ABSTRACT
Benthic mapping employs field surveys, hydroacoustic measurements, aerial photography, and satellite imagery. Effective benthic mapping involves removing overlying water effects from atmospherically corrected remotely sensed data to enhance signals from the seafloor. Our previous water correction algorithms depend on controlled laboratory measurements of substrates in clear water, which had challenges for replication. A more simplified water correction algorithm is presented, which uses bathymetry and only a few pixels from the image. Spectral profiles were extracted from four pixels in a Hyperspectral Imager for Coastal Oceans (HICO) image that was acquired in February 2014 over Indian River Lagoon, Florida. The four locations were chosen based on the assumption there were two types of homogeneous substrates at two depths. Our new algorithm calculates water column reflectance and water absorption at the instance of image data acquisition directly from the four pixel values. Water correction demonstrates improved benthic feature depiction including the near-infrared signals for benthic vegetation. A simple ratio was applied to the corrected image and demonstrates restored submerged vegetation signals.
Acknowledgements
We thank Lori Morris and others at the St. Johns River Water Management District for providing water quality data and seagrass survey products. We also thank Curtiss Davis and Jasmine Nahorniak at Oregon State University for providing an atmospherically corrected HICO image. The authors express thanks to Rachael Isphording and Sachidananda Mishra for their participation in and contribution to the preliminary work of the research.
Disclosure statement
No potential conflict of interest was reported by the authors.