et al 2013;Liao et al 2013). Spatial patterns of night lights from VIIRS have been shown to exhibit high correlation with gross domestic product and electricity power consumption (EPC) in China, at multiple spatial scales (Shi et al 2014).…”

Reviews of Geospatial Information Technology and Collaborative Data Delivery for Disaster Risk Management

“…Although this feature is useful for any phase of DRM, it is especially useful for planning purposes. Although satellite remote sensing can be used to observe physical characteristics of the land surface, several studies have developed socioeconomic datasets relevant to vulnerability assessment, such as urban expansion [32,33], population [34], and gross domestic product (GDP) [35,36], by using a combination of satellite-based data and socioeconomic statistics.…”