Comparing methods for solar-induced fluorescence efficiency estimation using radiative transfer modelling and airborne diurnal measurements of barley crops

Ability of remotely sensed solar-induced chlorophyll fluorescence (SIF) to serve as a vegetation productivity and stress indicator is impaired by confounding factors, such as varying crop-specific canopy structure, changing solar illumination angles, and SIF-soil optical interactions. This study investigates two normalisation approaches correcting diurnal top-of-canopy SIF observations retrieved from the O 2 -A absorption feature at 760 nm (F 760 hereafter) of summer barley crops for these confounding effects. Nadir SIF data was acquired over nine breeding experimental plots simultaneously by an airborne imaging spectrometer (HyPlant) and a drone-based high-performance point spectrometer (AirSIF). Ancillary measurements, including leaf pigment contents retrieved from drone hyperspectral imagery, destructively sampled leaf area index (LAI), and leaf water and dry matter contents, were used to test the two normalisation methods that are based on: i) the fluorescence correction vegetation index (FCVI), and ii) three versions of the near-infrared reflectance of vegetation (NIR V ). Modelling in the discrete anisotropic radiative transfer (DART) model revealed close matches for NIRv-based approaches when corrected canopy SIF was compared to simulated total chlorophyll fluorescence emitted by leaves (R 2 = 0.99). Normalisation with the FCVI also performed acceptably (R 2 = 0.93), however, it was sensitive to variations in LAI when compared to leaf emitted chlorophyll fluorescence efficiency. Based on the results modelled in DART, the NIRvH1 normalisation was found to have a superior performance over the other NIRv variations and the FCVI normalisation. Comparison of the SIF escape fractions suggests that the escape fraction estimated with NIRvH1 matched escape fraction extracted from DART more closely. When applied to the experimental drone and airborne nadir canopy SIF data, the agreement between NIRvH1 and FCVI produced chlorophyll fluorescence efficiency was very high (R 2 = 0.93). Nevertheless, NIRvH1 showed higher uncertainties for areas with low vegetation cover indicating an unaccounted contribution of SIF-soil interactions. The diurnal courses of chlorophyll fluorescence efficiency for both approaches differed not significantly from simple normalisation by incoming and apparent photosynthetically active radiation. In conclusion, SIF normalisation with NIRvH1 more accurately compensates the effects of canopy structure on top of canopy far red SIF, but when applied to top of canopy in-situ data of spring barley, the effects of NIRvH1 and FCVI on the diurnal course of SIF had a similar influence. • A drone-airborne diurnal SIF dataset interpreted using radiative transfer models. • NIRvH1 better compensates for F760 confounding effects than FCVI in simulated data. • NIRvH1 better tracks leaf F760 emission efficiency in sparse canopies than FCVI. • NIRvH1 and FCVI performed comparably in measured spectroscopy data.

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Publication Details

Journal
Remote Sensing of Environment
Published
2024-11-26
DOI
https://doi.org/10.1016/j.rse.2024.114521
Citations
6
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
2.75
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article

Comparing methods for solar-induced fluorescence efficiency estimation using radiative transfer modelling and airborne diurnal measurements of barley crops

Bastian Siegmann, Julie Krämer, Uwe Rascher, Juliane Bendig et al.
6 citations
Remote Sensing of Environment
Remote Sensing in Agriculture
2.75
article

Comparing methods for solar-induced fluorescence efficiency estimation using radiative transfer modelling and airborne diurnal measurements of barley crops

Bastian Siegmann, Julie Krämer, Uwe Rascher, Juliane Bendig, Zbyněk Malenovský
article en
6 citations

Abstract

Ability of remotely sensed solar-induced chlorophyll fluorescence (SIF) to serve as a vegetation productivity and stress indicator is impaired by confounding factors, such as varying crop-specific canopy structure, changing solar illumination angles, and SIF-soil optical interactions. This study investigates two normalisation approaches correcting diurnal top-of-canopy SIF observations retrieved from the O 2 -A absorption feature at 760 nm (F 760 hereafter) of summer barley crops for these confounding effects. Nadir SIF data was acquired over nine breeding experimental plots simultaneously by an airborne imaging spectrometer (HyPlant) and a drone-based high-performance point spectrometer (AirSIF). Ancillary measurements, including leaf pigment contents retrieved from drone hyperspectral imagery, destructively sampled leaf area index (LAI), and leaf water and dry matter contents, were used to test the two normalisation methods that are based on: i) the fluorescence correction vegetation index (FCVI), and ii) three versions of the near-infrared reflectance of vegetation (NIR V ). Modelling in the discrete anisotropic radiative transfer (DART) model revealed close matches for NIRv-based approaches when corrected canopy SIF was compared to simulated total chlorophyll fluorescence emitted by leaves (R 2 = 0.99). Normalisation with the FCVI also performed acceptably (R 2 = 0.93), however, it was sensitive to variations in LAI when compared to leaf emitted chlorophyll fluorescence efficiency. Based on the results modelled in DART, the NIRvH1 normalisation was found to have a superior performance over the other NIRv variations and the FCVI normalisation. Comparison of the SIF escape fractions suggests that the escape fraction estimated with NIRvH1 matched escape fraction extracted from DART more closely. When applied to the experimental drone and airborne nadir canopy SIF data, the agreement between NIRvH1 and FCVI produced chlorophyll fluorescence efficiency was very high (R 2 = 0.93). Nevertheless, NIRvH1 showed higher uncertainties for areas with low vegetation cover indicating an unaccounted contribution of SIF-soil interactions. The diurnal courses of chlorophyll fluorescence efficiency for both approaches differed not significantly from simple normalisation by incoming and apparent photosynthetically active radiation. In conclusion, SIF normalisation with NIRvH1 more accurately compensates the effects of canopy structure on top of canopy far red SIF, but when applied to top of canopy in-situ data of spring barley, the effects of NIRvH1 and FCVI on the diurnal course of SIF had a similar influence. • A drone-airborne diurnal SIF dataset interpreted using radiative transfer models. • NIRvH1 better compensates for F760 confounding effects than FCVI in simulated data. • NIRvH1 better tracks leaf F760 emission efficiency in sparse canopies than FCVI. • NIRvH1 and FCVI performed comparably in measured spectroscopy data.

Remote Sensing of EnvironmentVol. 317
University of Tasmania (AU), University of Bonn (DE), Forschungszentrum Jülich (DE), Centre d'Études Spatiales de la Biosphère (FR)
Affordable and clean energy
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
2.75
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