Contribution to a conference proceedings

FZJ-2023-04569

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png DEEP LEARNING BASED PREDICTION OF SUN-INDUCED FLUORESCENCE FROM HYPLANT IMAGERY

Buffat, J. (Corresponding author)FZJ* ; Pato, M. ; Alonso, K. ; Auer, S. ; Carmona, E. ; Maier, S. ; Müller, R. ; Rademske, P.FZJ* ; Rascher, U.FZJ* ; Scharr, H.FZJ*

2023
IEEE

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Please use a persistent id in citations: doi:10.1109/IGARSS52108.2023.10282828  doi:10.34734/FZJ-2023-04569

Abstract: The retrieval of sun-induced fluorescence (SIF) from hyper- spectral imagery is an ill-posed problem that has been tackled in different ways. We present a novel retrieval method com- bining semi-supervised deep learning with an existing spec- tral fitting method. A validation study with in-situ SIF mea- surements shows high sensitivity of the deep learning method to SIF changes even though systematic shifts deteriorate its absolute prediction accuracy. A detailed analysis of diurnal SIF dynamics and SIF prediction in topographically variable terrain highlights the benefits of this deep learning approach.

Note: This work is funded by the Helmholtz Initiative and Networking Fund, Helmholtz AI, Deutsches Zentrum für Luft- und Raumfahrt and Forschungszentrum Jülich GmbH. The authors gratefully acknowledge the computing time granted by the JARA Vergabegremium and provided on the JARA Partition part of the supercomputer JURECA [1] at Forschungszentrum Jülich.Jülch Supercomputing Centre, “JURECA: Data Centric and Booster Modules implementing the Modular Supercomputing Architecture at Jülch Supercomputing Centre,” Journal of large-scale research facilities, vol. 7, no. A182, 2021. [Online]. Available: http://dx.doi.org/10.17815/jlsrf-7-182

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Contributing Institute(s):

1. Pflanzenwissenschaften (IBG-2)
2. Datenanalyse und Maschinenlernen (IAS-8)

Research Program(s):

1. 2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217) (POF4-217)
2. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2023

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Database coverage:

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