Underlying topography and forest height estimation from SAR tomography based on a nonparametric spectrum estimation method with low sidelobes

Wang, Youjun; Peng, Xing; Xie, Qinghua; Li, Xinwu; Luo, Xu; Du, Yanan; Zhang, Bing

doi:10.1080/17538947.2022.2153939

Cited by 3 publications

(1 citation statement)

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“…In fact, the vertical profile of the forest volume is complex, and it is difficult to express in terms of a definite function. In view of this, tomographic SAR (TomoSAR) has been used to estimate the vertical profile without depending on a scattering model [11,[21][22][23][24]. However, TomoSAR requires a large number of SAR images characterized by uniformly distributed baselines.…”

Section: Introductionmentioning

confidence: 99%

A Fourier–Legendre Polynomial Forest Height Inversion Model Based on a Single-Baseline Configuration

Zhang,

Zhu,

et al. 2023

Forests

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In this article, we propose a Fourier–Legendre (FL) polynomial forest height estimation algorithm based on low-frequency single-baseline polarimetric interferometric synthetic aperture radar (PolInSAR) data. The algorithm can obtain forest height with a single-baseline PolInSAR configuration while capturing a high-resolution vertical profile for the forest volume. This is based on the consideration that the forest height remains constant within neighboring pixels. Meanwhile, we also assume that the coefficients of the FL polynomials remain unchanged within neighboring pixels, except for the last polynomial coefficient. The idea of using neighboring pixels to increase the observations provides us with the possibility to obtain high-order FL polynomials. With this approach, it is possible to obtain a high-resolution vertical profile that is suitable for forest height estimation without losing too much spatial resolution. P-band PolInSAR data acquired in Mabounie in Gabon and Krycklan in Sweden were selected for testing the proposed algorithm. The results show that the algorithm outperforms the random volume over ground (RVoG) model by 18% and 16.7% in forest height estimation for the Mabounie and Krycklan study sites, respectively.

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