Population, GDP, and Carbon Emissions as Revealed by SNPP-VIIRS Nighttime Light Data in China With Different Scales

Satellite-based artificial nighttime brightness observations are typically considered proxy measures of socioeconomic indicators at large scales, such as population, gross domestic product (GDP), and carbon emissions. However, few studies have explored and compared the correlations between Suomi National Polar Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (SNPP-VIIRS) nighttime light (NTL) data and socioeconomic indicators from administrative scale to grid scale and further analyzed the potential mechanisms for the dissimilar correlations at different grid scales. Using the regression model, dissimilarity index, and relief amplitude, the quantitative relationship and potential influence mechanism across different scales were investigated in this letter. Results show that the finer the scale is, the lower the correlations between total NTLs and socioeconomic indicators when comparing 1 km, town, and county scales. The determination coefficient ( ${R} ^{\mathbf {2}}$ ) values of the NTL-socioeconomic indicator correlations increase sharply with the increase of grid scale at 1–10 km scale. The ${R} ^{\mathbf {2}}$ values increase volatilely between 10 and 30 km but are relatively stable above 30 km. The differences in ${R} ^{\mathbf {2}}$ values may be attributed to the diversity and distribution balance of industrial types and relief amplitude at different scales. This letter provides new insights into estimating and predicting population, GDP, and carbon emissions by using SNPP-VIIRS data.

I. Introduction

Satellite-based artificial nighttime brightness observations are usually considered proxy measures of spatial behaviors in terms of population, economy, carbon emissions, and urbanization worldwide [1]. Great efforts have been made to demonstrate statistically significant correlations between human activities and nighttime lights, mainly derived from the operational linescan system (OLS) flown by the Defense Meteorological Satellite Program (DMSP) [2]. However, the inherent defects (e.g., lack of onboard calibration, saturation, and blooming) of DMSP-OLS data limit their accurate applications in socioeconomic estimations and evaluations [3]. As their successors, nighttime light data, derived from the Suomi National Polar Orbiting Visible Infrared Imaging Radiometer Suite (VIIRS) with the Suomi National Polar Orbiting Partnership (SNPP) satellite, provide more detailed human activities on nights with higher spatial, radiometric, and radiation resolutions than those of DMSP-OLS data [4]. The data have become the priority choice for socioeconomic indicator spatializations because many studies have proven that SNPP-VIIIRS data have better socioeconomic estimation ability than DMSP-OLS data [5], [6].