Spectral Information Adaptation and Synthesis Scheme for Merging Cross-Mission Ocean Color Reflectance Observations From MODIS and VIIRS


Getting a full clear read of coastal bays, estuaries, lakes, and inland waters is difficult with single satellite sensor observations due to cloud impacts. Cross-mission sensors give the synergistic opportunity to improve spatial and temporal coverage by merging their observations; but, discrepancies originating from the instrumental, algorithmic, and temporal variations should be eliminated before merging. This paper presents the Spectral Information Adaptation and Synthesis Scheme (SIASS) for generating cross-mission consistent ocean color reflectance by merging 2012–2015 observations from Moderate Resolution Imaging Spectroradiometer and visual Infrared Imaging Radiometer Suite over Lake Nicaragua in Central America, where the cloud impact is salient. The SIASS is ready to not only eliminate incompatibilities for matchup bands but additionally reconstruct spectral info for mismatched bands among sensors. Statistics indicate that the common monthly coverage of a merged ocean color reflectance product over Lake Nicaragua is sort of twice that of any single-sensor observation. Results show that SIASS significantly improves consistency among cross-mission sensors by mitigating distinguished discrepancies. In addition, reconstructed spectral data for those mismatched bands help preserve more spectral characteristics required to better monitor and understand the dynamic aquatic environment. The ultimate implementation of SIASS to map the chlorophyll- concentration demonstrates the efficacy of SIASS in bias correction and consistency improvement. In general, SIASS can be applied to get rid of cross-mission discrepancies among sensors to enhance the consistency.

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