长白山林区森林生物量变化定量驱动分析

In this paper，forest biomasses of plots were calculated according to single tree biomass model and forest inventory data. The regional forest biomass were estimated from four period remote sensing data by using higher experimental accuracy remote sensing models and the forest biomass change data of the corresponding period obtained from the image of forest biomass. Using bootstrap method, the driving factors such as meteorological data, business activity data and socio-economic data which caused forest biomass changes were selected. Meanwhile, the driving model of the forest biomass change was set up using partial last-squares method for different periods. And the VIP values were calculated which represented the impact of each factor on the forest biomass change in the study region. The results shows that the influence of human activity factors (VIP values) on Changbai Mountain forest biomass changes is less than that of the natural factors suggesting the national protection policy to forests had played an obvious role. Our research broadened the content of the forest biomass change driving analysis, and the method of calculating VIP value which quantitative represented the influence of driving factors to the forest biomass change provided a new way for the quantitative analysis on forest biomass change.