Mapping post-fire habitat characteristics through the fusion of remote sensing tools

Keyphrases

• Remote Sensing 100%
• LiDAR 100%
• Sensing Tool 100%
• Habitat Characteristics 100%
• Post-fire Habitat 100%
• Landsat 60%
• Woody Plants 60%
• Response Variable 60%
• Landsat Time Series 60%
• Wildlife Habitat 40%
• Shrub Cover 40%
• Series Product 40%
• Remote Sensing Predictors 40%
• Habitat Components 40%
• Remote Sensing Dataset 40%
• Forest Habitats 20%
• Salvage Logging 20%
• Forest Disturbance 20%
• 3D LiDAR 20%
• Timber 20%
• Shrub Layer 20%
• Competing Models 20%
• Area under the Curve 20%
• Management Objectives 20%
• Performance Prediction 20%
• False Negative Rate 20%
• Structure Model 20%
• Forest Condition 20%
• Calibration Data 20%
• Individual Performance 20%
• True Positive 20%
• Leave-one-out 20%
• Error Matrix 20%
• Habitat Features 20%
• Combined Model 20%
• Acceptable Accuracy 20%
• False Negative Errors 20%
• Variable Sensitivity 20%
• Logging Practices 20%
• Probability Threshold 20%
• Landsat Data 20%
• Calibration Plot 20%
• Error Accuracy 20%
• Understory Cover 20%
• Field Calibration 20%
• Cross-validation Errors 20%
• Prefire 20%
• Data Time Series 20%
• Dead Biomass 20%
• AIC Model Selection 20%
• Classification Statistics 20%
• Fire Forest 20%
• Cavity-nesting 20%

Earth and Planetary Sciences

• Landsat 100%
• Remote Sensing 100%
• Optical Radar 85%
• Time Series 42%
• Wildlife Habitat 28%
• Understory 14%
• Forest Fire 14%

Agricultural and Biological Sciences

• Landsat 100%
• Remote Sensing 100%
• Lidar 85%
• Wildlife Habitat 28%
• Understory 14%
• Forest Habitats 14%
• Forest Fire 14%
• Salvage Logging 14%