Improving pixel-based regional landslide susceptibility mapping

Keyphrases

• Pixel-based 100%
• Landslide Susceptibility 100%
• Regional Landslide 100%
• Hybrid Model 71%
• Explanatory Variables 57%
• Physics-based 42%
• Model Performance 28%
• Local Area 28%
• Classical Statistical 28%
• Statistical Algorithms 28%
• Spatial Neighborhood 28%
• Infinite Slope Stability 28%
• Nonlinearity 14%
• China 14%
• High Linearity 14%
• Safety Factor 14%
• Deep Learning Methods 14%
• Logistic Regression 14%
• Valuable Insight 14%
• Data-driven Approach 14%
• Pixel Area 14%
• Overfitting 14%
• Risk Mitigation 14%
• Single-pixel 14%
• Landslide 14%
• Prediction Uncertainty 14%
• Land Cover Types 14%
• 30-m Resolution 14%
• Land Cover Data 14%
• Convolutional Neural Network 14%
• Three Gorges Reservoir 14%
• Mapping Model 14%
• Generalization Ability 14%
• Mapping Practices 14%
• Data-driven Algorithm 14%
• Deep Learning Algorithm 14%
• Non-landslide 14%
• Typical Landslide 14%
• Landslide Inventory 14%
• Training Challenges 14%
• Incomplete Landslide Inventory 14%

Computer Science

• Performance Model 100%
• Stability Analysis 100%
• Interpretability 100%
• Driven Approach 50%
• Risk Mitigation 50%
• Logistic Regression 50%
• Generalization Ability 50%
• Deep Learning Technique 50%
• Convolutional Neural Network 50%
• Extensive Parameter 50%
• Mapping Practice 50%
• Deep Learning Method 50%

Earth and Planetary Sciences

• Nonlinearity 100%
• Stability Analysis 100%
• Land Cover 100%
• Slope Stability 100%
• China 50%
• Regional Geography 50%
• Safety Factor 50%