Analysis of the vegetation cover chang and its relationship with factors in the Three-North Shelter Forest Program
The Shelter Forest System Program (TNSEP) in Three-North Region of China is the largest ecological reforestation program in the world. The TNSFP vegetation research not only has important ecological environment meaning, but also attaches profound social and economic significance. Spatio-temporal variation of the vegetation coverage and its relationship with major climatic factors (temperature and precipitation) in TNSFP was explored by using GIMMS/NDVI dataset at 8km spatial resolution and climatic data during the period from 1982 to 2006. The results show that: 1) vegetation cover had an entirely rising trend during the past 25 years, the increasing rate of vegetation variation was slightly higher than reducing rate, I and IV NDVI increased most significantly P<0.001), while II showed a slight downward trend. Moreover, the vegetation coverage of four construction regions has been improved in different degree. 2) Vegetation cover, temperature and precipitation overall were positively correlated on the study area. The temperature and vegetation cover was negatively correlated in 17.74% of the region, but 6.84% of the region was a positive correlation. The precipitation was negatively correlated with vegetation cover in 10.60% of the region while 19.53% of the region was a positive correlation. Vegetation associated with the precipitation was significantly larger than the area related to temperature, precipitation was the key to factor vegetation growth on the study area. 3)lnter-annual residuals of vegetation variation showed a significant positive correlation area which was greater than the area of a significant negative correlation area, and the role of human construction on vegetation was stronger than the destructive role. Therefore, the positive impact of TNSFP ecological construction was showing.
Three-North Shelter Forest ProgramNDVIvegetation coverclimate factor, human activitycorrelation analysis
NETL
NSTL
万方数据
维普
