Interpretable Spatial Completion of Sparse InSAR-Derived Activity for Enhanced Landslide Susceptibility Zonation

Conventional landslide susceptibility mapping (LSM) mainly describes long-term predisposing conditions, but it is less sensitive to recent slope deformation. Interferometric synthetic aperture radar (InSAR) provides dynamic deformation evidence, yet valid observations are often spatially discontinuous in mountainous reservoir terrain. To address this limitation, this study proposes an interpretable framework for completing sparse InSAR-derived dynamic activity and incorporating it into landslide susceptibility enhancement in the Changping area of the Three Gorges Reservoir Area. The framework first uses 12 conditioning factors and ensemble learning to generate first-level susceptibility. Small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) deformation is then projected into the slope-oriented direction, and deformation-rate intensity and deformation trends are combined to derive observed activity labels. For activity completion, the active class was constructed from observed active InSAR cells, whereas the non-active class combined 1882 low-activity InSAR cells with randomly sampled proxy-reference cells from the unlabelled background. Extreme Gradient Boosting (XGBoost) was selected to estimate a continuous relative dynamic-activity score across the study area, achieving a mean receiver operating characteristic area under the curve (ROC-AUC) of 0.9002 across five independent proxy-reference sampling repeats. The completed activity layer was integrated with first-level susceptibility at the slope-unit scale and evaluated against a separately compiled supplementary survey inventory comprising 27 landslide records and 25 affected slope units. The enhanced moderate-to-high susceptibility classes captured more affected slope units than the corresponding first-level static classes, while occupying a similar proportion of all slope units. The enhanced moderate-to-high susceptibility classes captured 17 of the 25 affected slope units, compared with 12 for the static classes, a descriptive improvement while classifying a similar proportion of all slope units as moderate-to-high. A conditional comparison within static susceptibility classes further indicated incremental discriminatory information from the InSAR-conditioned activity layer. The completed activity layer was therefore described as an InSAR-conditioned relative dynamic-activity score constrained by the shared environmental predictors. SHapley Additive exPlanations (SHAP) and directed-dependence analyses further characterized the predictive contributions and structural associations of road proximity, built-up intensity, vegetation cover, lithological background, and slope geometry with the completed activity pattern. This framework provides a practical and interpretable route for using discontinuous InSAR observations in susceptibility enhancement.