Mapping coastal optical and biogeochemical variability using an autonomous underwater vehicle and a new bio-optical inversion algorithm
MetadataShow full item record
Autonomous underwater vehicles (AUVs) can map water conditions at high spatial ( horizontal and vertical) and temporal resolution, including under cloudy conditions when satellite and airborne remote sensing are not feasible. Applications of this technology are numerous, and harnessing the full potential of AUV platforms for oceanographic research will require innovative sampling and data processing techniques, particularly in shallow littoral environments. We deployed a passive radiometer on a small AUV called the Remote Environmental Monitoring UnitS (REMUS; Hydroid) to demonstrate a novel method that uses one optical sensor at depth to characterize variability in underwater clarity and the constituents of coastal seawater (i.e., dissolved organic material, algal biomass, and other particles). This approach uses spectral differences between attenuation coefficients that are computed from ratios of downwelling irradiance measured at one depth assuming a constant shape, but not magnitude, for the solar irradiance spectrum at the surface. A spectral inversion model provides estimates of the absorption coefficients ( m(-1)) of the constituents above the sensor. There is no requirement for sensors at the ocean surface using this approach and, compared to inversion methods for subsurface reflectance, the effects of bottom reflectance in shallow waters are minimal. Maps of biooptical properties at high spatial resolution demonstrate that our approach can be used for characterizing shallow and highly variable coastal waters. This simple and robust technique is also applicable to other in situ sampling platforms ( e. g., gliders, moorings, Argo floats).
Brown, CA, Y. Huot, MJ Purcell, JJ Cullen, et al. 2004. "Mapping coastal optical and biogeochemical variability using an autonomous underwater vehicle and a new bio-optical inversion algorithm." Limnology and Oceanography-Methods 2: 262-281. DOI:10.4319/lom.2004.2.262