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Comparison of Aboveground Biomass Estimation From InSAR and LiDAR Canopy Height Models in Tropical Forests

机译:热带森林中insar和激光裙冠层高度模型的地上生物量估计比较

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摘要

The potential of interferometric synthetic aperture radar (InSAR) heights from TanDEM-X for vegetation canopy height and aboveground biomass (AGB) estimation has long been recognized. Penetration of X-band into the canopy affects these estimations. Thus, the canopy height and AGB retrieval from InSAR are typically biased and cannot be compared directly to estimates from other data sources. The objective of this letter was to apply a penetration depth model to compensate for height biases in TanDEM-X InSAR heights. The resulting canopy height estimates are subsequently converted to AGB estimates using regression models. The uncorrected InSAR heights of the forest canopy are biased due to the penetration of the signal into the canopy and differ substantially to light detection and ranging (LiDAR) canopy height estimates. The application of the penetration depth compensation results in unbiased forest canopy height estimates and AGB regression models that are comparable between InSAR and LiDAR. These results indicate that TanDEM-X InSAR and LiDAR technologies can be used to estimate AGB in complex tropical forests suggesting a synergistic use of these fundamentally different observation concepts.
机译:从植被冠层高度和地上生物量(AGB)估计的Tandem-X的干涉性合成孔径雷达(Insar)高度的电位已经得到了认可。 X波段进入顶篷的渗透会影响这些估计。因此,从insar的冠层高度和AGB检索通常偏置,不能直接比较以与其他数据源的估计进行比较。这封信的目的是应用渗透深度模型来补偿串联X Insar高度的高度偏差。随后使用回归模型将所产生的冠层高度估计转换为AGB估计。由于信号进入树冠的渗透,并且基本上与光检测和测距(LIDAR)冠层高度估计不同,因此森林树冠的未矫正突出的高度被偏置。渗透深度补偿的应用导致无偏的森林冠层高度估计和Insar和LIDAR之间的AGB回归模型。这些结果表明,Tandem-x Insar和LIDAR技术可用于估计复杂的热带森林中的AGB,表明这些从根本上不同的观察概念的协同使用。

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