POSTER Session 3

PACE/OCI FOR OPTICALLY SHALLOW WATER APPLICATIONS

Satellite-based derivation of water quality data for optically shallow targets is particularly challenging due to the difficulties in separating the benthic and water column contributions to the reflectance signal. The recent launch of PACE, including the hyperspectral Ocean Color Instrument (OCI), provides an unprecedented opportunity to assess these environments on a near-daily basis. Here, we present initial results showing application of a spectral matching optimization algorithm tailored to OCI characteristics for derivation of water column inherent optical properties (IOPs), depth, and benthic albedo. Overall, we found broad agreement between OCI-derived parameters and both existing bathymetries and benthic habitat maps. Derived IOPs were temporally stable and matched expected spatial patterns, while limited validation data indicate potentially promising accuracy. Commensurate with the global reach of PACE, this approach was designed for application in any optically shallow waters, including targets for which no reliable benthic, bathymetric, or IOP data exist. For such targets, an initial processing step provides parameter estimates (e.g., depth) as needed for processing a single pixel, while repeat OCI sampling allows for generation of robust bathymetry and benthic albedo maps. These results show substantial promise for OCI-enabled monitoring of optically shallow environments, and further enable improved assessment of these important coastal with heritage sensors.

Brian Barnes, University of South Florida, USA, [email protected], https://orcid.org/0000-0003-0056-3500

Yuyuan Xie, University of South Florida, USA, [email protected]

Chaunmin Hu, University of South Florida, USA, [email protected]

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