Relationship between Lidar-Derived Canopy Densities and the Scattering Phase Center of High-Resolution TanDEM-X Data

天蓬 每年落叶的 激光雷达 遥感 树冠 环境科学 森林结构 叶面积指数 合成孔径雷达 植被(病理学) 雷达 大气科学 地理 地质学 生态学 计算机科学 医学 电信 生物 病理 考古
作者
Jonas Ziemer,Clémence Dubois,Christian Thiel,José–Luis Bueso–Bello,Paola Rizzoli,Christiane Schmullius
出处
期刊:Remote Sensing [Multidisciplinary Digital Publishing Institute]
卷期号:15 (14): 3589-3589 被引量:1
标识
DOI:10.3390/rs15143589
摘要

The estimation of forestry parameters is essential to understanding the three-dimensional structure of forests. In this respect, the potential of X-band synthetic aperture radar (SAR) has been recognized for years. Many studies have been conducted on deriving tree heights with SAR data, but few have paid attention to the effects of the canopy structure. Canopy density plays an important role since it provides information about the vertical distribution of dominant scatterers in the forest. In this study, the position of the scattering phase center (SPC) of interferometric X-band SAR data is investigated with regard to the densest vegetation layer in a deciduous and coniferous forest in Germany by applying a canopy density index from high-resolution airborne laser scanning data. Two different methods defining the densest layer are introduced and compared with the position of the TanDEM-X SPC. The results indicate that the position of the SPC often coincides with the densest layer, with mean differences ranging from −1.6 m to +0.7 m in the deciduous forest and +1.9 m in the coniferous forest. Regarding relative tree heights, the SAR signal on average penetrates up to 15% (3.4 m) of the average tree height in the coniferous forest. In the deciduous forest, the difference increases to 18% (6.2 m) during summer and 24% (8.2 m) during winter. These findings highlight the importance of considering not only tree height but also canopy density when delineating SAR-based forest heights. The vertical structure of the canopy influences the position of the SPC, and incorporating canopy density can improve the accuracy of SAR-derived forest height estimations.

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