TY  - JOUR
AU  - Buffat, Jim
AU  - Pato, Miguel
AU  - Alonso, Kevin
AU  - Auer, Stefan
AU  - Carmona, Emiliano
AU  - Maier, Stefan
AU  - Müller, Rupert
AU  - Rademske, Patrick
AU  - Siegmann, Bastian
AU  - Rascher, Uwe
AU  - Scharr, Hanno
TI  - A multi-layer perceptron approach for SIF retrieval in the O2-A absorption band from hyperspectral imagery of the HyPlant airborne sensor system
JO  - Remote sensing of environment
VL  - 318
SN  - 0034-4257
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - FZJ-2025-01146
SP  - 114596 -
PY  - 2025
N1  - published under CC-BY-NC and Gold Open Access
AB  - Accurate estimation of solar-induced fluorescence (SIF) from passively sensed hyperspectral remote sensing data has been identified as fundamental in assessing the photosynthetic activity of plants for various scientific and ecological applications at various spatial scales. Different techniques to derive SIF have been developed over the last decades. In view of ESA’s upcoming Earth Explorer satellite mission FLEX aiming to provide high-quality global imagery for SIF retrieval an increased interest is placed in physical approaches. We present a novel method to retrieve SIF in the O2-A absorption band of hyperspectral imagery acquired by the HyPlant sensor system. It aims at a tight integration of physical radiative transfer principles and self-supervised neural network training. To this end, a set of spatial and spectral constraints and a specific loss formulation are adopted. In a validation study we find good agreement between our approach and established retrieval methods as well as with in-situ top-of-canopy SIF measurements. In two application studies, we additionally find evidence that the estimated SIF (i) satisfies a first-order model of diurnal SIF variation and (ii) locally adapts the estimated optical depth in topographically variable terrain.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:001399725900001
DO  - DOI:10.1016/j.rse.2024.114596
UR  - https://juser.fz-juelich.de/record/1038099
ER  -