Impact of Image Saturation on Radiometric Intercalibration of DMSP/OLS Nighttime Light Images

Abstract

This article aims to evaluate impact of image saturation on radiometric intercalibration of Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) stable nighttime light (NTL) images. We simulated two sets of stable NTL images, one with saturation and the other without saturation, by using DMSP/OLS radiance calibrated images without saturation. For each dataset, we intercalibrated the simulated images of seven years using a quadratic regression model. We found that the saturation-derived difference of the radiometric intercalibration is more obvious in areas where the digital number value is higher than a certain value (e.g., ∼30). By comparing the calibrated images of the two datasets, we found that the absolute value of the saturation-derived relative bias of the intercalibration tends to be positively correlated to the ratio of saturated pixels in the calibration field, with Pearson correlation of 0.4610 ($p$ < 0.01). Besides, the absolute value of the saturation-derived relative bias is positively correlated to the nonlinearity of the data relationship in the calibration field (measured by the difference between the ${{\boldsymbol{R}}^2}$ of quadratic regression and linear regression), with Pearson correlation of 0.6398 ($p$< 0.01). These findings indicate that the image saturation impacts the intercalibration of the DMSP/OLS stable NTL images, and the impact is affected by the image characteristics.

Keywords

• Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS)
• intercalibration
• nonlinearity
• quadratic regression model
• saturation