A Quadtree Wavelet Multiresolution Approach for InSAR Heterogeneous Topography-Correlated Tropospheric Delay Correction in Mountainous Landslide Monitoring

Landslides are recurrent and far-reaching natural disasters that exert significant impacts on infrastructure stability and human livelihood. Interferometric Synthetic Aperture Radar (InSAR) has been widely adopted for landslide deformation monitoring and early hazard detection with its features such as broad spatial coverage and high accuracy. However, in mountainous canyon regions which are more likely to the unstable rock and soil movements, InSAR is particularly susceptible due to elevation-correlated tropospheric delays. Existing correction methods, predominantly based on mathematical modeling of atmosphere-elevation relationships, exhibit limitations to estimate topography-correlated tropospheric delays with heterogeneous terrain in the spatial domain. This study proposes a new wavelet multi-resolution analysis approach, namely Quad-Multiresolution Analysis (Quad-MRA), that accounts for spatial heterogeneity of tropospheric delays in the frequency domain with a quad-tree segmentation strategy. The validation in simulated experiments indicates Quad-MRA method not only mitigates atmospheric delays but also enhances phase stability, reducing the Standard Deviation (STD) of interferograms from 3.8 rad to 0.7 rad. We further found that the applicability of this method is influenced by the proportion of landslide-affected pixels in the interferogram, with optimal performance observed when the pixel proportion is 2% or lower. This method also has been employed for the Zhongpai Landslide, Gansu, China using the Sentinel-1 data, in which various lines of highways passby. The results demonstrate a 50% reduction in STD of phase fluctuation, and the Root Mean Square Error (RMSE) for InSAR and GNSS improves from 32 mm to 7 mm. The results also identified four distinct deformation transitions between 2021-2024, and each associated with accelerated deformation triggered by rainfall. These findings demonstrate the effectiveness of proposed method in mitigating topographic related tropospheric delays in the mountainous terrain, and particularly benefits for the landslide monitoring, detection, and mechanism interpretation.