Ji Yongjie, Huang Jimao, Ju Yilin, Guo Shipeng, Yue Cairong
Southwest Forestry University, School of Geography and Ecotourism, Kunming, Yunnan, China.
Southwest Forestry University, Forestry College, Kunming, Yunnan, China.
PeerJ. 2020 Sep 30;8:e10055. doi: 10.7717/peerj.10055. eCollection 2020.
Forest structure plays an important role in forest biomass inversion using synthetic aperture radar (SAR) backscatter. Synthetic aperture radar (SAR) sensors with long-wavelength have the potentiality to provide reliable and timely forest biomass inversion for their ability of deep penetration into the forest. L-band SAR backscatter shows useful for forest above-ground biomass (AGB) estimation. However, the way that forest structure mediating the biomass-backscatter affects the improvement of the related biomass estimation accuracy. In this paper, we have investigated L-band SAR backscatter sensitivity to forests with different mean canopy density, mean tree height and mean DBH (diameter at breast height) at the sub-compartment level. The forest species effects on their relationship were also considered in this study. The linear correlation coefficient R, non-linear correlation parameter, Maximal Information Coefficient (MIC), and the determination coefficient R from linear function, Logarithmic function and Quadratic function were used in this study to analyze forest structural properties effects on L-band SAR backscatter. The HV channel, which is more sensitive than HH to forest structure parameters, was chosen as the representative of SAR backscatter. 6037 sub-compartment were involved in the analysis. Canopy density showed a great influence on L-band backscatter than mean forest height and DBH. All of the R between canopy density and L-band backscatter were greater than 0.7 during the forest growth cycle. The sensitivity of L-band backscatter to mean forest height depends on forest canopy density. When canopy density was lower than 0.4, R values between mean forest height are smaller than 0.5. In contrast, the values of R were greater than 0.8 if canopy density was higher than 0.4. The sensitivity SAR backscatter to DBH fluctuated with canopy density, but it only showed obvious sensitivity when canopy density equals to 0.6, where both the linear and non-liner correlation values are higher than others. However, their effects on L-bang HV backscatter are affected by forest species, the effects on three forest structural parameters depend on tree species.
森林结构在利用合成孔径雷达（SAR）后向散射进行森林生物量反演中起着重要作用。长波长的合成孔径雷达（SAR）传感器因其能够深入穿透森林的能力，具有提供可靠且及时的森林生物量反演的潜力。L波段SAR后向散射对于森林地上生物量（AGB）估计很有用。然而，森林结构介导生物量与后向散射的方式影响了相关生物量估计精度的提高。在本文中，我们在亚林班水平上研究了L波段SAR后向散射对具有不同平均树冠密度、平均树高和平均胸径（胸高处直径）的森林的敏感性。本研究还考虑了森林物种对它们关系的影响。本研究使用线性相关系数R、非线性相关参数、最大信息系数（MIC）以及线性函数、对数函数和二次函数的决定系数R来分析森林结构特性对L波段SAR后向散射的影响。选择对森林结构参数比HH通道更敏感的HV通道作为SAR后向散射的代表。分析涉及6037个亚林班。树冠密度对L波段后向散射的影响比平均林高和胸径更大。在森林生长周期中，树冠密度与L波段后向散射之间的所有R值均大于0.7。L波段后向散射对平均林高的敏感性取决于森林树冠密度。当树冠密度低于0.4时，平均林高之间的R值小于0.5。相比之下，如果树冠密度高于0.4，R值大于0.8。SAR后向散射对胸径的敏感性随树冠密度波动，但仅在树冠密度等于0.6时表现出明显的敏感性，此时线性和非线性相关值均高于其他情况。然而，它们对L波段HV后向散射的影响受森林物种影响，对三个森林结构参数的影响取决于树种。
