A Machine Learning Approach for Maize Green Area Index Retrieval from Multi-Polarization C- and L-band Synthetic Aperture Radar Data

Bouchat, Jean;Tronquo, Emma;Orban, Anne;Neyt, Xavier;Defourny, Pierre;et.al.
(2022) 2022 Living Planet Symposium — Location: Bonn, Germany (23.May.2022)

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Authors
  • Bouchat, Jeanorcid-logoUCLouvain
    Author
  • Tronquo, EmmaUGent
    Author
  • Orban, AnneULiège
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  • Neyt, XavierRoyal Military Academy
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  • et. al.
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Citations

Bouchat, J., Tronquo, E., Orban, A., Neyt, X., Verhoest, N. E. C., Defourny, P., & et al. (2022). A Machine Learning Approach for Maize Green Area Index Retrieval from Multi-Polarization C- and L-band Synthetic Aperture Radar Data. 2022 Living Planet Symposium, Bonn, Germany. https://hdl.handle.net/2078.5/241109