## 1 Introduction  
Boreal forest covers a large part of the northern hemisphere, stretching from Canada over to Northern Europe and Siberia. With nearly 12.2 million km\({}^{2}\), boreal forests are one third of the global forest cover [1]. Boreal forests play a crucial role in the global carbon sequestration cycle, containing almost 30% of the world's carbon stock. Thus, assessing forest productivity [2; 3; 4] is important for monitoring change in forest carbon stock. The cost-effective acquisition of spatial data on large forest areas can only be achieved using remote sensing instruments. Fortunately, with the advent of recent satellite instruments with higher spatial and spectral resolution, such as Sentinel 2 [5] and the upcoming ESA's FLEX mission [6], the quantification of biochemical processes can be currently achieved on a large scale. Photosynthetic light use efficiency (LUE), the efficiency at which the plant converts light into fixed carbon, is one of the indicators used in the field of remote sensing of vegetation productivity [7]. LUE is defined as the ratio of gross primary production (GPP) to photosynthetically active radiation absorbed by vegetation (APAR) [7; 8; 9]. The LUE of plants can show significant variation at all scales, with structural scales ranging from within-leaf to ecosystems, and temporal scales ranging from near-instantaneous to annual, due to plant seasonal cycles [10; 11]. The LUE of plants is driven on a daily basis by changes in light, water, and temperature. Under excessive incident radiation, plants activate their defense mechanisms, de-epoxidate their xanthophyll cycle pigments, and downregulate photosynthesis. Excess light is then discarded as heat [12]. Measuring photosynthetic activity using remote sensing has significantly increased in popularity over the last two decades. At the moment, one of the most promising proxies for measuring LUE remotely is the xanthophyll-sensitive photochemical reflectance index (PRI) [13], one of the few vegetation indices that have proven to be effective in estimating LUE and pigment composition at both the leaf and canopy scales [13; 14]. PRI is a narrow-band spectral index used to detect light-induced change in the epoxidation state of the xanthophyll cycle [15], and is used as a proxy for vegetation stress detection on a diurnal timescale [13]. PRI is defined as: \(\text{PRI}=\frac{r_{\text{31}}-r_{\text{700}}}{r_{\text{531}}-r_{\text{750}}}\) where \(r_{\lambda}\) is the reflectance factor at the wavelength \(\lambda\) in nanometers of either a plant leaf or canopy. The downregulation associated with a change in the epoxidation state of xanthophylls is visible at 531 nm. The 570 nm-band is insensitive to short-term changes in the xanthophyll cycle, and is used as a reference. The usability of PRI has been extensively validated at the leaf level [16]. PRI theoretically ranges from \(-1\) to \(1\), with high PRI values indicating a lack of downregulation [17]. Under natural conditions, the range of PRI is substantially reduced, with most values being between \(-0.2\) and \(0.2\)[18; 19]. Contrary to the scale of a leaf, at canopy level, PRI is ambiguously related to LUE. It is affected by factors such as understory reflection, viewing direction, and different illumination conditions [19; 20; 21]. [PERSON] and [PERSON] [18] showed that LUE derived from canopy PRI values can vary significantly due to variations in the observation angle, soil background, and leaf area index (LAI). The narrow crown dimensions of trees in boreal forests create strong shadows and allow for easy penetration of understory reflectance [22; 23; 24]. In addition to changes in the xanthophyll cycle, morphological changes in plants during the seasonal cycle, water stress, drought, and air temperature all have direct effects on the leaf PRI-LUE relationship [25; 26]. The crowns of single trees, especially in high northern latitudes where the solar angle is low, are always partly shaded due to neighboring crowns.