Satellite-Derived Bathymetry Using Sentinel-2 and Airborne Hyperspectral Data: A Deep Learning Approach with Adaptive Interpolation

Satellite-Derived Bathymetry Using Sentinel-2 and Airborne Hyperspectral Data: A Deep Learning Approach with Adaptive Interpolation

Accurate coastal bathymetry is critical for navigation, environmental monitoring, and marine resource management. This study presents a deep learning-based approach that fuses Sentinel-2 multispectral imagery with airborne hyperspectral-derived reference data to generate high-resolution satellite-de...

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Bibliographic Details
Main Authors: Seung-Jun Lee, Han-Saem Kim, Hong-Sik Yun, Sang-Hoon Lee
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Remote Sensing
Subjects:
satellite-derived bathymetry
Sentinel-2
hyperspectral data fusion
interpolation methods
deep learning
fully convolutional neural network
Online Access:https://www.mdpi.com/2072-4292/17/15/2594
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