Atmospheric correction of vegetation reflectance with simulation-trained deep learning for ground-based hyperspectral remote sensing
Abstract Background Vegetation spectral reflectance obtained with hyperspectral imaging (HSI) offer non-invasive means for the non-destructive study of their physiological status. The light intensity at visible and near-infrared wavelengths (VNIR, 0.4–1.0µm) captured by the sensor are composed of mi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-07-01
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| Series: | Plant Methods |
| Online Access: | https://doi.org/10.1186/s13007-023-01046-6 |