Characterization of Sentinel-2A and Landsat-8 top of atmosphere, surface, and nadir BRDF adjusted reflectance and NDVI differences

The medium spatial resolution satellite data from the polar-orbiting Sentinel-2A Multi Spectral Instrument (MSI) and Landsat-8 Operational Land Imager (OLI) sensors provide 10 m to 30 m multi-spectral global coverage with a better than 5-day revisit. There are a number of differences between the sensor data that need to be considered before the data can be used together reliably. Sentinel-2A and Landsat-8 data for approximately 10 degrees x 10 degrees of southern Africa acquired in two summer (December and January) and in two winter (June and July) months of 2016 were compared. The data were registered and each orbit projected into 30 m fixed non-overlapping tiles defined in the sinusoidal equal area projection. Only corresponding sensor observations of each 30 m tile pixel that were both not cloudy, shadow, saturated, or cirrus contaminated, and that were acquired within one-day of each other, were compared. Both the Sentinel-2A MSI and Landsat-8 OLI data were atmospherically corrected using the Land Surface Reflectance Code (LaSRC) and were also corrected to nadir BRDF adjusted reflectance (NBAR). Top of atmosphere (TOA), surface reflectance, and NBAR, for the spectrally corresponding visible, near infrared (NIR) and shortwave infrared (SWIR) MSI and OLI bands, and derived normalized difference vegetation index (NDVI) (from the narrow NIR band for MSI), were compared and their sensor differences quantified by regression analyses. Atmospheric contamination and bi-directional reflectance differences were evident in the 65 million pairs of contemporaneous MSI and OLI observations considered. The MSI surface reflectance was greater than the OLI surface reflectance for all the bands except the green, red, and the broad MSI NIR bands, and the MSI surface NDVI was greater than the OLI surface NDVI. This pattern was also found in the NBAR sensor comparisons except for the red bands. Simulated MSI and OLI reflectance derived using the sensor spectral response functions and laboratory spectra showed similar results in the red, NIR and SWIR bands as the real data comparisons. Ordinary least squares (OLS) linear regressions of the 65 million pairs of contemporaneous MSI and OLI data for the three processing levels had good fits (r(2) > 0.87 for the TOA data comparisons, r(2) > 0.89 for the atmospherically corrected data comparisons, r(2) > 0.90 for the NBAR data comparisons; p-values < 0.0001). The OLS regression coefficients are provided so that they can be used to help improve the consistency between Sentinel-2A MSI and Landsat-8 OLI data.