Time-frequency InSAR forest height inversion method that considers the geometric distribution of the sub-look coherent set

HOU Jiali; SHEN Peng; ZHANG Lu; WU Chuanjun; TAN Pengyuan

doi:10.11834/jrs.20265347

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Time-frequency InSAR forest height inversion method that considers the geometric distribution of the sub-look coherent set
Vol. 30, Issue 4, Pages: 943-956(2026)
Received：12 September 2025，

Published：07 April 2026
DOI： 10.11834/jrs.20265347
稿件说明：

移动端阅览

侯佳丽，沈鹏，张路，吴传军，谭鹏源.2026.顾及子视相干集几何分布的时频InSAR森林高度反演方法.遥感学报，30（4）： 943-956 DOI： 10.11834/jrs.20265347.

Hou J L，Shen P，Zhang L，Wu C J and Tan P Y. 2026. Time-frequency InSAR forest height inversion method that considers the geometric distribution of the sub-look coherent set. National Remote Sensing Bulletin， 30（4）：943-956 DOI： 10.11834/jrs.20265347.

摘要

森林高度是表征森林垂直结构的重要参数，对于森林资源管理、碳循环及气候变化等研究具有重要意义。传统森林高度反演方法基于时间频率TF（Time Frequency）分析的雷达干涉测量InSAR（Interferometric Synthetic Aperture Radar）技术采用子视随机地体散射RVoG（Random Volume over Ground）模型，难以准确提取用于描述子视复相干系数几何分布的特征点，导致森林高度反演精度低。为此，本文提出了一种顾及子视相干集几何分布的时频InSAR森林高度反演方法。首先通过子孔径分解构建多孔径干涉相干矩阵，其次提出子视相干集概念并分析其几何轮廓分布特性，在此基础上利用相干集长轴获取更接近纯体去相干的复数观测和地表相位，最后采用固定消光系数法实现森林高度产品反演。采用欧洲航天局2016年在非洲加蓬共和国通过AfriSAR机载任务获取的全极化P波段SAR数据进行实验，实验区域覆盖Mabounie地区，验证数据采用全波形激光雷达LVIS（Land Vegetation and Ice Sensor）获取的LiDAR数据。实验结果表明，在40 m×40 m样地尺度下，本文单极化TF分析方法的森林高度估计精度（RMSE=8.54 m）比传统方法（RMSE=10.22 m）改善了34.44%，可达到与全极化方法相近的森林高度估计精度，可为大范围、低成本的森林监测应用提供可靠的技术途径。

Abstract

Forest height is a crucial parameter of the forest vertical structure and plays a notable role in forest resource management

carbon cycle research

and climate change studies. Traditional Time-Frequency (TF) analysis-based Interferometric Synthetic Aperture Radar (TF-InSAR) techniques employ the random volume over ground model with a limited number of discrete sub-look complex coherence observations. However

given the reliance on limited observations

these methods often struggle to acquire the characteristic points used to describe the geometric distribution of sub-look complex coherence coefficients

resulting in low accuracy in forest height inversion. To address this issue

this study proposes a TF-InSAR forest height inversion method that incorporates the geometric distribution of the sub-look coherence set. First

a multi-aperture interferometric coherence matrix is constructed through sub-aperture decomposition. Second

the concept of a sub-look coherence set is introduced

and its geometric characteristics are analyzed. On this basis

the major axis of the coherence set is utilized to obtain complex observations and a surface phase that are close to pure-volume decorrelation. Finally

the forest height product is generated using a fixed extinction coefficient inversion approach. The experimental data are acquired from the airborne fully polarimetric P-band SAR data obtained during the AfriSAR campaign conducted by the European Space Agency in Gabon

Africa

in 2016

covering the Mabounie test site. Validation is performed using full-waveform LiDAR data from the Land Vegetation and Ice Sensor. Experimental results indicate that at the 40 m×40 m plot scale

the forest height estimation accuracy achieved by the proposed single-polarization TF analysis method (root mean square error RMSE=6.70 m) shows a 34.44% improvement over the conventional method (RMSE=10.22 m). Conclusion Using only single-polarization SAR data

the proposed TF-based analysis method can achieve a forest height estimation accuracy comparable to that of full polarimetric data-based methods (RMSE=8.54 m)

providing a reliable and cost-effective technical solution for large-scale forest monitoring.

关键词

Keywords

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