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Comparison of Aboveground Biomass Estimation From InSAR and LiDAR Canopy Height Models in Tropical Forests
IEEE Geoscience and Remote Sensing Letters ( IF 4.8 ) Pub Date : 2020-03-01 , DOI: 10.1109/lgrs.2019.2925901
Michael Schlund , Stefan Erasmi , Klaus Scipal

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.

中文翻译:

热带森林中 InSAR 和 LiDAR 冠层高度模型的地上生物量估计的比较

TanDEM-X 的干涉合成孔径雷达 (InSAR) 高度对植被冠层高度和地上生物量 (AGB) 估计的潜力早已得到认可。X 波段进入冠层会影响这些估计。因此,来自 InSAR 的冠层高度和 AGB 检索通常是有偏差的,不能直接与其他数据源的估计值进行比较。这封信的目的是应用穿透深度模型来补偿 TanDEM-X InSAR 高度中的高度偏差。随后使用回归模型将所得的冠层高度估计值转换为 AGB 估计值。由于信号渗透到树冠中,森林树冠的未校正 InSAR 高度存在偏差,并且与光探测和测距 (LiDAR) 树冠高度估计值大不相同。穿透深度补偿的应用导致无偏森林冠层高度估计和 AGB 回归模型在 InSAR 和 LiDAR 之间具有可比性。这些结果表明,TanDEM-X InSAR 和 LiDAR 技术可用于估计复杂热带森林中的 AGB,这表明可以协同使用这些根本不同的观测概念。
更新日期:2020-03-01
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