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UAV multispectral to hyperspectral reconstruction based on deep learning and radiative transfer models for crop nitrogen monitoring

International Journal of Applied Earth Observation and Geoinformation · 1 Jun 2026 · 10.1016/j.jag.2026.105364

Abstract

• Proposed a multispectral to hyperspectral reconstruction framework M2H–SWIR. • The M2H–SWIR framework integrates the PROSAIL and deep learning. • M2H–SWIR reconstructs VNIR multispectral to full-range hyperspectral (400–2500 nm) • Reconstructed SWIR bands enhance UAV-based canopy nitrogen mapping accuracy. • M2H–SWIR outperforms traditional PROSAIL inversion for canopy nitrogen estimation.

Plant phenotyping relevance

UAVマルチスペクトルからハイパースペクトルを再構成し、作物キャノピー窒素を推定する手法が研究の中心であり、植物形質の取得・推定方法を開発している。

abstractProposed a multispectral to hyperspectral reconstruction framework M2H–SWIR.
abstractReconstructed SWIR bands enhance UAV-based canopy nitrogen mapping accuracy.
abstractM2H–SWIR outperforms traditional PROSAIL inversion for canopy nitrogen estimation.

Code and data availability

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