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SSBAS-InSAR: A Spatially Constrained Small Baseline Subset InSAR Technique for Refined Time-Series Deformation Monitoring

Authors :
Zhigang Yu
Guanghui Zhang
Guoman Huang
Chunquan Cheng
Zhuopu Zhang
Chenxi Zhang
Source :
Remote Sensing, Vol 16, Iss 18, p 3515 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

SBAS-InSAR technology is effective in obtaining surface deformation information and is widely used in monitoring landslides and mining subsidence. However, SBAS-InSAR technology is susceptible to various errors, including atmospheric, orbital, and phase unwrapping errors. These multiple errors pose significant challenges to precise deformation monitoring over large areas. This paper examines the spatial characteristics of these errors and introduces a spatially constrained SBAS-InSAR method, termed SSBAS-InSAR, which enhances the accuracy of wide-area surface deformation monitoring. The method employs multiple stable ground points to create a control network that limits the propagation of multiple types of errors in the interferometric unwrapped data, thereby reducing the impact of long-wavelength signals on local deformation measurements. The proposed method was applied to Sentinel-1 data from parts of Jining, China. The results indicate that, compared to the traditional SBAS-InSAR method, the SSBAS-InSAR method significantly reduced phase closure errors, deformation rate standard deviations, and phase residues, improved temporal coherence, and provided a clearer representation of deformation in time-series curves. This is crucial for studying surface deformation trends and patterns and for preventing related disasters.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
18
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.77f64dbf0ec448db0c78f5cc7e8b6f9
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16183515