Assessment of hydrological loading displacement from GNSS and GRACE data using deep learning algorithms

Assessment of hydrological loading displacement from GNSS and GRACE data using deep learning algorithms

Abstract This work introduces a novel method for estimating hydrological loading displacement using 3D Convolutional Neural Networks (3D-CNN). This approach utilizes vertical displacement time series data from 41 Global Navigation Satellite System (GNSS) stations across Yunnan Province, China, and i...

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Bibliographic Details
Main Authors: Changshou Wei, Maosheng Zhou, Zhixing Du, Lijing Han, Hao Gao
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
3D-CNN
Terrestrial water loading displacement
GRACE
GNSS
Load Green’s function
Online Access:https://doi.org/10.1038/s41598-025-90363-y
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https://doi.org/10.1038/s41598-025-90363-y

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