Abstract: Abstract：Firstly, we established spatial lag regression model to estimate the population density of Su-Xi-Chang region based on NPP/VIIRS DNB, LJ1-01 nighttime light data original images and county level resident population data. Combining the regression functions of population and nightlight data, we arrived at two sets of gridded population density map with a spatial resolution of 500m×500m and 200m×200m, respectively. The accuracy of the two-gridded population dataset was estimated using demographic data at township level. The results prove that LJ1-01 data has higher precision in population spatialization study. Then, based on the correlation between electronic map point of interest (POI) data and population distribution, we optimized the simulation results of LJ1-01 original image by merging POIs. And the accuracy evaluation of population spatialization results was carried out at the township scale, also. The analysis shows that:(1) LJ1-01 night light image brightness value is significantly positively correlated with population, and the correlation coefficient is higher than NPP/VIIRS night light data.(2) Accuracy assessment results show that the night light of LJ1-01 is superior to NPP/VIIRS in population spatial processing research. We also show that the recently published LJ1-01 night light data is suitable for research on spatial processing of demographic data.(3) When the LJ1-01 night light data were combined with POIs, the complex correlation coefficient(R2) of the spatial lag regression model is increased to 0.946 3, indicating that this method can effectively improve the precision of population spatialization. Through the study of this paper, it can be find that the night light data of LJ1-01 has enormous potential value for the spatial processing of demographic data in the future.