POSTER SESSION 3
15:30–17:30, Wednesday, September 16
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
ABSTRACT 1404 | POSTER 39
PROCESS HYPERSPECTRAL PACE OCI SPECTRA OF OPTICALLY DEEP AND SHALLOW WATERS WITH ONE ALGORITHM
While simultaneous retrieval of inherent optical properties (IOPs) and bathymetry using physics-based semi-analytical models is theoretically well-established, a significant operational gap remains: current operational algorithms, including those implemented by NASA, have yet to achieve a unified approach capable of seamlessly and simultaneously processing both optically shallow and deep waters. The advent and application of next-generation hyperspectral satellite data provide a breakthrough opportunity to overcome this technical bottleneck. This study aims to fill this gap by applying the Hyperspectral Optimization Processing Exemplar (HOPE) model to hyperspectral imagery from NASA’s Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE), thereby achieving a unified retrieval of optical parameters across shallow- and deep-water regimes. Specifically, we systematically evaluate the retrieval performance of the HOPE model under various configurations of unknown parameters across highly variable optical depths. Validation results from the Great Bahama Bank (GBB), based on three closely acquired PACE scenes, demonstrate that bathymetry derived from the PACE-driven HOPE approach shows strong agreement with NASA’s Coastal and Nearshore Along-Track Bathymetry Product (ATL24), achieving an average coefficient of determination (R²) of 0.91 and a root mean square error (RMSE) of 2.2 m over a depth range of 0 to 30 m. Furthermore, comparison of IOP retrievals against the Quasi-Analytical Algorithm (QAA) and the Generalized Inherent Optical Properties algorithm (GIOP) reveals that the optimized model more accurately characterizes actual physical conditions, successfully achieving the highly sought-after smooth spatial transition between optically shallow and optically deep waters.
Tiantian Cao*, Xiamen University, [email protected]
Zhongping Lee, Xiamen University, [email protected]
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
