Land subsidence monitoring using InSAR technique in the southwestern region of Bangladesh

Sarker, Md. Shahoriar; Kamal, A. S. M. Maksud; Rahman, Md. Zillur; Faruki Fahim, Abul Kashem

doi:10.1080/19475705.2024.2333795

Cited by 1 publication

(1 citation statement)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using the GMM algorithm, the distribution of pixel points in the coherence coefficient image was represented to delineate homogeneous coherence areas [27,28]. The EM algorithm was then applied to obtain the normal distribution parameters of each coherent class, facilitating the removal of interfering low-coherence pixel points, while maximizing the retention of PS points in high-coherence areas [29]. Combining these two sets of PS candidate point sets enhanced SAR image interpretation, improving the quantity and quality of recognized PS points on the under-construction cross-sea bridge.…”

Section: Ps Point Selection Based On Statistical Theory and Gmm-em Al...mentioning

confidence: 99%

A Persistent Scatterer Point Selection Method for Deformation Monitoring of Under-Construction Cross-Sea Bridges Using Statistical Theory and GMM-EM Algorithm

Li,

Xu,

Zhang

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

Using traditional algorithms to identify persistent scatterer (PS) points is challenging during bridge construction because of short-term changes at construction sites, such as earthworks, as well as the erection and dismantling of temporary structures. To address this issue, this study proposes a PS point selection method based on statistical theory and Gaussian Mixture Model-Expectation Maximization (GMM-EM) algorithm. This method adopts amplitude information as an incoherence evaluation indicator. Furthermore, the statistical median of the amplitude dispersion index and amplitude mean is screened twice to extract a set of candidate points, including PS points that exhibit stable backscattering over long durations. Temporal coherence is simultaneously used as the coherence evaluation indicator. Another candidate point set is obtained by extracting high-coherence PS points using the GMM-EM algorithm. These sets of candidate points are then combined to obtain a final PS points set. In the experiment, the deformation monitoring of the under-construction Shenzhen-Zhongshan Cross-Sea Bridge in China was selected as a case study, with 28 Sentinel-1A images used as the data source for PS selection and deformation information extraction. The results show that the proposed method enhanced the density and quality of PS points on the under-construction cross-sea bridge compared to existing PS selection methods, thus offering higher reliability. Deformation analysis further revealed fluctuating deformation trends at characteristic points of the Shenzhen-Zhongshan Cross-Sea Bridge, indicating the occurrence of elastic deformation during its construction.

show abstract

Section: Ps Point Selection Based On Statistical Theory and Gmm-em Al...mentioning

confidence: 99%

A Persistent Scatterer Point Selection Method for Deformation Monitoring of Under-Construction Cross-Sea Bridges Using Statistical Theory and GMM-EM Algorithm

Li,

Xu,

Zhang

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

show abstract

Land subsidence monitoring using InSAR technique in the southwestern region of Bangladesh

Cited by 1 publication

References 54 publications

A Persistent Scatterer Point Selection Method for Deformation Monitoring of Under-Construction Cross-Sea Bridges Using Statistical Theory and GMM-EM Algorithm

A Persistent Scatterer Point Selection Method for Deformation Monitoring of Under-Construction Cross-Sea Bridges Using Statistical Theory and GMM-EM Algorithm

Contact Info

Product

Resources

About