A multi-baseline PolInSAR forest height inversion method taking into account the ground scattering effects and parametric linear

被引：0
|
作者：
Lin D. [1 ,2 ]
Zhu J. [3 ]
Li Z. [3 ]
Fu H. [3 ]
Liang J. [1 ]
Zhou F. [4 ]
Zhang B. [5 ]
机构：
[1] Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan
[2] School of Geodesy and Geomatics, Wuhan University, Wuhan
[3] School of Geosciences and Info-Physics, Central South University, Changsha
[4] Changsha University of Science and Technology, Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway, Changsha
[5] School of Geomatics, Liaoning Technical University, Fuxin
来源：
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2023年 / 52卷 / 01期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
GVR; ill-posed problem; multi-baseline; PolInSAR; vegetation height;
D O I：
10.11947/j.AGCS.2023.20200581
中图分类号：
学科分类号：
摘要：
Affected by the insufficient information of single baseline observation data, the three-stage method assume the ground-to-volume ratio (GVR) to be zero so as to invert the vegetation height. However, this assumption introduces much biases into the parameter estimates which greatly limit the accuracy of the vegetation height inversion. Multi-baseline observation can provide redundant information and is helpful for the inversion of GVR. Nevertheless, there are many geometry parameters that share similar values in a multi-baseline model, which lead to ill-posed problems and reduce the inversion accuracy of conventional algorithm. To this end, we propose a new step-by-step inversion method applied to the multi-baseline observations. Firstly, an adjustment inversion model is constructed by using multi-baseline volume scattering dominant polarization data, and the regularized estimates of model parameters are obtained by regularization method. Then, the reliable estimates of GVR is determined by the mean square error (MSE) analysis of each regularized parameter estimation. Secondly, using the estimated GVR extracts the pure volume coherence, and then inverting the vegetation heights from the pure volume coherences by least squares estimation. The experimental results show that the new method can improve the vegetation height inversion result effectively. The inversion accuracy is improved by 26% with respect to three-stage method and the conventional solution of multi-baseline. The results have demonstrated the feasibility and effectiveness of the new method. © 2023 SinoMaps Press. All rights reserved.
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页码：51 / 60
页数：9
相关论文
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