Abstract: To accurately grasp the changes of the temporal and spatial pattern of carbon emissions and formulate regional differential emission reduction policies according to local conditions is a widely concerned in current society. Based on the night lighting data from 2000 to 2019 and the estimation of national energy carbon emissions, a fitting model is established to deduce the carbon emission data of prefecture-level cities, and then the spatial dependence of carbon emissions under the background of the rapid development of urbanization is studied from three aspects: carbon emission type, spatial aggregation and center of gravity transfer. The results show that the total carbon emission in China shows an upward trend from 2000 to 2019, with the growth rate and carbon emission intensity gradually slowing down as a whole. In the five inversion models for total night lighting data and provincial carbon emission data from 2000 to 2019, the quadratic model has the highest fitting degree, with R2 reaching 0.8261. Energy carbon emissions in China show an uneven distribution in space, with a basic pattern of high in the east and low in the west, and high in the north and low in the south. From 2000 to 2019, the regional differencesand spatial accumulation of carbon emissions is becoming more and more obvious, and the spatial distribution of carbon emission center has generally shifted from west to east.

Key words: nighttime light data, CO2 emissions, spatio-temporal characteristics, center of gravity transfer