Coastal ecosystems are highly dynamic and vulnerable to climate change, sea-level rise, and rapid urbanization. However, many landscape ecological risk assessments are limited by fixed scales and assumptions of spatial uniformity. This study develops a geomorphology-based framework to analyze coastal ecological risk. Using multi-source data from 1980 to 2020, the optimal analytical scale was identified as 120 m (grain) and 1000 m (extent). An integrated approach combining OPGD, XGBoost–SHAP, and restricted cubic spline (RCS) models was applied to examine risk patterns and driving mechanisms across four coastal types in Guangdong, China. The results show that the importance and interactions of driving factors vary significantly among geomorphic types, with clear nonlinear responses. Key statistical thresholds were identified, indicating ranges where risk sensitivity changes, including NDVI ≈ 0.624 in the Hilly Ria Coast, slope ≈ 2.8° in the Platform Ria Coast, elevation ≈ 14.5 m in the Barrier–Lagoon Coast, and GDP ≈ 1644.65 × 106 CNY/km2 in the Estuarine Delta Coast. These findings provide quantitative evidence for understanding spatial heterogeneity and the nonlinear dynamics of coastal ecological risk, and offer practical references for adaptive management.
Feng et al. (Sat,) studied this question.
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