Casal, Gema, Harris, Paul, Monteys, Xavier, Hedley, John, Cahalane, Conor and McCarthy, Tim (2020) Understanding satellite-derived bathymetry using Sentinel 2 imagery and spatial prediction models. GIScience & Remote Sensing, 57 (3). pp. 271-286. ISSN 1548-1603
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Abstract
ABSTRACT
Optical satellite data is an efficient and complementary method to hydrographic surveys for
deriving bathymetry in shallow coastal waters. Empirical approaches (in particular, the models
of Stumpf and Lyzenga) provide a practical methodology to derive bathymetric information
from remote sensing. Recent studies, however, have focused on enhancing the performance
of such empirical approaches by extending them via spatial information. In this study, the
relationship between multibeam depth and Sentinel-2 image bands was analyzed in an
optically complex environment using the spatial predictor of kriging with an external drift
(KED), where its external drift component was estimated: a) by a ratio of log-transformed
bands based on Stumpf’s model (KED_S) and b) by a log-linear transform based on Lyzenga’s
model (KED_L). Through the calibration of KED models, the study objectives were: 1) to better
understand the empirical relationship between Sentinel-2 multispectral satellite reflectance
and depth, 2) to test the robustness of KED to derive bathymetry in a multitemporal series of
Sentinel-2 images and multibeam data, and 3) to compare the performance of KED against
the existing non-spatial models described by Stumpf et al. and Lyzenga. Results showed that
KED could improve prediction accuracy with a decrease in RMSE of 89% and 88%, and an
increase in R2 of 27% and 14%, over the Stumpf and Lyzenga models, respectively. The
decrease in RMSE provides a worthwhile improvement in accuracy, where results showed
effective prediction of depth up to 6 m. However, the presence of higher concentrations of
suspended materials, especially river plumes, can reduce this threshold to 4 m. As would be
expected, prediction accuracy could be improved through the removal of outliers, which were
mainly located in the channel of the river, areas influenced by the river plume, abrupt
topography, but also very shallow areas close to the shoreline. These areas have been
identified as conflictive zones where satellite-derived bathymetry can be compromised.
Item Type: | Article |
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Keywords: | Bathymetry; multispectral; geostatistical modelling; kriging; |
Academic Unit: | Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS Faculty of Social Sciences > Research Institutes > Maynooth University Social Sciences Institute, MUSSI |
Item ID: | 15555 |
Identification Number: | 10.1080/15481603.2019.1685198 |
Depositing User: | Tim McCarthy |
Date Deposited: | 22 Feb 2022 16:52 |
Journal or Publication Title: | GIScience & Remote Sensing |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/15555 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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