1 Fundamentals of Polarimetric Radar Imaging and Interpretation |
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1 | (42) |
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1.1 Radar Polarimetry Basics |
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2 | (8) |
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1.1.1 Polarization of Electromagnetic Wave |
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2 | (3) |
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1.1.2 Polarimetric Scattering Matrix |
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5 | (1) |
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1.1.3 Polarization Basis Transformation |
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6 | (1) |
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1.1.4 Polarimetric Coherency Matrix in Linear Polarization Basis |
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7 | (1) |
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1.1.5 Polarimetric Covariance Matrix in Linear Polarization Basis |
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8 | (1) |
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1.1.6 Polarimetric Covariance Matrix in Circular Polarization Basis |
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9 | (1) |
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1.2 Polarimetric Radar Imaging |
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10 | (12) |
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10 | (1) |
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1.2.2 SAR Imaging Principles |
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11 | (2) |
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13 | (3) |
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16 | (3) |
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1.2.5 PoIInSAR Principles |
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19 | (3) |
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1.3 Target Scattering Mechanism Interpretation Overview |
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22 | (16) |
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1.3.1 Basic Eigenvalue-Eigenvector-Based Decomposition |
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24 | (3) |
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1.3.2 Basic Model-Based Decomposition |
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27 | (7) |
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1.3.3 Polarization Orientation Angle and Orientation Compensation |
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34 | (4) |
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38 | (1) |
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38 | (5) |
2 Advanced Polarimetric Target Decomposition |
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43 | (64) |
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43 | (1) |
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2.2 Limitations of Classical Model-Based Decomposition |
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44 | (11) |
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2.2.1 Dynamic Range of Volume Scattering Component |
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44 | (3) |
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2.2.2 Orientation Compensation and Its Limitation |
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47 | (8) |
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2.3 Recent Advances in Model-Based Decomposition |
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55 | (7) |
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2.3.1 Orientation Compensation Processing |
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56 | (3) |
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2.3.2 Nonnegative Eigenvalue Constraint |
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59 | (1) |
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2.3.3 Generalized Volume Scattering Models |
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59 | (1) |
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2.3.4 Generalized Double- and Odd-Bounce Scattering Models |
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60 | (1) |
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2.3.5 Complete Information Utilization |
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60 | (1) |
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2.3.6 Full-Parameter Inversion Strategy |
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61 | (1) |
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2.3.7 Fusion of Polarimetric-Interferometric Information |
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62 | (1) |
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2.4 Adaptive Polarimetric-Interferometric Model-Based Decomposition |
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62 | (18) |
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2.4.1 Po1InSAR Coherence Diversity Investigation |
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63 | (3) |
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2.4.2 Adaptive Model-Based Decomposition Development |
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66 | (4) |
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2.4.3 Experiment with Airborne PoIInSAR Data |
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70 | (5) |
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2.4.4 Experiment with Spaceborne PoIInSAR Data |
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75 | (4) |
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2.4.5 Discussions and Perspectives |
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79 | (1) |
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80 | (1) |
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2.5 General Model-Based Decomposition |
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80 | (19) |
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2.5.1 General Decomposition Scheme |
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81 | (4) |
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2.5.2 Experimental Results and Analysis |
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85 | (6) |
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91 | (7) |
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98 | (1) |
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2.6 Discussions and Perspectives |
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99 | (3) |
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2.6.1 PoISAR Data Preprocessing Issue |
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99 | (1) |
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2.6.2 Radar Frequency Issue |
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99 | (1) |
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2.6.3 High Spatial Resolution Issue |
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99 | (1) |
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2.6.4 Model Priority Issue |
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100 | (1) |
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100 | (1) |
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2.6.6 Performance Evaluation Issue |
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101 | (1) |
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2.6.7 Further Generalized Modeling |
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102 | (1) |
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102 | (1) |
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103 | (4) |
3 Uniform Polarimetric Matrix Rotation Theory |
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107 | (36) |
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107 | (1) |
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3.2 Polarimetric Matrix in Rotation Domain |
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108 | (4) |
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3.2.1 Polarimetric Scattering Matrix in Rotation Domain |
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108 | (1) |
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3.2.2 Polarimetric Coherency Matrix in Rotation Domain |
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109 | (1) |
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3.2.3 Cascade Rotation Property |
