Abstract
The LJ1-01 satellite is the first dedicated nighttime light remote sensing satellite in the world and offers a higher spatial resolution than the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) satellites of the United States. This study compared the LJ1-01 nighttime light data with NPP/VIIRS data in the context of modeling socio-economic parameters. In the eastern and central regions of China, 10 parameters from the four aspects of gross regional product (annual average population, electricity consumption, and area of land in use) were selected to build linear regression models. The results showed that the LJ1-01 nighttime light data offered better potential for modeling socio-economic parameters than the equivalent NPP/VIIRS data; the former can be an effective tool for establishing models for socio-economic parameters. There were significant positive correlations between the two types of nighttime light data and the 10 socio-economic parameters; that for the gross regional product was the highest.
Highlights
Socio-economic parameters are of great value in the context of government policies and scientific research
The GRP includes the gross regional product of the total city and the gross regional product of districts within the city; it is expressed in units of 10,000 yuan
The regression results for the two parameters show that the correlation between the LJ1-01 data and the GRP was higher than the same for the National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) data
Summary
Socio-economic parameters are of great value in the context of government policies and scientific research. Elvidge et al [8,9,10,11] evaluated the quantitative relationship between nighttime light images and the population and gross domestic product (GDP). Ma et al [12] examined the high correlation between the population, GDP, electricity consumption, and area of paved roads with nighttime light data on a small scale. Nighttime light data can provide an important basis for the estimation of socio-economic parameters, such as the gross regional product (GRP) [13,14,15,16,17], annual average population [18,19,20], electricity consumption [2,3], and area of land in use [12,21]
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