## Materials and Methods
### DART Simulation
#### 2.2.4 Simulation Experiment  
We conducted a numerical simulation experiment to simulate SIF escape probability using the 3-D DART model and then using it to evaluate the validity of the remote estimation methods described in Section 2.1. DART provides a realistic representation of plant architecture [18; 29]. Hence, DART provides a way to simulate and evaluate SIF escape probability in a more realistic vegetation scene relative to simpler models, especially for sparse forest stands which are found across the boreal forest [31]. A 3-D Silver birch tree (_Betula pendula_ Roth) reconstructed from Terrestrial laser scanning (TLS) data, measured in the vicinity of the Station for Measuring Ecosystem-Atmosphere Relations II (SMEAR II) in southern Finland (24.31478\({}^{\circ}\) E, 61.84335\({}^{\circ}\) N), was used to generate a 3-D simulation scene. We used an option of repetitive scene of the DART model to eliminate boundary effects [29]. The scene horizontal dimension was set to 4 m for default configuration (i.e., fractional vegetation cover (FVC) = 0.6, see Table 2). By adjusting the scene horizontal dimensions, the fractional vegetation cover (FVC) was modified from sparse forest (FVC = 0.3) to a dense forest (FVC = 0.8). Due to the computational constraints, four key input parameters of the DART model were varied to generate the simulation database (see Table 2), including leaf chlorophyll content (Cab), fractional vegetation cover (FVC), background spectra, and solar zenith angle (SZA). Variable values of leaf chlorophyll content were used to represent the variation of leaf optical properties. Varying values of fractional vegetation cover were used to describe the canopy structure of different forest types: 0.3, 0.6, and 0.8 are referred to as very sparse, little sparse, and dense forest, respectively. Given the two-layer structure of the forest and its seasonal variation in spectral properties, three typical background spectra were adapted to represent the change of background spectral properties. In addition, a non-reflecting background was used to test the ability of SIF escape probability that was estimated using SIT. Contrary to the DART simulations carried out by previous studies in which the solar zenith angle was set to a constant value [12; 23], the solar zenith angle was varied here from 20\({}^{\circ}\) to 70\({}^{\circ}\) with a step of 10\({}^{\circ}\) to represent the seasonal variation for most of the boreal forest areas. Details about the other default variables for the DART simulations can be found in [29]. All simulations were performed between 640 and 850 nm at a spectral resolution of 7.5 nm. Directional and total emitted SIF at 760 nm were used for the simulation and estimation of SIF escape probability. All canopy reflectance and SIF were retrieved in nadir viewing direction (i.e., view zenith angle equal to 0) to keep consistent with the default observation mode of current SIF satellite (such as the OCO-2 satellite). NDVI was derived from the canopy reflectance in the red (650 nm) and near-infra-red (NIR) (800 nm) bands according to [32]. SIF escape probabilities simulated by the DART \begin{table}
\begin{tabular}{c c c c c} \hline  & **Parameters** & **Unit** & **Values** & **Default** \\ \hline Leaf optical properties & Chlorophylll content (Cab) & \(\mu\)g/cm\({}^{2}\) & 15, 35, 60 & 35 \\ \hline Canopy structure & Fractional vegetation cover (FVC) & [-] & 0.3, 0.6, 0.8 & 0.6 \\ \hline Background spectral properties & Background reflectance spectra & [-] & Three reflectance spectra (see Figure S1: Ref-1, 2, and 3) and a non-reflecting background & Ref-2 \\ \hline Solar-view geometry & Solar zenith angle (SZA) & [\({}^{\circ}\)] & 20–70\({}^{\circ}\) with a step of 10\({}^{\circ}\) & 30 \\ \hline \end{tabular}
\end{table} 
Table 2: Main input parameters of the Discrete Anisotropic Radiative Transfer (DART) simulations with indication of the default configuration.