Sentinel-2 Bathymetry Indicates River-Mouth Migration and Asymmetric Sediment Redistribution at Cua Dai, Vietnam
Copyright © 2026 Duong Cong Dien, Dang Song Ha, Truong Manh Chien, Nguyen Vu Thang, Nguyen Thieu Hoa. Published by Nan Yang Academy of Sciences Pte. Ltd.
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
Abstract
Satellite-derived bathymetry (SDB) can support monitoring of dynamic river mouths, but its interpretation depends on survey–image timing, validation design and spatially explicit uncertainty. This study applies an established Sentinel-2 blue–green log-ratio workflow to Cua Dai, Vietnam, using four archived image–echo-sounding comparison data sets from 2016–2018. Recalculation from all valid paired records (n = 1,974–3,483 per date) yielded bias from −0.184 to +0.259 m, MAE (mean absolute error) of 0.394–0.651 m, RMSE (root mean square error) of 0.495–0.849 m and predictive R2 of 0.751–0.924. The same-day Sept 2018 comparison performed best; the other image–survey pairs were separated by 36–61 days. Inter-date maps indicate alternating deepening and shoaling, river-mouth/bar reorganisation and an asymmetric pattern of northern vulnerability and southern deposition. Provisional LoD95 values are 2.19 m for Apr 2016–May 2017 and 1.73 m for May 2017–Sep 2018, so smaller differences are treated as unresolved. The latter interval spans the Nov 2017 flood and about ten subsequent months and therefore cannot isolate flood effects. A wave-shadow/sediment-connectivity explanation is presented as a testable hypothesis rather than a demonstrated mechanism. The revised analysis shows how SDB can guide targeted field monitoring while preventing unsupported volume estimates and causal attribution.
Keywords: Multispectral Remote Sensing, Shallow-Water Mapping, Limit of Detection, Validation Uncertainty, Estuarine Morphodynamics, Coastal Monitoring
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