Refraction Correction for Spectrally Derived Bathymetry Using UAS Imagery

Abstract

Spectrally derived bathymetry (SDB) algorithms are rapidly gaining in acceptance and widespread use for nearshore bathymetric mapping. In the past, refraction correction could generally be ignored in SDB, due to the relatively small fields of view (FOVs) of satellite sensors, and the fact that such corrections were typically small in relation to the uncertainties in the output bathymetry. However, the validity of ignoring refraction correction in SDB is now called into question, due to the ever-improving accuracies of SDB, the desire to use the data in nautical charting workflows, and the application of SDB algorithms to airborne cameras with wide FOVs. This study tests the hypothesis that refraction correction leads to a statistically significant improvement in the accuracy of SDB using uncrewed aircraft system (UAS) imagery. A straightforward procedure for SDB refraction correction, implemented as a modification to the well-known Stumpf algorithm, is presented and applied to imagery collected from a commercially available UAS in two study sites in the Florida Keys, U.S.A. The results show that the refraction correction produces a statistically significant improvement in accuracy, with a reduction in bias of 46–75%, a reduction in RMSE of 3–11 cm, and error distributions closer to Gaussian.