Refined InSAR tropospheric delay correction for wide-area landslide identification and monitoring

SAR Interferometry (InSAR) proves to be effective for investigating landslides. However, its measurement accuracy is largely limited by the complex atmospheric delay distortion in alpine valley regions, resulting poor performance of landslides detection and monitoring. Particularly, spatial heterogeneity over wide areas cannot accurately reflected conventional empirical phase-elevation models or external data-based methods. In this study, we proposed a multi-temporal moving-window linear model (MMLM) correct tropospheric wide-area investigation. This regression based on elevation-phase relationship modeling phases within sliding local window. It mitigates influence turbulent phase, landslide deformation, phase unwrapping error parameter estimation, providing precise heterogeneous corrections InSAR identification A simulation experiment was conducted analyze sensitivity parameters settings evaluate effectiveness MMLM model. Furthermore, demonstrated through comparison with ERA5, GACOS, spatial-temporal filtering, traditional using descending ascending Sentinel-1 data reservoir area Lianghekou hydropower station. Among above-mentioned methods, standard deviation original unwrapped achieved largest decrease more than 35% 50% after correction tracks, respectively. addition, accurate deformation corrected improved investigation, not only can help delineating boundaries space but also retrieving movement evolution time.