## 3 Results
### Variability of NDVI, EVI, and SIF in Driving Factors  
#### 3.2.1 Effects of Air Temperature, Precipitation, and Relative Humidity on NDVI, EVI, and SIF  
Figure 5 presents the temporal changes in China's air temperature, precipitation, and relative humidity from 2000 to 2019. Air temperature, precipitation, and relative humidity all exhibit increasing trends, with the most pronounced increase observed in relative humidity, which also implies increasing warming in China. In 2005, the three vegetation remote sensing products showed a decreasing trend (Figure 2); air temperature decreased, while precipitation and relative humidity increased. In 2010, the three vegetation remote sensing products exhibited a decreasing trend; air temperature and relative humidity decreased, and precipitation increased. In 2015, the three vegetation remote sensing products showed an increasing trend; air temperature, precipitation, and relative humidity all displayed increasing trends. When vegetation cover changes, transpiration changes and the way in which the leaf stomata close and open changes, which in turn, leads to alterations in vegetation foliar temperature. Air temperature is susceptible to this thermal response, resulting in a positive correlation between air temperature and vegetation over time. Both excessive and insufficient precipitation and relative humidity affect vegetation cover changes, resulting in a difference in their temporal correlation with vegetation. This observation suggests that a combination of meteorological factors drives changes in vegetation cover. Figure 6 displays the spatial distribution of air temperature, precipitation, and relative humidity. Air temperature, precipitation, and relative humidity show an increasing trend from northwest to southeast. Their spatial distributions exhibit a high degree of similarity with those of the three vegetation remote sensing products. The spatial distribution of air temperature (Figure 6A) is higher in some parts of northwest China, which is inconsistent with our discussion on how air temperature and vegetation remote sensing products have a specific positive temporal correlation. Although air temperature and the three vegetation remote sensing products positively correlate with material changes, some parts of northwest China are plateau and Gobi Desert areas. The combined effect of low precipitation and relative humidity causes air temperature and the three vegetation remote sensing products to show some negative correlation. This phenomenon further indicates that vegetation cover change is driven by multiple meteorological factors rather than a single driver. Figure 5: Interannual timeline chart of average air temperature, precipitation, and relative humidity. (**A**): Time variation of temperature; (**B**): Time variation of precipitation; (**C**): Time variation of relative humidity. Figure 7 illustrates the spatial correlations of the three vegetation remote sensing products with air temperature, precipitation, and relative humidity. The NDVI, EVI, and SIF values display positive spatial correlations with air temperature, precipitation, and relative humidity, and negative temporal correlations with relative humidity (Table 1). The spatial correlation coefficients between the SIF and air temperature are more consistent with the spatial distribution of the SIF (Figure 3C), while the spatial correlation coefficients between the NDVI and EVI are more consistent with the spatial distribution of precipitation and relative humidity (Figure 3A,B). However, the spatial correlation coefficients of the SIF and precipitation (Table 1) are more significant than those of the NDVI and EVI. The NDVI, EVI, and SIF show negative correlations with air temperature in many areas in Figure 7A-C, such as the northern Inner Mongolia desert region and some Gobi Desert lands in the northwest. This area is primarily in the plateau zone and has low precipitation and relative humidity.