Radiative transfer and viewing geometry considerations for the SIF/GPP
relationship
Abstract
Solar-Induced chlorophyll Fluorescence (SIF) provides a powerful proxy
for determining forest gross primary production (GPP), particularly in
evergreen ecosystems where traditional measures of greenness fail. The
dynamics of the SIF/GPP relationship, however, are poorly understood
under varying viewing directions and light conditions. This is, in large
part, due to challenges in measuring SIF at the spatiotemporal scale
that is necessary to understand these effects. Therefore, the aim of
this work is to utilize high-temporal and spatial resolution SIF
measurements to better constrain the response of SIF to ambient canopy
illumination and viewing geometry. We use a PhotoSpec instrument and
eddy covariance measurements to explore the SIF/GPP relationship under
various viewing directions and light conditions during the 2019 and 2020
growing seasons at the Old Black Spruce site in Saskatchewan, Canada.
PhotoSpec is a tower-based 2-D scanning spectrometer system capable of
taking Fraunhofer-line based SIF retrievals in the red and far-red
wavelength ranges with a 0.7 degree field of view at a
~30 second time resolution. Measured SIF and GPP are
combined with SCOPE modelling results to provide a mechanistic
understanding of the physical and ecophysiological drivers for the
SIF/GPP relationship in the Boreal Forest. Our results show that viewing
direction and solar zenith/azimuth angles are important for the SIF
signal under direct light conditions, but not under diffuse.
Furthermore, the SIF/GPP relationship changes under direct and diffuse
light conditions at a 30 minute, daily, and monthly resolution. Our
ability to use SIF as a proxy for GPP depends on a quantitative
understanding of radiative transfer within the canopy and how scanning
geometry impacts SIF measurements. These results provide an important
insight into these relationships in the Boreal forest, a region where
GPP has been traditionally difficult to track using remote sensing.