Work

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

Year: 2024

Type: article

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.

Source: Remote Sensing

DOI: 10.3390/rs16183515

Authors: Zhigang Yu, Guanghui Zhang, Guoman Huang, Chunquan Cheng, Zhuopu Zhang, Chenxi Zhang

Institutions: Shandong University of Science and Technology, Chinese Academy of Surveying and Mapping

Language: English

Topic: Synthetic Aperture Radar (SAR) Applications and Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,069