.png){kind=icon}
返回
Monitoring land subsidence through improved CAESAR algorithm in time-series InSAR processing
.png){kind=icon}
OA
AI
DOI：10.1080/10106049.2024.2364689.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
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.
Keyword:
Eigenvalue decomposition
principal component analysis
distributed scatterer
permanent scatterer
期刊
IF:
3.5
论文数:
2.4K
被引数:
6.9K
机构
暂无机构信息
引用论文
British Discourses on Europe: Sovereignty of Parliament, Instrumentality and the Non-Mythical Europe
PREAI
分享收藏Monitoring reclaimed lands subsidence in Hong Kong with InSAR technique by persistent and distributed scatterers.png)
NATURAL HAZARDS
NATURAL HAZARDSIF3.7
PREAI
分享收藏A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms基于小基线差分SAR干涉图的地表变形监测新算法
PREAI
分享收藏
查看更多内容