FIM-based DSInSAR method for mapping and monitoring of reservoir bank landslides: an application along the Lancang River in China

Hu, Jiyuan; Wu, Wenhao; Motagh, Mahdi; Qin, Fen; Wang, Jiayao; Pan, Shun; Guo, Jiming; Zhang, Chunyu

doi:10.1007/s10346-023-02097-5

Cited by 4 publications

(1 citation statement)

References 31 publications

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“…In the past few decades, the number of satellites used for scientific research has increased and the accuracy of surface monitoring with space-borne-based technology has gradually improved [10,11]. The usage of satellite-derived techniques is also helpful in landslide-studying, starting from landslide mapping [12], landslide susceptibility [13][14][15], and landslide monitoring based on the Synthetic Aperture Radar (SAR) and Interferogram SAR (InSAR) techniques [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Parametric Test of the Sentinel 1A Persistent Scatterer- and Small Baseline Subset-Interferogram Synthetic Aperture Radar Processing Using the Stanford Method for Persistent Scatterers for Practical Landslide Monitoring

Bahti,

Chung,

Lin

2023

Remote Sensing

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The landslide monitoring method that uses the Sentinel 1A Interferogram Synthetic Aperture Radar (InSAR) through the Stanford Method for Persistent Scatterers (StaMPS) method is a complimentary but complex procedure without exact guidelines. Hence, this paper delivered a parametric test by examining the optimal settings of the Sentinel 1A Persistent Scatterer (PS)- and Small Baseline Subset (SBAS)-InSAR using the StaMPS compared to the Global Navigation Satellite Systems (GNSS) in landslide cases. This study first revealed parameters with the suggested values, such as amplitude dispersion used to describe amplitude stability, ranging from 0.47 to 0.48 for PS and equal to or more than 0.6 for SBAS in WuWanZai, Ali Mt. The study further examined the suggested values for other factors, including the following: unwrap grid size to re-estimate the size of the grid; unwrap gold n win as the Goldstein filtering window to reduce the noise; and unwrap time win as the smoothing window (in days) for estimating phase noise distributions between neighboring pixels. Furthermore, the study substantiated the recommended settings in the Woda and Shadong landslide cases with the GNSS, inferring that the SBAS has adequate feasibility in practical landslide monitoring.

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