Largely Automated Regional Screening of Candidate Active-Slope Units Integrating InSAR and Topographic Constraints

Landslides are among the most serious geohazards worldwide, and accurately identifying their locations is a prerequisite for effective risk prevention and mitigation. However, regional-scale screening of candidate active-slope units from InSAR observations is still hindered by subjective manual interpretation, inconsistent deformation-rate thresholds, and insufficient topographic constraints. To address these limitations, this study proposes a largely automated terrain-constrained framework for candidate active-slope screening by integrating InSAR observations, slope units, and screening based on slope-unit bootstrap intervals and a regional two-standard-deviation background envelope. First, surface deformation rates are derived from InSAR measurements and post-processed to reduce the influence of identifiable artifacts before slope-unit analysis. Then, a clustering-based method is introduced to delineate topographically constrained slope units in alpine canyon regions, whose visual terrain correspondence is examined qualitatively using terrain information and optical imagery. Next, rather than applying a fixed site-specific deformation-rate cutoff in mm/yr, data-dependent bootstrap confidence-interval comparisons are used to determine whether the deformation interval of each slope unit extends beyond the regional deformation-background interval, thereby enabling rule-based screening of candidate active-slope units. This confidence-interval screening rule provides a quantitative criterion for regional screening but requires further calibration across additional geomorphic and deformation settings. Finally, the proposed method is applied to two landslide-prone regions in western China, located in sections of the Upper Yellow River and Upper Jinsha River, where final inventories containing 92 and 25 candidate active-slope units are produced, respectively. These polygons are geomorphologically constrained candidate active-slope units produced for regional screening and should not be interpreted as the exact boundaries of individual landslides. Inventory-based spatial comparison and targeted optical inspection were reported as complementary evidence streams rather than as independent validation of contemporaneous slope activity. These results document implementation in two related alpine river-valley settings in western China and indicate the framework’s potential as a quantitatively defined, topographically constrained approach for largely automated regional screening of candidate active-slope units in comparable settings. These two applications do not establish broad applicability across substantially different environments.