Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1-Reference-Cited by-同舟云学术

Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1

Published:2025-01-06 Issue:1 Volume:18 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Zhang Leixin¹²^ORCID,Zhao Feng¹²,Wang Yunjia¹²,Mallorqui Jordi J.³,Wang Teng¹²,Zhang Yuxuan¹²,Hu Zhongbo⁴,Du Sen⁴,Fernández José⁴

Affiliation:

1. Key Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of China

2. School of Environment Science and Spatial Informatics, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of China

3. CommSensLab, Universitat Politècnica de Catalunya Barcelona, Spain

4. Instituto de Geociencias (IGEO), CSIC-UCM, 7 Madrid, Spain

Funder

National Key R&D Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Young Elite Scientists Sponsorship Program by CAST

XinJiang key research and development program

China Scholarship Council

Spanish Ministry of Science and Innovation

European Funds for Regional Development

G2HOTSPOTS

Construction Program of Space-Air-Ground-Well Cooperative Awareness Spatial Information Project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2447335

Reference37 articles.

1. Ground infrastructure monitoring in coastal areas using time-series inSAR technology: the case study of Pudong International Airport, Shanghai

2. Efficient Phase Estimation for Interferogram Stacks

3. Evaluation of polarimetric capabilities of dual polarized Sentinel-1 and TerraSAR-X data to improve the PSInSAR algorithm using amplitude dispersion index optimization

4. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms

5. Ground subsidence risk assessment method using PS-InSAR and LightGBM: a case study of Shanghai metro network

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1. Landslide Identification in the Yuanjiang Basin of Northwestern Hunan, China, Using Multi-Temporal Polarimetric InSAR with Comparison to Single-Polarization Results;Remote Sensing;2025-04-25

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