High-resolution sub-canopy topography mapping via TanDEM-X DEM combined with future P-band BIOMASS PolInSAR data

被引:2
作者
Zhu, Jianjun [1 ]
Liu, Zhiwei [1 ]
Fu, Haiqiang [1 ]
Zhou, Cui [2 ]
Zhou, Yi [1 ]
Wang, Huiqiang [3 ]
Xie, Yanzhou [1 ]
机构
[1] Cent South Univ, Sch Geosci & Info Phys, Changsha 410083, Hunan, Peoples R China
[2] Cent South Univ Forestry & Technol, Coll Sci, Changsha 410004, Peoples R China
[3] Inner Mongolia Agr Univ, Coll Water Conservancy & Civil Engn, Hohhot 010018, Peoples R China
基金
中国国家自然科学基金;
关键词
Sub-canopy topography; TanDEM-X; BIOMASS; InSAR; PolInSAR; APERTURE RADAR INTERFEROMETRY; SRTM DEM; POL-INSAR; SAR DATA; ABOVEGROUND BIOMASS; BASE-LINE; TOMOGRAPHY; MODEL; DECOMPOSITION; PERFORMANCE;
D O I
10.1007/s00190-023-01807-0
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Precise DEMs at high spatial resolution are indispensable for a variety of scientific studies and applications. Presently, the TanDEM-X mission possesses the capability to collect global-scale InSAR data at high spatial resolution, enabling the generation of a high-resolution global DEM (12 m). Nevertheless, directly utilizing InSAR data poses challenges in detecting sub-canopy topography within forest areas, due to the presence of volume scattering and limited penetration of X-band. Conversely, the upcoming BIOMASS mission operated in P-band will provide an exceptional opportunity for sub-canopy topography extraction, owing to its strong penetration and the capability to collect fully-polarimetric SAR data. However, it is imperative to acknowledge that BIOMASS data do have its own limitation, manifesting as lower resolution (100 m) due to limited bandwidth. To address these challenges and generate high-resolution sub-canopy topography, we propose a new method that leverages the strengths of both TanDEM-X InSAR and BIOMASS PolInSAR datasets through the wavelet transform. We evaluated the performance of our method at two test sites characterized by different forest types and terrain conditions using airborne LiDAR data. Our findings demonstrate a significant improvement in sub-canopy topography accuracy. Specifically, under the boreal coniferous forest scenario, the root mean square error (RMSE) of the resulting sub-canopy topography decreased by 44% compared to the TanDEM-X InSAR DEM. In tropical broadleaf forest scenario, the RMSE reduction reached 64% over the TanDEM-X InSAR DEM. These results indicate the potential of our approach for high-resolution sub-canopy topography mapping by combing data from these two different spaceborne SAR sensors.
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页数:21
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