measurement of Beijing’s economic development by nighttime light using Suomi-NPP VIIRS DNB data

Abstract

New satellite images of the Earth at night can be achieved with earth observation by continuous remote sensing throughout all day. The images give the most complete view of contemporary global human settlement, especially cities. Beijing is the capital, one of the most important and typical big cities of China. This study estimated economic activities of Beijing using remote sensing nighttime earth surface light data from S-NPP VIIRS DNB night data with corrections, with a focus on the relationship between economic index and city lights. Our study aims to eliminate the influence of cloud, moonlight and atmosphere on artificial light sources at night, in order to achieve more accurate inversion of ground artificial light source information. The results proved that there is a strong linear regression relationship between corrected DNB nighttime data and GDP with 0.79405 fitting coefficient, which was higher than the linear fitting coefficient (0.2817) of average radiance composite images data and GDP. The linear fitting coefficient of the tertiary industry and corrected DNB nighttime data is 0.76102 is higher than 0.1836 of the tertiary industry and average radiance composite images data. Therefore, the approach was provided for the dynamic evaluation of social and economic data, and the developed urban light fusion product will lay a foundation for the derivative application of backend and the inversion and application of night light data in other locations.