Work

Analysis of Slow-moving Landslide-Prone Areas in Gangwon State Using C-band and L-band InSAR

Year: 2026

Type: article

Abstract: This study constructed slope displacement data for the Gangwon State by applying persistent scatterer (PS) and distributed scatterer (DS) synthetic aperture radar interferometry (InSAR) time-series analysis to Sentinel-1 C-band and ALOS-2 PALSAR-2 L-band data, and evaluated the applicability of each sensor for slow-moving landslide detection in mountainous terrain dominated by dense forest cover. Following co-registration and topographic phase removal, sequential phase linking was applied to optimize interferometric phases, and line-of-sight (LOS) displacement velocity maps were generated through time-series analysis integrating both PS and DS pixels. The results revealed that Sentinel-1 observations were largely confined to exposed surfaces such as urban areas and road cuts, whereas ALOS-2 PALSAR-2 provided spatially continuous coverage extending into forested slopes. On slopes steeper than 10°, the valid pixel ratios for ALOS-2 PALSAR-2 reached 78.0%, 68.0%, and 57.0% for the 10-20°, 20-30°, and ≥30° slope ranges, respectively, compared to only 11.4%, 5.6%, and 4.7% for Sentinel-1. In the land-cover-based comparison, Sentinel-1 achieved moderate valid pixel ratios for cropland (49.3%) and grassland (37.0%) through phase optimization, but only 6.5% for forested areas, whereas ALOS-2 PALSAR-2 maintained 66.0% even in forests. In the aspect-wise comparison, ALOS-2 PALSAR-2 sustained observation densities exceeding 30% across all slope orientations, including both satellite-facing and satellite-away slopes. Furthermore, time-series analysis of two slow-moving landslide-prone sites identified from the ALOS-2 PALSAR-2 velocity map revealed mean LOS velocities of -28.2, +12.9, -39.7 mm/yr for three slope sectors, all exhibiting linear displacement trends over approximately 5 years. These results demonstrate that L-band InSAR displacement data can serve as a fundamental dataset for regional-scale early detection and long-term monitoring of slow-moving landslides in the mountainous terrain of Gangwon.

Source: GEO DATA

DOI: 10.22761/gd.2026.0011