Mapping oak wilt disease from space using land surface phenology

Keyphrases

• Oak Wilt 100%
• Land Surface Phenology 100%
• Carotenoids 66%
• Chlorophyll a (Chl a) 66%
• Phenological Metrics 66%
• Oak Trees 50%
• Area under the Curve 50%
• Space Observation 33%
• Minnesota 16%
• Disease Progression 16%
• High-resolution 16%
• Wisconsin 16%
• Biodiversity 16%
• Partial Least Squares Structural Equation Modeling (PLS-SEM) 16%
• Ecosystem Services 16%
• Growing Season 16%
• Multi-location 16%
• Pathogenic Fungi 16%
• Forest Health 16%
• False Positive Rate 16%
• Health Condition 16%
• Scale Change 16%
• Coefficient of Variation 16%
• Time-series Observations 16%
• Overall Accuracy 16%
• Model Performance 16%
• Local Stakeholders 16%
• Photosynthetic Activity 16%
• Start of Season 16%
• Prediction Map 16%
• End of Growing Season 16%
• Dense Time Series 16%
• Discriminant Model 16%
• Sentinel-2 16%
• Bretziella Fagacearum 16%
• Analysis Ready Data 16%
• Tree Health Condition 16%
• Airborne Imagery 16%
• Common Oak 16%
• Ground Verification 16%
• Dead Area 16%
• Phenological Shift 16%
• Developing Tools 16%
• Disease Hotspot 16%

Agricultural and Biological Sciences

• Quercus 100%
• Phenology 100%
• Wilt Disease 100%
• Carotenoid 44%
• Growing Season 22%
• Photosynthetic Pigment 11%
• Tree Health 11%
• Forest Health 11%
• Pathogenic Fungus 11%
• Least Square 11%
• Decision Making 11%

Earth and Planetary Sciences

• Land Surface 100%
• Carotenoid 66%
• Growing Season 33%
• Minnesota 16%
• Ecosystem Service 16%
• Forest Health 16%
• Wisconsin 16%
• Time Series 16%
• Spatial Variation 16%
• Sentinel-2 16%
• Airborne Sensing 16%
• Decision Making 16%