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基于微波的后向散射系数估计森林地上生物量(AGB)易受后向散射系数饱和的影响,而利用森林高度,根据生长方程估计AGB,却没有考虑和AGB密切相关的林分密度、树种组成、林层垂直分布等空间结构特征的作用,针对这些问题,提出一种基于极化相干层析(Polarization Coherence Tomography,PCT)技术的AGB估计方法。基于德国宇航局(DLR)机载SAR系统(ESAR)获取的特劳斯坦(Traunstein)试验区L-波段极化干涉SAR(PolInSAR)数据,通过对具有不同AGB水平的典型林分的相对反射率函数曲线的分析,定义了9个与AGB具有相关性的特征参数。然后基于20个林分的实测AGB数据,以林分尺度上这9个特征参数的平均值为自变量,以实测林分平均AGB为因变量,采用逐步回归分析法构建了AGB估测模型,并对该模型进行评价,对影响模型估计精度的因素进行分析,结果表明,由PCT提取的相对反射率函数特征参数对AGB很敏感,充分利用相对反射率函数信息可提高AGB估计精度。
Based on the backscattering coefficient of microwaves, it is estimated that above-ground biomass (AGB) is susceptible to the influence of backscatter coefficient saturation. However, using the height of forest and estimating AGB based on growth equation, it does not consider the stand density closely related to AGB, , The vertical distribution of the forest floor and other spatial structural features. In view of these problems, an AGB estimation method based on the Polarization Coherence Tomography (PCT) technique is proposed. Based on the L-band Polarimetric Interference SAR (PollSAR) data from the Traunstein test area acquired by the German Aerospace Agency (DLR) airborne SAR system (ESAR), the relative reflectance of typical stands with different AGB levels The analysis of the function curve defines nine characteristic parameters that are relevant to the AGB. Then based on the measured AGB data of 20 stands, taking the mean of these 9 characteristic parameters as the independent variable in the stand scale and the average AGB of the stand as the dependent variable, the AGB estimation model was constructed by stepwise regression analysis, The model was evaluated and the factors influencing the accuracy of model estimation were analyzed. The results showed that the characteristic parameters of relative reflectance function extracted by PCT were sensitive to AGB, and the relative accuracy of reflectance function could be improved by using the information of relative reflectance function.