STGCN-based inversion of landslide creep parameters using GNSS displacement time series

Key Points

• Inversion of landslide creep parameters shows improved accuracy using STGCN techniques, demonstrating effectiveness with GNSS data.
• Key evidence indicates that utilizing GNSS displacement time series leads to a significant advancement in modeling landslide behavior.
• Analysis employs a spatiotemporal graph convolutional network (STGCN) to process GNSS data for parameter estimation.
• Findings highlight the potential of advanced modeling approaches in enhancing landslide prediction and monitoring.