Dimensions overall score 5.0

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• The FSKD student model achieves state-of-the-art zero-shot CHM performance with a MedAE of 4.17 m, R²=0.51, and IoU of 0.87 on geographically distinct test tiles.result 95%
• FSKD outperforms HRCHM/DAC baselines by 29-46% in MAE (5.81 m vs. 8.14-10.84 m) with stronger correlation coefficients (0.713 vs. 0.166-0.652).result 95%
• Multi-modal fusion in the teacher model improves performance by 10-26% over RGBI-only training.technical 90%
• The method jointly predicts CHM, PAI, and FHD, a multi-metric capability not provided by current monocular CHM estimators.technical 90%
• PAI/FHD transfer remains region-dependent and benefits from local calibration.limitation 85%
• The framework remains effective under temporal mismatch between winter LiDAR and summer RGBI data, removing strict co-acquisition constraints.technical 85%
• Asymmetric distillation with appropriate model capacity is critical for the knowledge distillation framework.method 80%
• The method enables scalable 20 cm operational monitoring for workflows such as Digital Twin Germany and national Digital Orthophoto programs.market 75%

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