## 3 Materials and Methods
### Retrieval of Vegetation Properties Time Series Using HLS and Airborne Data and the SCOPE Model
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline  & **Parameter** & **Symbol** & **Unit** & **LB** & **UB** & **UB** & **\(\mu\)** & **SD** & **Measured Mean \({}^{\dagger}\)/Range \({}^{\ast}\)** \\ \hline  & Leaf chlorophyll content & \(C_{\rm chh}\) & \(\rm{ng\,cm^{-2}}\) & 0 & 100 & 50 & 28.8 & 38.42 \({}^{\ddagger}\) \\ Biochemical properties & Leaf water content & \(C_{\rm w}\) & \(\rm{g\,cm^{-2}}\) & 0 & 0.05 & 0.025 & 0.01 & 0.02 \({}^{\dagger}\) \\  & Leaf dry matter content & \(C_{\rm dm}\) & \(\rm{g\,cm^{-2}}\) & 0 & 0.04 & 0.02 & 0.01 & 0.015 \({}^{\dagger}\) \\  & Senescent material & \(C_{\rm s}\) & — & 0 & 1.5 & 0.75 & 0.43 \({}^{\ast}\) & — \\  & Carotenoids & \(C_{\rm ca}\) & \(\rm{pg\,cm^{-2}}\) & 0 & 20 & 10 & 5.77 & 7.91 \({}^{\dagger}\) \\ \hline  & Leaf area index & \(LAI\) & \(\rm{mag^{-2}}\) & 6 & 10 & 8 & 1.15 & 8.66 \({}^{\dagger}\) \\ Structural properties & Leaf inclination distribution function & \(LIDF_{\rm s}\) & — & –1 & +1 & 0 & 0.58 & — \\  & Bimodality of leaf inclination & \(LIDF_{\rm b}\) & — & –1 & +1 & 0 & 0.58 & — \\  & Leaf structural parameter & N & — & 1 & 3.5 & 2.25 & 0.72 & — \\ \hline  & Soil Brightness parameter & \(B\) & — & 0 & 0.9 & 0.45 & 0.26 & — \\  & Soil spectral shape latitude & \(Lat\) & deg & 10 & 50 & 30 & 11.5 & — \\  & Soil spectral shape longitude & \(Lat\) & deg & 40 & 70 & 55 & 8.7 & — \\  & Soil water content & SWC & \(\%\) & & & & 15.61-31.54 \({}^{\ast}\) \\ \hline \end{tabular} \({}^{\dagger}\) means mean and \({}^{\ast}\) means range.  
\end{table} 
Table 2: Input parameters for the radiative transfer module (RTMo) of the Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model together with the lower bound (LB), upper bound (UP), prior mean (\(\mu\)), prior standard deviation (SD), and mean of the measurements acquired in August 2016 from three field sampling plots (Figure 1). The range of the measured soil water content (SWC) in the brightness-shape-moisture (BSM) submodel is provided from Table 3.  
We evaluated the quality of HLS data before the retrieval of vegetation properties. For the 2016 vegetation growing season, we downloaded HLS data for 39 days. The HLS data are distributed with a per-pixel quality layer to mask the pixels of poor quality (e.g., due to the presence of clouds or other processing artifacts). However, the accuracy of the internal cloud mask is insufficient [30], and its use may lead to the omission of cloud detection. This was also the case for our study area for some days. Therefore, we did not use the internal cloud mask of the HLS data, but propose our method for filtering the time series based on the empirical threshold of NDVI and NIR reflectance. We only considered pixels to be of high quality when the NDVI varied between 0.5 and 0.99 (vegetation pixels) and the NIR reflectance between 0.1 and 0.4 (typical spruce canopy reflectance values as, for instance, reported by [PERSON] et al. [55]). Thresholds were set based on our previous experience with the reflectance characteristics of Norway spruce in the study area during the growing season. For each day, we calculated the mean of TOC reflectance in each HLS band within the target area if more than 50% of the pixels were of high quality (fulfilling both the NDVI and NIR thresholds). Of the original 39 days, 14 days were retained after the filtering. For the retrieval, we selected six HLS bands relevant for studying the vegetation properties that were common in both Sentinel-2 and Landsat-8 data. These selected bands were blue (482 nm), green (561.4 nm), red (654.6 nm), NIR narrow (864.7 nm), and two shortwave infrared bands (SWIR 1 (1608.9 nm) and SWIR 2 (2200.7 nm)). Table 3 shows the 14 days with the percentage of high quality pixels within the target area. For each of the 14 days with HLS data, we used an optimization method to invert the RTMo model against mean TOC reflectance to retrieve the dynamics of the vegetation properties, as described in [PERSON] et al. [24].