Land subsidence monitoring based on PS-InSAR Persistent Scatterers identification with spectral analysis method

• Published in: Proceedings of the International Association of Hydrological Sciences Vol. 382; pp. 249 - 253
• Main Authors: Zhou, Di, Yu, Jie, Zhu, Lin, Wang, Yanbing, Zhang, Jing, Jiao, Shuai, Chen, Ren Shu
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Gottingen Copernicus GmbH 22.04.2020; Copernicus Publications
• Subjects: Accuracy; Coherent scattering; Construction; Fast Fourier transformations; Fourier analysis; Fourier transforms; Frequency domain analysis; Identification; Image acquisition; Interferometric synthetic aperture radar; Land subsidence; Monitoring; Noise; Photosystem I; Radar data; SAR (radar); Satellites; Simulation; Spectral analysis; Spectrum analysis; Stability; Subsidence; Synthetic aperture radar; Synthetic aperture radar interferometry; Urban areas; Beijing China; China
• ISSN: 2199-899X; 2199-8981; 2199-899X
• DOI: 10.5194/piahs-382-249-2020

Layover occurs as a consequence of the slant range scale distortion in Synthetic Aperture Radar (SAR) data and it is commonly observed in the images acquired over urban areas. There may be two or more Persistent Scatterers (PSs) in one pixel. Moreover, these PSs do not have amplitude stability and spatial coherence. The threshold method used in the Persistent Scatterer Interferometric (PSI) SAR technique cannot identify the PS with two scatterers in urban, the accuracy of urban land subsidence is reduced. To solve this problem, we used Fast Fourier Transform (FFT) convert PSs in frequency domain during PS identification process of PSI, by observing their characteristics in the frequency domain, the layover scatterers can be identified and separated. The results of simulation experiment show that by analyzing the peak distribution characteristics of PSs in the elevation direction under the relatively even space baseline, PSI with FFT can identify single scatterers and layover scatterers. After separating the layover scatterers, the reliability of PSs identification are improved. For the real data experiment, we use 31 Sentinel-1A IW images covering Beijing from 2014 to 2016 as data sources. The results show that the proposed method can effectively identify layover scatterers which cannot be identified by the threshold method in urban, reducing the effect of layover scatterers, improving the accuracy of urban land subsidence monitoring.