## 2 Materials and Methods
### Materials
#### 2.1.3 Validation Data  
Satellite-based SIF observations represent a regional and large-scale remote sensing method. Therefore, to verify the accuracy of these data, it is essential to perform cross-comparisons using in situ near-surface observations. In recent years, several ground-based SIF observation systems have been developed to meet the requirements of ecosystem and canopy-scale monitoring [30; 31]. One such system is PhotoSpec, a ground-based spectrometer system designed to measure SIF distributions in the red (670-732 nm) and far-red (729-784 nm) wavelength ranges [30]. The system is usually mounted on a flux tower, and its height from the underlying surface is determined based on the observed target. Continuous measurements are usually conducted during the day, and the data are processed to a 30 min time resolution to match the results of flux measurements. According to observational data provided by [PERSON] et al., measurements were conducted at two sites: CA-OBS in Canada (53.98\({}^{\circ}\)N, 105.12\({}^{\circ}\)W) and US-NR1 in Colorado, USA (40.03\({}^{\circ}\)N, 105.55\({}^{\circ}\)W) [32; 33]. On the other hand, the China Spectral Observation Network provides continuous SIF monitoring at multiple flux tower sites across China [23], offering standard 30 min and daily average observations. Two sites, Huailai in Hebei Province and Jurong in Jiangsu Province, were selected from publicly available datasets for validation purposes [31; 34]. During the site selection process, we excluded locations with insufficient observation periods or poor data quality. Ultimately, only the above four sites were retained, as their reliability had been utilized and verified in previous studies.  
Additionally, we conducted comparative analyses with existing satellite SIF products, including the TROPOMI SIF product and the GOME-2 0.05\({}^{\circ}\) product. The TROPOMI SIF dataset used is the gridded 0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\) eSIF product, which is an 8-day composite derived from \"baseline\" SIF retrievals in the 743-758 nm band. The dataset excludes observations with a cloud fraction > 0.2, a viewing zenith angle > 0.5, or with invalid cloud screening [35]. The GOME-2 SIF product referenced here, known as SIF\({}_{\text{Diveuiller}}\), was developed by [PERSON] et al. using GOME-2 SIF data downscaled via a Light Use Efficiency (LUE) model to 8-day, 0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\) resolution [36].  
\begin{table}
\begin{tabular}{c c c c} \hline
**Data** & **Resolution** & **Description** & **Source** \\ \hline MCD43C4 & 0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\) & NBAR: Nadir BRDF-Adjusted & [[https://lpdaac.usgs.gov/products/](https://lpdaac.usgs.gov/products/)]([https://lpdaac.usgs.gov/products/](https://lpdaac.usgs.gov/products/)) \\  & & Reflectance & mcd43c4v061/ (accessed on 5 June 2025) \\ MOD11C1 & 0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\) & LST: Land Surface Temperature & [[https://lpdaac.usgs.gov/products/](https://lpdaac.usgs.gov/products/)]([https://lpdaac.usgs.gov/products/](https://lpdaac.usgs.gov/products/)) \\  & & PAR: Photosynthetically Active & [[https://ceres.larc.nasa.gov/data/](https://ceres.larc.nasa.gov/data/)]([https://ceres.larc.nasa.gov/data/](https://ceres.larc.nasa.gov/data/))\# \\ CERES\_SYN1 deg & 1\({}^{\circ}\)\(\times\) 1\({}^{\circ}\) & Radiation & (accessed on 5 June 2025) \\ MCD12C1 & 0.05\({}^{\circ}\)\(\times\) 0.05\({}^{\circ}\) & IGBP classification: Land & [[https://lpdaac.usgs.gov/products/](https://lpdaac.usgs.gov/products/)]([https://lpdaac.usgs.gov/products/](https://lpdaac.usgs.gov/products/)) \\  & & Use/Land Cover type & mcd12c1v061/ (accessed on 5 June 2025) \\ GOME-2 SIF & 0.5\({}^{\circ}\)\(\times\) 0.5\({}^{\circ}\) & SIF: Sun-induced chlorophyll & [[ftp://ftp.gfz-potsdam.de/home/mefe/](ftp://ftp.gfz-potsdam.de/home/mefe/)]([ftp://ftp.gfz-potsdam.de/home/mefe/](ftp://ftp.gfz-potsdam.de/home/mefe/)) \\  & & Fluorescence & GlobFluo/ (accessed on 5 June 2025) \\ \hline \end{tabular}
\end{table}
Table 1: Model input data.