## 3 Results
### Spatial Distribution of Remote Sensing Products  
In this section, we present intensity maps of annual SIF, GPP, and EVI at spatial resolutions of 0.1\({}^{\circ}\) and 2\({}^{\circ}\) in Figures 8 and 9, respectively. The SIF products at 0.1\({}^{\circ}\) grid cells are directly averaged results, while those at 2\({}^{\circ}\) grid cells are normalized for illumination conditions to enable comparison with EVI.  
Considering the differences in intensity between the two SIF products, we assigned different color bars to them using the 3\(\sigma\) principle, resulting in higher color-intensity resolution in the Caltech SIF product's intensity map. The differences between the two SIF maps at a 0.1\({}^{\circ}\) grid resolution are minimal. However, under this color bar, the Caltech SIF product cannot effectively distinguish between high SIF scenarios near the equator and other vegetation regions. In contrast, in the intensity map of our retrieval results, high-intensity levels of blue SIF can be observed near the equator, which is particularly noticeable in Southeast Asia.  
Figure 7: Scatter plot and goodness-of-fit (R), Pearson correlation coefficient (P) of 2019 annual SIF products with GPP and VI at 2\({}^{\circ}\) spatial resolution.  
At a 2\({}^{\circ}\) spatial resolution, the SIF products were normalized for illumination to enable comparison with the EVI intensity maps. It is noteworthy that, although the goodness-of-fit (GOF) between the Caltech SIF and EVI is higher at this resolution, our retrieval results show a higher correlation with the EVI maps and a stronger ability to distinguish between different land features. This will be detailed in conjunction with Figure 9.  
Figure 10 presents intensity maps of SIF and EVI for some typical regions. Considering the absence of scenes in the intensity map of EVI for 2\({}^{\circ}\) grid cells due to the selection of uniform land surfaces, we compare it with the intensity map of EVI for 0.1\({}^{\circ}\) grid cells.  
Figure 8: Intensity distribution of the two 2019 annual mean SIF products and 2019 annual mean EVI, GPP in 0.1\({}^{\circ}\) grid units. To facilitate observation, morphological dilation was applied to the SIF intensity distribution images.  
Figure 9: Intensity distribution of the two 2019 annual solar-normalized SIF products and annual mean EVI, GPP in 2\({}^{\circ}\) grid units.  
Clear boundaries exist between tropical rainforests, farmland, and bare mountains in South America, which can be observed distinctly in the intensity map of the retrieval results but relatively fuzzily in the Caltech SIF map. Both SIF products can distinguish high-vegetation areas in the southeastern United States from low-vegetation areas, but the color matching between our retrieval results and the EVI map is significantly higher. Most regions in Europe have high vegetation abundance, while the Iberian Peninsula is relatively barren. In contrast to the retrieval results, the differences between these two regions are not obvious in the intensity image of Caltech SIF. The color differences in the intensity map of the retrieval results for different vegetation types (tropical rainforest, grassland, desert) in Africa are more pronounced, achieving better differentiation of these terrains. The comparison with EVI in these regions reflects the stronger resolution capability of our retrieval results for different land surface types.