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110 | (1) |
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3.2.4 Roll-Invariant Terms |
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111 | (1) |
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3.3 Development of the Uniform Polarimetric Matrix Rotation Theory |
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112 | (10) |
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3.3.1 Uniform Representation |
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112 | (1) |
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3.3.2 Interpretation of Oscillation Parameters |
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113 | (3) |
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3.3.3 Further Derived Angle Parameters and Interpretation |
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116 | (3) |
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3.3.4 Links to Huynen Parameters and Interpretation |
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119 | (1) |
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3.3.5 Polarimetric Covariance Matrix in Rotation Domain |
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120 | (2) |
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3.4 Demonstration and Application of Oscillation Parameters |
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122 | (4) |
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3.4.1 Multi-Frequency Pi-SAR Data Description |
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123 | (1) |
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3.4.2 Oscillation Parameters |
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123 | (3) |
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3.5 Demonstration and Application of Angle Parameters |
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126 | (5) |
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3.5.1 Multi-Frequency AIRSAR Data Description |
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126 | (1) |
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127 | (1) |
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3.5.3 Unsupervised Land Cover Classification |
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128 | (3) |
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3.6 Supervised Classification Demonstration |
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131 | (6) |
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3.6.1 Demonstration with SVM Classifier |
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132 | (3) |
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3.6.2 Demonstration with DT Classifier |
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135 | (2) |
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3.7 Discussions and Perspectives |
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137 | (1) |
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3.7.1 Summary of Roll-Invariant Terms |
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137 | (1) |
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3.7.2 Utilization Perspectives |
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137 | (1) |
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138 | (1) |
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139 | (4) |
4 Polarimetric Coherence Pattern: A Visualization and Interpretation Tool |
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143 | (38) |
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143 | (1) |
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4.2 Polarimetric Coherence Pattern |
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144 | (11) |
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4.2.1 Definition of Polarimetric Coherence Pattern |
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144 | (1) |
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4.2.2 Visualization and Characterization |
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145 | (2) |
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4.2.3 Interpretation and Discussion |
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147 | (2) |
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4.2.4 Demonstration and Investigation |
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149 | (6) |
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4.3 Classification Development and Application |
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155 | (7) |
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4.3.1 Classification Methodology Development |
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155 | (2) |
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4.3.2 Classification with UAVSAR PoISAR Data |
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157 | (1) |
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4.3.3 Classification with AIRSAR PoISAR Data |
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157 | (3) |
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4.3.4 Discussions and Perspectives |
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160 | (2) |
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4.4 Further Application for Manmade Target Extraction |
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162 | (5) |
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4.4.1 Polarimetric Coherence Enhancement Over Urban Area |
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163 | (2) |
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4.4.2 Manmade Target Extraction |
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165 | (2) |
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4.5 Further Application for Crops Discrimination |
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167 | (10) |
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4.5.1 Polarimetric Coherence Enhancement Over Crop Area |
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169 | (2) |
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4.5.2 Feature Selection and Crops Discrimination |
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171 | (6) |
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177 | (1) |
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178 | (3) |
5 Natural Disaster Investigation and Urban Damage Level Mapping |
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181 | |
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181 | (1) |
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5.2 Urban Damage Characterization Using Polarimetric Technique |
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182 | (18) |
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5.2.1 Study Area and Data Description |
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183 | (3) |
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5.2.2 Model-Based Decomposition Technique |
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186 | (7) |
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5.2.3 Polarization Orientation Angle Technique |
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193 | (7) |
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5.3 Urban Damage Level Mapping |
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200 | (14) |
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5.3.1 Urban Area Extraction |
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202 | (3) |
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5.3.2 Damage Level Index Estimation |
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205 | (1) |
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5.3.3 Experimental Study and Demonstration |
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205 | (9) |
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5.4 Other Damage Situations Investigation |
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214 | (8) |
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5.4.1 Flooded River Area Analysis Using Spaceborne PoISAR Data |
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214 | (3) |
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5.4.2 Flooded Paddy Field Analysis Using Airborne PoISAR Data |
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217 | (5) |
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222 | (1) |
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223 | |