GSLC Dataset for Observing Surface Displacement Caused by the 2018 Hualien Earthquake

Abstract

Differential Interferometric Synthetic Aperture Radar (DInSAR) is a space geodetic technique for measuring surface displacement from the phase difference between two SAR acquisitions. However, conventional DInSAR processing requires a series of complex preprocessing steps, such as co-registration, flat-earth phase removal, topographic phase correction, and geocoding. These processing procedures can limit the accessibility and usability of SAR data for non-specialist users. To address this limitation, Geocoded Single Look Complex (GSLC), which is a type of Analysis Ready Data, has recently attracted increasing attention. GSLC products are provided in a common geocoded coordinate system, with flat-earth and topographic phase components corrected in advance. Consequently, a differential interferogram can be generated directly by multiplying one GSLC image by the complex conjugate of another. In this study, we evaluated the applicability of Sentinel-1 GSLC products for detecting coseismic displacement associated with the February 2018 Hualien earthquake. Two GSLC images were generated from Sentinel-1 acquisitions, with the flat-earth and topographic phase components removed during GSLC processing. A differential interferogram derived from the GSLC products was then compared with one generated using a conventional SLC-based DInSAR workflow. The two interferograms exhibited highly consistent spatial phase patterns, indicating that the GSLC-based approach can retrieve surface displacement signals comparable to those obtained through a conventional SLC-based approach. These results demonstrate that GSLC products can substantially simplify the DInSAR workflow while preserving the quality of the interferometric measurements. Furthermore, these results suggest the potential for providing long-term GSLC datasets and extending the approach to displacement time series analysis.