FGump applies CatBoost gradient boosting to features from multi-baseline polarimetric SAR covariance matrices and reports accurate forest and ground height estimates at low computational cost on the Paracou dataset.
First demonstration of airborne sar to- mography using multibaseline l-band data,
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An Efficient Machine Learning Framework for Forest Height Estimation from Multi-Polarimetric Multi-Baseline SAR data
FGump applies CatBoost gradient boosting to features from multi-baseline polarimetric SAR covariance matrices and reports accurate forest and ground height estimates at low computational cost on the Paracou dataset.