Slope Stability

Slope stability analysis focuses on predicting the likelihood of landslides, a crucial task for mitigating risks to life and infrastructure. Current research emphasizes developing improved predictive models, leveraging machine learning techniques such as neural networks (including physics-informed and interpretable variants) and ensemble methods like random forests, often incorporating high-resolution remote sensing data and digital elevation models. These advancements aim to enhance prediction accuracy, reduce computational costs, and provide greater insight into the contributing factors influencing slope failure, ultimately leading to more effective landslide hazard assessment and management.