Estimating Wheat Traits Using Artificial Neural Network-Based Radiative Transfer Model Inversion

Estimating Wheat Traits Using Artificial Neural Network-Based Radiative Transfer Model Inversion

Estimating wheat traits based on spectral reflectance measurements and machine learning remains challenging due to the large datasets required for model training and testing. To overcome this limitation, a simulated dataset was generated using the radiative transfer model (RTM) PROSAIL and inverted...

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Bibliographic Details
Main Authors: Lukas J. Koppensteiner, Hans-Peter Kaul, Sebastian Raubitzek, Philipp Weihs, Pia Euteneuer, Jaroslav Bernas, Gerhard Moitzi, Thomas Neubauer, Agnieszka Klimek-Kopyra, Norbert Barta, Reinhard W. Neugschwandtner
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Remote Sensing
Subjects:
phenotyping
machine learning
simulation learning
vegetation indices
background soil spectra
Online Access:https://www.mdpi.com/2072-4292/17/11/1904
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