Validation of VIIRS and MODIS reflectance data in coastal and oceanic waters: An assessment of methods Remote Sensing of Environment

Satellite ocean color datasets have vast potentials for assessing and monitoring of marine environments. However, with the MODIS sensor aging and the VIIRS sensor reaching maturity, it is important to continuously evaluate the quality of reflectance data from both instruments. Here, we critically assess the statistical performance of both MODIS and VIIRS, including analysis of two separate (and commonly used) VIIRS processing routines. In addition, we note variability in the literature as to the methods used to identify and remove low-quality data during similar validation exercises. Although most studies use some implementation of satellite quality flags (L2 flags) and many exclude data based on spatial heterogeneity or large temporal gap from satellite overpasses, critical assessment of these methods indicates variable performance. Indeed, we found little improvement in validation statistics after implementation of these data culling techniques, with substantial variability in effectiveness between wavebands and sensors. Overall, these findings highlight the need to critically assess the impact (on both data quantity and quality) of exclusion criteria, towards more effective techniques to ensure quality and consistency of satellite ocean color datasets. Grant no. NA15OAR4320064