Assessment of PRISMA level-2 hyperspectral imagery for large scale satellite-derived bathymetry retrieval

Alevizos, Evangelos; Le Bas, Tim ORCID: https://orcid.org/0000-0002-2545-782X; Alexakis, Dimitrios D.. 2022 Assessment of PRISMA level-2 hyperspectral imagery for large scale satellite-derived bathymetry retrieval. Marine Geodesy. 1-23. https://doi.org/10.1080/01490419.2022.2032497

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Official URL: http://dx.doi.org/10.1080/01490419.2022.2032497

Abstract/Summary

Currently, several satellite-derived bathymetry (SDB) workflows are based on a variety of satellite imagery which are analyzed by empirical or analytical methods. The latest availability of PRISMA hyperspectral data provides a new opportunity for testing their application in shallow water bathymetry mapping. Here we utilize two Level-2 PRISMA scenes from the Caribbean Sea capturing seafloor areas with diverse benthic features and we analyze them using the shallow water analytical models provided by the water-color simulator (WASI) software. The presented study examines the influence of spatial resolution and end-member spectra on the SDB output. Consequently, in one study area we apply inversion using additional reference spectra and in the other study area we exploit the PRISMA panchromatic band for producing a pan-sharpened, hyperspectral cube for bathymetry inversion. The results show good correlation with reference bathymetry data (sonar and admiralty chart) suggesting that PRISMA imagery has a clear potential in optical bathymetry studies. The use of appropriate end-member spectra assists in enhancing the accuracy of SDB, and pan-sharpened PRISMA imagery assists in improving the results when detailed bathymetry is required. PRISMA imagery can be effectively analyzed with open-source software WASI-2D and thus contribute new bathymetric data to regional-scale seafloor mapping projects.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1080/01490419.2022.2032497
ISSN:	0149-0419
Date made live:	07 Apr 2022 16:28 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/532444

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1080/01490419.2022.2032497

ISSN:

0149-0419

Date made live:

07 Apr 2022 16:28 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/532444