An application of 1D convolution and deep learning to remote sensing modelling of Secchi depth in the northern Adriatic Sea

An application of 1D convolution and deep learning to remote sensing modelling of Secchi depth in the northern Adriatic Sea

ABSTRACTThis paper presents a novel approach for predicting the water quality indicator – Secchi disk depth (ZSD). ZSD indirectly reflects water clarity and serves as a proxy for other quality parameters. This study utilizes Deep Neural Network (DNN) trained on satellite remote sensing and measured...

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Bibliographic Details
Main Authors: Antonia Ivanda, Ljiljana Šerić, Dušan Žagar, Krištof Oštir
Format: Article
Language:English
Published: Taylor & Francis Group 2024-01-01
Series:Big Earth Data
Subjects:
Secchi
Sentinel-3
OLCI
1D-CNN
Adriatic sea
Online Access:https://www.tandfonline.com/doi/10.1080/20964471.2023.2273058

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