Abstract: In this paper, the DMSP/OLS image data is corrected by mutual invariance, continuity correction and oversaturation correction. The corrected DMSP/OLS data is used as a reference to reclassify the VⅡRS/DNB data. The two image data are used in time. The VⅡRS/DNB data fitted to the overlapping area in the space and the results are evaluated to obtain long-term continuous and stable nighttime lighting data. At the same time, the relationship between image data and social and economic indicators of Xinjiang regional corrections, the total population at the end of the year, total production value, average daily power consumption, construction land use are established, and the ability of nighttime lighting data to simulate social and economic parameters under long-term sequence is explored. The results show that the nighttime light image after correction by the invariant object method is more stable and continuous, which reduces the magnitude difference of the DN value between the VⅡRS/DNB data and the DMSP/OLS data pixel, making the light data under long-term sequence comparable. The correlation between long-term sequential nighttime lighting data and socioeconomic parameters after correction is high, indicating that the corrected long-term sequence light image data is consistent with socioeconomic indicators at the provincial level.

Key words: DMSP/OLS images, VIIRS/DNB images, invariant target method, socioeconomic parameter