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根据研究区单木生物量模型及森林资源清查资料计算样地生物量,采用试验精度较高的遥感模型进行4期遥感数据的森林生物量估算,获得区域单位面积生物量变化值,并利用bootstrap方法对引起这种变化的气象因素、森林经营活动因素和社会经济因素等驱动因子进行变量筛选,利用偏最小二乘算法建立不同时间段的森林生物量变化驱动模型,计算变量投影重要性指标(VIP)定量刻画各因素对森林生物量变化的影响重要程度.结果表明:目前人为因素对长白山林区森林生物量变化的影响程度(VIP值)已经小于自然因素,说明国家对林区的森林保护政策已经起到了明显的效果.本文拓宽了森林生物量变化驱动分析的内容,引入了VIP值对森林生物量的变化驱动因子进行定量刻画,为定量分析森林生物量的变化提供了一条新的途径.
Based on the single-tree biomass model and forest inventory data of the study area, the biomass of the plot was calculated, and the remote sensing model with high accuracy was used to estimate the forest biomass of the four-phase remote sensing data to obtain the change of biomass per unit area. The bootstrap Methods The variables of meteorological factors, forest management activities and socioeconomic factors that caused such changes were screened by using partial least squares method to establish the driving model of forest biomass change in different time periods, and to calculate the importance projection of variable projection VIP) to quantitatively describe the importance of various factors on the changes of forest biomass.The results show that the influence degree of human factors on the forest biomass change (VIP value) in Changbai Mountain is less than the natural factors, indicating that the national forest protection The policy has played a significant effect.This paper broadens the driving analysis of forest biomass change, introduces the value of VIP to quantitatively describe the change drivers of forest biomass, and provides a new way for quantitative analysis of forest biomass change .