POSTER Session 3

SENSOR-GENERIC ADJACENCY-EFFECT CORRECTION FOR NEARSHORE AQUATIC REMOTE SENSING

The adjacency effect distorts the top-of-atmosphere (TOA) signals of water in nearshore environments, compromising the retrieval of satellite-derived aquatic products. We refined the adjacency-effect-correction approach of Vermote et al. [J. Geophys. Res., 102(D14), 1997] with three modifications: 1) we removed the assumption of infinitesimally small pixels, 2) accounted for variations in surface-level irradiance caused by surface heterogeneity, and 3) applied the correction at the TOA level, facilitating subsequent use of atmospheric correction (AC) tools tailored for specific environments. The atmospheric point-spread function is computed for the given solar-sensor geometry with ancillary atmospheric and aerosol data, and is then used to convolve the input imagery. For each spectral band, the difference between the observed and convolved reflectances is used to correct for the adjacency effect, i.e., pixels are corrected to the TOA reflectance they would exhibit if each pixel were surrounded by pixels of identical reflectance. Validation was conducted by deriving water-leaving reflectance using three state-of-the-art AC processors, ACOLITE, POLYMER, and L2gen, with and without adjacency correction, and comparing them to in situ measurements collected within 200 m of coastlines from the GLORIA dataset (n = 212). On average, the correction led to a 16.7% reduction in root mean square error, a 32.4% reduction in symmetric signed percentage bias, and a 36.8% improvement in median symmetric accuracy across the three processors. The algorithm is available in a publicly available Python package. We anticipate that it will lead to improved retrieval of satellite-derived aquatic products for nearshore environments.

*Yulun Wu, University of Ottawa, Canada, [email protected], https://orcid.org/0000-0003-0635-3715

Anders Knudby, University of Ottawa, Canada, [email protected]

Nima Pahlevan, Science Systems and Applications Inc. (SSAI) and NASA Goddard Space Flight Center, USA, [email protected]

David Lapen, Agriculture and Agri-Food Canada, [email protected]

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