A Method to Reduce Saturation of DMSP/OLS Nighttime Light Data for Introducing Road Network and Building Information

A new composite index for efficiently reducing the saturation problem of nighttime light data has been proposed in this study. It introduces the elements of road network and buildings. It assumes that the lighting of road network and buildings contributes more to the DN(digital number) values of the image. The results were analyzed and compared to EANTLI(enhanced vegetation index adjusted nighttime light index) in three aspects:(1)The ability to distinguish objects within city; (2)The degree of fitting with radiation calibration data; (3)The ability to estimate electricity consumption. Experimental results show that composite index has obvious advantages in the details of the interior of the city and the ability to distinguish objects. And the determination coefficient for single row can be up to 0.928, which can be increased by 0.1 compared to EANTLI. And the determination coefficient can reach 0.901 in the estimation of electric power consumption. In conclusion, the composite index can effectively reduce nighttime light data saturation in urban centers and has certain reliability.