Early detection of slow-moving landslides in the Himalayas and Western Ghats using PSInSAR

Landslides are major natural hazards in mountainous regions, such as the Himalayas and Western Ghats. Rainfall-induced slope failures in these regions exhibit a seasonal recurring nature and pose a serious threat to life and property. Understanding landslide occurrences and their relationship with ground and climatic parameters is therefore important for mitigating their impact. This study investigates slope deformations with persistent scatterer interferometric synthetic aperture radar (PSInSAR) time series analysis using Sentinel-1 images. This study employs a detailed site monitoring strategy for slow-moving slopes or reactivation sites susceptible to slow movement. This study proposes a statistical framework to quantify movement transitions in persistent scatterer (PS) groups. However, limited studies have systematically quantified movement transitions within PS groups to understand pre-failure deformation behaviour in slow-moving landslides. This study addresses this gap by developing a statistical framework to detect early deformation signatures, advancing current PSInSAR applications for landslide early warning. A comparative study of spatiotemporal deformations revealed characteristic movement patterns. Monitoring the PS of the slow-moving zones exhibits desynchronized deformation within slide zones marked by transitions in contrast to the neighbourhood. The study also identified transition periods that precede landslides and correlate with rainfall, highlighting the potential for early detection.