## 4 Discussion  
The multiyear change rate of the NDVI in northern China generally decreased from 2000 to 2012 and then increased from 2013 to 2018. It increased in the east and decreased in the west of northern China. This is basically consistent with the NDVI variation for the world [11] and in central Asia [36]. It also conforms to the conclusion that the NDVI in northern Xinjiang Uygul Zizhiqiu [38] has increased on the whole. However, [PERSON] et al. [41] and [PERSON] et al. [48] proposed that the areas where NDVI has increased significantly are primarily located in the Tianshan Mountains, northern Xinjiang Uygul Zizhiqiu, and the Tarim Basin. The areas with a significantly decreased NDVI were shown to be mostly concentrated in the Greater and Lesser Khingan Mountains and in the Changbai Mountains in northeast China, which is somewhat different from the research results in this paper and may be caused by the different research periods. Multivariate correlations between the NDVI, P, and T were generally strong (Mnpmax > Mnpave > Mnpmin). The areas that passed the 95% confidence level in the test of significance accounted for approximately 43.4%, 31.1%, and 28.5% of the total, respectively, which indicates that the joint effect of P and T has an important influence on the growth and distribution of vegetation in the study area. Moreover, the conclusion that the NDVI is closely correlated with P and T, which are dominant contributors to the NDVI [49,50], basically conforms to the results of this study. Some scholars [51] also pointed out that the multiple correlations among NDVI, P, and T are insignificant. This perspective is different from the conclusions of this study to some extent, possibly due to the different study areas. The explanatory power of the synergistic effect between P and Tmin, Tave, and Tmax for the NDVI in the study area was descending (i.e., Qnpmax > Qnpave > Qnpmin on the whole). The Q value was between 0.36 and 0.81. Spatially, the explanatory power of the synergistic effect between P and T for the NDVI was strengthened overall in the study area from northwest to southeast. The conclusion that the explanatory power of P and T for China's NDVI was between 0.76-0.83 and 0.48-0.56, respectively [52], and the conclusion that the main contributors to the spatial distribution of vegetation coverage were P, T, sunshine, and relative humidity in the order of explanatory power [53], all conform to the conclusions of this study to some degree. However, the conclusion [54] that elevation is the major contributor to the NDVI and its explanatory power of roughly 52.9% differ from the results presented in this article, which may be caused by the different time scales or data. The annual change rate for Q decreased in the middle and increased in the east and west of  
Figure 5: Spatial distribution of the synergistic effect between P and T for the NDVI. the study area. The two areas accounted for 10.47% and 89.53% of the total (taking Onpave as an example), which indicates that the synergistic effect between P and T on the NDVI of the study area was generally enhanced. [PERSON] et al. proposed [PERSON] et al. (2018) that, from 2000 to 2020, the impact of natural factors on the NDVI was weakened on the whole, while those of human factors were strengthened. This conclusion is somewhat different from that presented in this article, which may be derived from the inconsistency of the study period. Many scholars have pointed out that anthropogenic factors are also primary factors that affect the growth and distribution of vegetation, and their impact is dual [PERSON] et al. (2018). For example, the construction of the Qinghai-Tibet Railway had a significant impact on the growth of vegetation. That is, the growth of vegetation was improving before the railway was built, a degradation trend appeared during construction, and the growth gradually recovered after the project [PERSON] et al. (2018).