A novel lightweight 3D CNN for accurate deformation time series retrieval in MT-InSAR

Authors

Xiaoli Ding (ORCID: https://orcid.org/0000-0002-5733-3629)
Mahmoud Abdallah (ORCID: https://orcid.org/0000-0001-9541-5521)
Songbo Wu (ORCID: https://orcid.org/0000-0003-2118-0963)
S. H. Younis

Publication Details

Journal: Science of Remote Sensing
Published: 2025-02-10
DOI: https://doi.org/10.1016/j.srs.2025.100206
Citations: 4
Primary Topic: Synthetic Aperture Radar (SAR) Applications and Techniques
Type: article
Field-Weighted Citation Impact: 19.97

Funders

National Natural Science Foundation of China
University Grants Committee

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article

A novel lightweight 3D CNN for accurate deformation time series retrieval in MT-InSAR

Xiaoli Ding, Mahmoud Abdallah, Songbo Wu, S. H. Younis

Feb 10, 2025

4 citations

Science of Remote Sensing

Synthetic Aperture Radar (SAR) Applications and Techniques

19.97

article

A novel lightweight 3D CNN for accurate deformation time series retrieval in MT-InSAR

Xiaoli Ding, Mahmoud Abdallah, Songbo Wu, S. H. Younis

February 10, 2025article en

4 citations

Abstract

No abstract available for this paper.

Science of Remote SensingVol. 11

National Natural Science Foundation of China, University Grants Committee

Climate action

Openalex Percentile: Top 1%

Synthetic Aperture Radar (SAR) Applications and Techniques

19.97

DOI Open Access PDF OpenAlex

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A novel lightweight 3D CNN for accurate deformation time series retrieval in MT-InSAR — Xiaoli Ding, Mahmoud Abdallah, et al. · Science of Remote Sensing (2025) | TGRS Research Map | TGRS