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Monitoring land subsidence through improved CAESAR algorithm in time-series InSAR processing

delete2024-06-24
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OA
AI
Q
Qian He *
H
Huan He
K
Kangming Song
J
Jiawei Chen
DOI：10.1080/10106049.2024.2364689delete
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Abstract

Abstract

En 中文
Time-series SAR interferometry (InSAR) combining permanent scatterer and distributed scatterer (DS), has been strongly developed in subsidence monitoring. It is known that the Component extrAction and sElection SAR (CAESAR) is a recently presented approach of selecting and filtering scattering mechanisms for DS. This article proposes an improved CAESAR algorithm in InSAR processing. Phase optimization is performed by eigenvalue decomposition and principal component analysis of the coherence matrix that constructed based on the identified homogeneous pixels. In addition, only the interferometric phases with low noise are used to calculate the goodness-of-fit value. The improved method has been tested for subsidence monitoring over a nonurban area located in Xiongxian, China using 25 Sentinel-1A images. The results show that the improved method can provide the high spatial density of deformation measurements with accuracy ensured. Noticeable land subsidence is revealed widely within the north of Xiongxian county, particularly in Daying, Mijiawun and Beishakou towns.
Keywords:
Eigenvalue decomposition
principal component analysis
distributed scatterer
permanent scatterer

Journal

Geocarto International cover
Geocarto International
IF:
3.5
Papers:
2.4K
Citations:
6.9K

Organization

No organization information available