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The Planet SuperDove sensors produce eight-band, three-meter resolution images covering the blue, green, red, red-edge, and NIR spectral bands. Variations in spectral response in the data used to perform atmospheric correction combined with low signal-to-noise over ocean waters can lead to visible striping artifacts in the downstream ocean-color products. It was determined that the striping artifacts could be removed from these products by filtering the top of the atmosphere radiance in the red and NIR bands prior to selecting the aerosol models, without sacrificing high-resolution features in the imagery. This paper examines an approach that applies this filtering to the respective bands as a preprocessing step. The outcome and performance of this filtering technique are examined to assess the success of removing the striping effect in atmospherically corrected Planet SuperDove data. [ABSTRACT FROM AUTHOR]

An increasing number of commercial nanosatellite-based Earth-observing sensors are providing high-resolution images for much of the coastal ocean region. Traditionally, to improve the accuracy of normalized water-leaving radiance ( n L w ) estimates, sensor gains are computed using in-orbit vicarious calibration methods. The initial series of Planet nanosatellite sensors were primarily designed for land applications and are missing a second near-infrared band, which is typically used in selecting aerosol models for atmospheric correction over oceanographic regions. This study focuses on the vicarious calibration of Planet sensors and the duplication of its red band for use in both the aerosol model selection process and as input to bio-optical ocean product algorithms. Error measurements show the calibration performed well at the Marine Optical Buoy location near Lanai, Hawaii. Further validation was performed using in situ data from the Aerosol Robotic Network—Ocean Color platform in the northern Adriatic Sea. Bio-optical ocean color products were generated and compared with products from the Visual Infrared Imaging Radiometric Suite sensor. This approach for sensor gain generation and usage proved effective in increasing the accuracy of n L w measurements for bio-optical ocean product algorithms. [ABSTRACT FROM AUTHOR]

Since the October 2011 launch of the VIIRS (Visible Infrared Imaging Radiometer Suite) instrument, a number of inter-sensor comparisons between VIIRS and MODIS (Moderate Resolution Imaging Spectroradiometer) radiances have been reported. Most of these comparisons are between calibrated radiances and temperatures based on observations of the two sensors from simultaneous nadir overpasses (SNO). Few comparisons between the retrieved ocean color data products, such as chlorophyll concentration, from VIIRS and MODIS data have been reported. Retrievals from measured data at large solar zenith angles and large view zenith angles are excluded from these comparison studies. In this paper, we report the inter-sensor comparisons between VIIRS and MODIS data acquired over the Chesapeake Bay and nearby areas with relatively large differences in sensor view angles. The goal for this study is to check the consistency between MODIS and VIIRS ocean color data products in order to merge the products from the two sensors. We compare total radiances (Lt) at the top of atmosphere (TOA) and the ocean color (OC) data products derived with the automatic processing system (APS) from both VIIRS and MODIS data. APS was developed at the Naval Research Laboratory, Stennis Space Center (NRL/SSC). We have found that, although there are large differences between the measured radiances (Lt) of the two sensors when the sensor zenith angle differences are significant, the mean percent differences between the retrieved normalized water-leaving radiances are about 15%. The results show that the variation in satellite view zenith angles is not a main factor affecting the retrieval of ocean color data products, i.e., the atmospheric correction routine adequately removes the view-angle dependence. [ABSTRACT FROM AUTHOR]