The variability of the remote sensing reflectance, Rrs, now routinely retrieved from ocean color (OC) and high spatial resolution sensors, is often used to characterize water variability due to changes in inherent optical properties of the water body. At the same time, Rrs is partially variable because of uncertainties in its retrieval in the process of atmospheric correction. Using data from SNPP-VIIRS and Landsat-8 OLI sensors, the contribution of the main components to the variance of Rrs due to its spatial variability is determined based on a model in which variances were considered proportional to the mean values of the corresponding components. It is shown that there is practically no spatial variability in the open ocean waters and water variability is proportional to the spatial resolution of the sensor in coastal waters. Variances due to surface effects, inaccuracies of aerosol models, and sunglint can contribute significantly to Rrs variance, which characterizes Rrs spatial variability, with variances due to the water variability itself often being significantly smaller.
Uncertainties in the retrieval of remote sensing reflectance, Rrs, from Ocean Color (OC) satellite sensors have a strong impact on performance of algorithms for the estimation of chlorophyll-a concentrations and inherent optical properties (IOPs). Uncertainties are highest in the blue bands, especially in coastal waters with low blue-band Rrs values. We recently showed that the main uncertainty contributions when observing at sun glint-optimized geometries are due to two components: variability of in-water parameters and skylight reflected from the water surface. Sunlight propagates to the water and back to the top of the atmosphere (TOA), capturing the instantaneous state of in-water conditions and sky light reflected from the wind-roughened wave facets. Both processes are averaged with the spatial resolution of the sensor. This results in the satellite measured TOA radiance spectrum, which is typically different from vector radiative transfer simulations that are based on the mean values of sea surface reflectance coefficient. Preliminary analysis shows that these two uncertainty components are spatially highly variable. Using the recently released provisional Aquatic Reflectance product for Landsat 8, we analyzed spatial scales of these components for multiple scenes in the open ocean and coastal waters at spatial resolutions ranging from 30 m to several kilometers.
A novel polarization camera (Teledyne DALSA) based on the Sony first polarization imaging sensor provides a high resolution broadband image of the object in 400-900 nm spectral range, where each pixel contains four subpixels bearing built-in linear polarizers oriented at the 0, 45, 90 and -45 degrees. With an additional lens it has a field of view (FOV) of about 40° degrees. The camera was equipped with a filter wheel containing five band-pass filters, thus providing multispectral, multi-angular high quality polarimetric data with high spatial resolution. The camera has undergone radiometric calibration and was used in various illumination conditions and water environments in NYC area. Spatial and temporal distribution of water and sky Stokes vector components were characterized at various wind speeds. Polarization images were also used for the estimation of wave slope statistics from the ocean surface. Results are compared with concurrent measurements of total and polarized radiances by a state-of-the-art snapshot hyperspectral imager, which simultaneously acquires spectra with 4 nm spectral resolution in the wavelength range of 450- 750nm, also with a 40° FOV for 20 - 60° viewing angles. A computer-controlled filter wheel was installed in front of the imager, allowing division-of-time Stokes vector images from the ocean surface. The combination of these two instruments allows to observe spectral and polarization properties of the wind-roughened ocean at high spatial and temporal resolution, with the goal of advancing our understanding of the air-water interface and in-water light propagation.
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