Correction of hyperspectral reflectance measurements for surface objects and direct sun reflection on surface waters

Abstract

Satellite, airborne, or platform-based remote sensing reflectance measurements of aquatic targets are frequently compromised by water-surface effects such as specular sun reflection (glint) or transient objects like buoys or boats. For temporal or spatial data series where sub-surface reflectance is of interest, the elimination of affected data may require time-consuming manual selection of spectra and substantial data loss. Here, we present a method for the automated elimination of data points containing surface objects or strong sun reflection, which is based on the spectral slope in the ultra-violet to blue (350 nm to 450 nm). To minimize data loss, an automated sun glint correction combining two previously published methods is also presented. The method operates by subtracting a glint spectrum by means of a regression curve characterized from low to medium glint data points and is further automated by selecting these low glint data on the basis of the oxygen absorption depth in the near infrared (NIR). The elimination and correction algorithms facilitate rapid automated processing of large bio-optical data sets for both spatial and temporally resolved remote-sensing reflectance data sets. Here we demonstrate their efficacy on a three-month data set of hourly light field measurements from a fixed platform in the northwest Mediterranean.

Acknowledgements

The authors thank the staff of the Food and Agriculture Research and Technical Institute (IRTA), Alfred-Wegener Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Institute of Marine Resources (IMARE), and University of Applied Science Bremerhaven for their assistance in fieldwork, the company Explotaciones Marinas Alfaques for providing access to their aquaculture raft to deploy the sensor system, and the IRTA for support in system set-up and maintenance. The technical support of TriOS is also gratefully acknowledged. Part of the field work was financially supported by the Helmholtz POLMAR Graduate School. Support from the European Regional Development Fund (ERDF) funding the IMARE is gratefully acknowledged.