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To objectively reflect historical patterns, future trends, and internal drivers of geohazard risk, this paper proposes the ‘hazard–impact–drive’ (HID) model for resilience assessment. The HID model advances conventional approaches by establishing causal linkages between hazard characteristics (H), exposure vulnerability (I), and driving mechanisms (D), enabling bidirectional analysis that integrates historical recognition with prospective forecasting. By extending risk assessment (R = H × I) into a resilience framework, the model ensures methodological continuity for intervention design. To quantify resilience, a comprehensive assessment model is constructed using the improved G1-CRITIC method, integrating multi-dimensional socio-economic and natural factors for indicator weighting to balance analytical rigor with operational tractability. By applying this method to Huangu Town, Shaanxi Province (2013–2022) using remote sensing and field data, the following results are obtained: (1) Resilience exhibits temporal regularity, where major turning points align with policy and social events, validating the HID model’s causal identification; (2) evolution follows a dual-timescale pattern –short-term fluctuations are driven by instantaneous natural factors, while long-term trajectories are shaped by cumulative socio-economic reconfiguration; and (3) dynamic feedback between natural and socio-economic systems creates a non-monotonic resilience trajectory, necessitating the coordination of immediate response mechanisms with multi-level long-term governance.
Xu et al. (Sun,) studied this question.