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@INPROCEEDINGS{Buffat:1048173,
author = {Buffat, Jim and Pato, Miguel and Alonso, Kevin and Auer,
Stefan and Carmona, Emiliano and Maier, Stefan and Müller,
Rupert and Rademske, Patrick and Rascher, Uwe and Scharr,
Hanno},
title = {{R}etrieval of {S}un-{I}nduced {P}lant {F}luorescence in
the {O}$_2$-{A} {A}bsorption {B}and from {DESIS} {I}magery},
volume = {15625},
address = {Cham},
publisher = {Springer Nature Switzerland},
reportid = {FZJ-2025-04535},
isbn = {978-3-031-91835-3},
series = {Lecture Notes in Computer Science},
pages = {81 - 100},
year = {2025},
comment = {Computer Vision – ECCV 2024 Workshops / Del Bue, Alessio
(Editor) ; Cham : Springer Nature Switzerland, 2025, Chapter
6 ; ISSN: 0302-9743=1611-3349 ; ISBN:
978-3-031-91834-6=978-3-031-91835-3 ;
doi:10.1007/978-3-031-91835-3},
booktitle = {Computer Vision – ECCV 2024
Workshops / Del Bue, Alessio (Editor) ;
Cham : Springer Nature Switzerland,
2025, Chapter 6 ; ISSN:
0302-9743=1611-3349 ; ISBN:
978-3-031-91834-6=978-3-031-91835-3 ;
doi:10.1007/978-3-031-91835-3},
abstract = {We provide the first method allowing to retrieve spaceborne
SIF maps at 30 m ground resolution with a strong correlation
(r$^2$ = 0.6) to high-quality airborne estimates of
sun-induced fluorescence (SIF) ̇SIF estimates can provide
explanatory information for many tasks related to
agricultural management and physiological studies. While SIF
products from airborne platforms are accurate and spatially
well resolved, the data acquisition of such products remains
science-oriented and limited to temporally constrained
campaigns. Spaceborne SIF products on the other hand are
available globally with often sufficient revisit times.
However, the spatial resolution of spaceborne SIF products
is too small for agricultural applications. In view of
ESA’s upcoming FLEX mission we develop a method for SIF
retrieval in the O2-A band of hyperspectral DESIS imagery to
provide first insights for spaceborne SIF retrieval at high
spatial resolution. To this end, we train a simulation-based
selfsupervised network with a novel perturbation based
regularizer and test performance improvements under
additional supervised regularization of atmospheric variable
prediction. In a validation study with corresponding HyPlant
derived SIF estimates at 740 nm we find that our model
reaches a mean absolute difference of 0.78 mW nm$^{−1}$
sr$^{−1}$ m$^{−2}$},
month = {Sep},
date = {2024-09-29},
organization = {ECCV 2024 Workshops, Milano (Italy),
29 Sep 2024 - 30 Sep 2024},
cin = {IAS-8 / IBG-2},
cid = {I:(DE-Juel1)IAS-8-20210421 / I:(DE-Juel1)IBG-2-20101118},
pnm = {2173 - Agro-biogeosystems: controls, feedbacks and impact
(POF4-217) / 5112 - Cross-Domain Algorithms, Tools, Methods
Labs (ATMLs) and Research Groups (POF4-511)},
pid = {G:(DE-HGF)POF4-2173 / G:(DE-HGF)POF4-5112},
typ = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
doi = {10.1007/978-3-031-91835-3_6},
url = {https://juser.fz-juelich.de/record/1048173},
}