观测信息不足条件下TanDEM-X InSAR的大范围林下地形反演

doi:10.11947/j.AGCS.2024.20230004

测绘学报 ›› 2024, Vol. 53 ›› Issue (5): 959-966.doi: 10.11947/j.AGCS.2024.20230004

观测信息不足条件下TanDEM-X InSAR的大范围林下地形反演

朱珺¹^,²(), 彭葳¹(), 付海强³, 欧蔓³, 雷缮诚¹, 张石平²

^1.长沙理工大学交通运输工程学院，湖南　长沙　410114
^2.湘江实验室，湖南　长沙　410205
^3.中南大学地球科学与信息物理学院，湖南　长沙　410083

收稿日期:2023-01-04 修回日期:2024-04-19 发布日期:2024-06-19
通讯作者: 彭葳 E-mail:jzhu@csust.edu.cn;pengwei@csust.edu.cn
作者简介:朱珺（1986—），男，博士，讲师，研究方向为卫星大地测量。E-mail：jzhu@csust.edu.cn
基金资助:
湘江实验室重大项目/开放基金(22XJ01009);国家自然科学基金(42330717);湖南省自然科学基金(2022JJ40472)

Large-scale TanDEM-X InSAR sub-canopy topography inversion under insufficient observation information

Jun ZHU¹^,²(), Wei PENG¹(), Haiqiang FU³, Man OU³, Shancheng LEI¹, Shiping ZHANG²

^1.Changsha University of Science & Technology, Changsha 410114, China
^2.Xiangjiang Laboratory, Changsha 410205, China
^3.Central South University, Changsha 410083, China

Received:2023-01-04 Revised:2024-04-19 Published:2024-06-19
Contact: Wei PENG E-mail:jzhu@csust.edu.cn;pengwei@csust.edu.cn
About author:ZHU Jun (1986—), male, PhD, lecturer, majors in satellite geodesy. E-mail: jzhu@csust.edu.cn
Supported by:
Major Program/Open Project of Xiangjiang Laboratory(22XJ01009);The National Natural Science Foundation of China(42330717);The Natural Science Foundation of Hunan Province(2022JJ40472)

摘要/Abstract

摘要：

TerraSAR/TanDEM-X InSAR双站卫星系统是目前最主要的全球测图卫星系统之一，但该系统主要获取单基线、单极化InSAR数据。受观测信息不足的限制，无法直接分离植被体散射与地表散射信息，难以获取高精度的森林高度和林下地形。鉴于此，本文提出了联合单/双基线的大范围林下地形反演方法，其核心思想为：在InSAR干涉对重叠区，每个干涉对有不同的基线，两个干涉对重叠相当于双基线观测，可以采用RVoG模型估计森林高度。然后，利用简化的RVoG模型（C-SINC模型），以重叠区反演的树高结果为已知值，通过假定不同树高的散射过程具有相似性，对C-SINC模型进行求解进而获取林下地形。最后，以西班牙Teruel试验区对本文方法进行验证，与LiDAR DEM进行精度对比，InSAR DEM的RMSE为7.43 m，本文方法获取的林下地形RMSE为5.98 m，精度提高了20%。本文方法为利用TanDEM-X实现大范围林下地形测绘提供了参考。

关键词: 林下地形, 单/双基线InSAR, 大范围地形反演, 干涉对

Abstract:

The TerraSAR/TanDEM-X InSAR system is currently one of the most important global mapping satellite systems, the data acquired by this system is mainly single-baseline, single-polarized SAR data. Restricted by insufficient observation information, vegetation, and surface scattering information cannot be directly separated from the data, which makes it hard to apply the system to the large-scale, high-precision inversion of terrain under forest. Therefore, this article proposes a method for large-scale terrain inversion under forest using single/dual baseline observations. The core concept of this method is as follows: for overlapping zones (dual baseline observation), the RVoG model is used to estimate the terrain under forest and the forest height; for non-overlapping zones (single baseline observation), with the estimated tree height of the overlapping zone as the prior information, a simplified RVoG model (C-SINC) is used to estimate the terrain under forest. The new method was analyzed and verified in the Teruel experimental zone of Spain. Comparing the results with LiDAR DEM, the RMSE of sub-canopy topography acquired by this method is 5.98 m, which is 20% higher in precision than the RMSE of 7.43 m obtained by InSAR DEM. For large-scale areas, the new method provides a reference for the application of TanDEM-X to estimate the sub-canopy Topography.

Key words: sub-canopy topography, single/dual baseline InSAR, large-scale topography inversion, interferometric pairs

中图分类号:

P237

朱珺, 彭葳, 付海强, 欧蔓, 雷缮诚, 张石平. 观测信息不足条件下TanDEM-X InSAR的大范围林下地形反演[J]. 测绘学报, 2024, 53(5): 959-966.

Jun ZHU, Wei PENG, Haiqiang FU, Man OU, Shancheng LEI, Shiping ZHANG. Large-scale TanDEM-X InSAR sub-canopy topography inversion under insufficient observation information[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(5): 959-966.

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参考文献 26

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影像获取日期	数据编号	入射角/(°)	垂直基线/m	垂直有效波数/(rad/m)	高程模糊度/m
2012-10-23	1	33.09	181.9	0.19	33
2012-10-23	2	33.09	181.5	0.19	33
2011-12-20	3	36.12	104.9	0.11	57
2011-12-20	4	36.12	105.0	0.11	57

观测信息不足条件下TanDEM-X InSAR的大范围林下地形反演

Large-scale TanDEM-X InSAR sub-canopy topography inversion under insufficient observation information

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数据	所有区域	重叠区	非重叠区
InSAR DEM	7.43	7.31	7.64
林下地形	5.98	5.72	6.09