# The Ongoing Greening in Southwest China despite Severe Droughts and Drying Trends
## 3 Results
### The Impact of Land Management on Vegetation in SWC  
Since 2000, SWC has experienced highly obvious agricultural intensive production (Figure 8); this was mainly manifested in the massive use of pesticides and fertilizers and the rapid increase in the total power of agricultural machinery, which increased by 22%, 33%, and 154% from 2001 to 2019, respectively. At the same time, the sown area, crop yield, and crop output value increased by 11%, 16%, and 345% from 2006 to 2019, respectively. China has been implementing several ambitious plans in recent years to protect and expand forests and reduce soil erosion. It can also be clearly seen from the relevant statistical data that since 2004, the annual afforestation area in the SWC was between 0.5 and 2.5 million \(\mathrm{h}\mathrm{m}^{2}\), most of which were artificial forests. During the 15 years from 2004 to 2019, the forest area in SWC increased by nearly 1000 \(\mathrm{h}\mathrm{m}^{2}\).  
In order to reduce the uncertainty caused by statistical data, RESDC was used to describe land-use changes in SWC. From 1980 to 2015, the land use of the entire study area was mainly divided into two stages (Figure 9). Before 2000, the main manifestations were the decrease in cropland and forest and the increase of grassland. Cropland and forest decreased by 1274 \(\mathrm{k}\mathrm{m}^{2}\) and 2376 \(\mathrm{k}\mathrm{m}^{2}\), respectively, and grassland increased by 3102 \(\mathrm{k}\mathrm{m}^{2}\). From a spatial perspective, the increase in grassland was largely due to the decrease in forest. After 2000, forests increased, cropland and grassland decreased, cropland decreased by 6211 \(\mathrm{k}\mathrm{m}^{2}\), grassland decreased by 2099 \(\mathrm{k}\mathrm{m}^{2}\), forest increased by 1017 \(\mathrm{k}\mathrm{m}^{2}\), and forest expansion mainly came from cropland and grassland. Although the area of cropland decreased significantly after 2000, the sown area of croplands showed an increasing trend, which may be due to the impact of multiple cropping [25].  
Figure 7: The spatial change trend of LAI, EVI, and GPP in SWC. (**a1–a4**), (**b1–b4**), and (**c1–c4**) represent the spatial change trend of LAI, EVI, and GPP, respectively; (**a1,b1,c1**) are LTT, (**a2,b2,c2**) are the difference between LTT and BDT; (**a3,b3,c3**) are the difference between LTT and ADT, and (**a4,b4,c4**) are the difference between ADT and BDT.  
In addition, we also identified the impact of human activities through the residual trend method (Figure 10). Be it for LAI, EVI, or GPP, there were positive trends in SWC, and positive pixel values accounted for 27%, 37%, and 19% of the entire study area, respectively, which indicates that the impact of human activities on vegetation in the entire study area is very significant, and the impact of human activities may be even greater than 10%.  
Figure 8: Agricultural and forestry changes in SWC. (**a–f**) are agricultural changes, which are crop sown area, crop yield, crop output value, pesticide use, fertilizer use, total power of agricultural machinery, (**g-i**) are forestry changes, which are total afforestation area, artificial afforestation area, and forest area, respectively.  
Figure 9: Land-use change in SWC, (**a–a3**) is land use change from 1980 to 2000, (**b1–b3**) is land use change from 2000 to 2015. (**a1,b1**) are cropland, (**a2,b2**) are forest, and (**a3,b3**) are grassland.  
after 2000 (the number of positive pixels in EVI is significantly more than that in LAI). In summary, be it statistical data, satellite data, or the statistical method, it is recognized that the entire study area has experienced a very wide range of human activities and the positive impact of land management on vegetation.