Ground Subsidence Monitoring of Reclaimed Land Using Persistent Scatterer Interferometry Approach with ALOS-2 Stripmap-ScanSAR Observations
Abstract
Land subsidence is the gradual or sudden sinking of the grounds surface by natural processes or anthropogenic activities. Continuous monitoring is essential to prevent and cope with the damage from the subsidence. The spaceborne synthetic aperture radar (SAR) interferometry has been successfully applied to observe the subsidence in the range of several mm to cm by using phase information regardless of day and night and weather conditions thanks to characteristics of the microwave. Persistent scatterer interferometry (PSI) technique can obtain a time series analysis of surface displacement suppressing atmospheric artifacts and topography errors. Generally, at least a few tens of SAR data are required for more accurate time series analysis. The L-band used in ALOS-2 has a long wavelength which is more advantageous for maintaining coherence and stable phase centers rather than a shorter wavelength of C- or X-band. Our study area is a coastal reclaimed land at Busan city located in the south-eastern part of South Korea. However, the ALOS-2 PALSAR-2 archive images collected in the study area are somewhat insufficient for time series analysis with 11 Stripmap and 15 ScanSAR images. To overcome the small number of SAR images collected in each mode, we evaluated the PSI analysis using different beam mode acquisition of ALOS-2 PALSAR-2 Stripmap and ScanSAR. Although the interferometry between ALOS-2 PALSAR-2 Stripmap and ScanSAR has been successfully applied, in the case of PSI, it can be difficult to easily identify persistent scatterers due to different system parameters such as pulse repetition frequency (PRF), analog-to-digital converter (ADC) sample rate, bandwidth, and Doppler centroid frequency, etc. In this study, we evaluate the feasibility of the Stripmap-ScanSAR PSI application for monitoring the subsidence by comparing it with Global Navigation Satellite System (GNSS) data.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.G45B0410J