Quantitative detection of sediment dust analog over green canopy using airborne hyperspectral imagery

Keyphrases

• Airborne Hyperspectral Images 100%
• Airborne Imagery 50%
• Airborne Sensors 50%
• Al2O3 Oxide 50%
• Al2O3 Powder 50%
• Alumina Powder 50%
• Aluminum Oxide 50%
• Dark Background 50%
• Decision Tree Algorithm 50%
• Dual Sensor 50%
• Dust 50%
• Dust Analogue 100%
• Dust Pollution 50%
• Endmember 100%
• Gradient-based Optimization 50%
• Hyperspectral 100%
• Imagery Data 50%
• Likelihood Distance 50%
• Linear Spectral Unmixing 50%
• Maximum Likelihood Classification 50%
• Minimum Distance 50%
• Multiple Endmember Spectral Mixture Analysis (MESMA) 50%
• New Frontiers 50%
• Nonlinear Domain 50%
• Nonlinear Unmixing 50%
• Optimization Approach 50%
• Quantitative Detection 100%
• Spectral Indices 50%
• Spectral Region 50%
• Spectral Signal 50%
• Supervised Classification 50%
• SW-NIR 50%
• Unmixing 50%
• Unmixing Method 50%
• Unsupervised Classification 50%
• Vegetation Canopy 50%

Earth and Planetary Sciences

• Aluminum Oxide 100%