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Research progress on tomographic SAR three-dimensional imaging methods and forest parameter inversion

  • role： First author第一作者
  • Affiliation：

    School of Geosciences and Info-physics, Central South University, Changsha 410083, China

  • Email：wanjie@csu.edu.cn
  • Introduction：万杰，研究方向为层析SAR三维成像算法与应用。E-mail： wanjie@csu.edu.cn
WAN Jie,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geosciences and Info-physics, Central South University, Changsha 410083, China

  • Email：wangchangcheng@csu.edu.cn
  • Introduction：汪长城，研究方向为干涉SAR、极化干涉SAR、层析SAR理论与应用。E-mail： wangchangcheng@csu.edu.cn
WANG Changcheng*,  
  • Affiliation：

    School of Geosciences and Info-physics, Central South University, Changsha 410083, China

ZHU Jianjun,  
  • Affiliation：

    School of Geosciences and Info-physics, Central South University, Changsha 410083, China

FU Haiqiang

реферат

Forests are the largest ecosystems on land and play an important role in the global carbon and oxygen cycle. Synthetic aperture Radar tomography (TomoSAR) has the capability to carry out three-dimensional (3-D) imaging of observation targets and obtain information about forest internal structure, which serves an important function in the inversion of forest parameters. This paper will review the imaging methods and applications of TomoSAR over the past two decades and focus on its latest research progress in forest parameter inversion. More importantly, different parameter inversion methods will be systematically compared, and the challenges in TomoSAR forest parameter inversion will be analyzed.First, the mathematical models of TomoSAR in single-polarization and full-polarization mode were introduced. Then, different TomoSAR imaging algorithms were analyzed in detail. The performances of different methods in terms of vertical resolution, radiation accuracy, computational efficiency, and stability were compared. Next, we summarized the progress of TomoSAR in the inversion of forest parameters, such as underlying topography, forest height, and biomass. Finally, this paper analyzed the key challenges faced in the inversion of forest parameters using TomoSAR and predicted the frontier applications of TomoSAR. The P-band TropiSAR 2009 dataset over a test site in Paracou, French Guiana, were used to analyze the performance of different methods.By reviewing the published literature, the theoretical differences between different TomoSAR imaging algorithms were listed. Experiments showed that the Fourier transform method has limited vertical resolution but high radiation accuracy and has been successfully used for biomass estimation. Beamforming spectral estimation method can improve the vertical resolution, but the image quality is seriously degraded when the number of observations is reduced. Compressed sensing and statistical optimization algorithms have sparse imaging capabilities and super-resolution, enabling the fine-grained identification of forest vertical structures. For the estimation of forest underlying topography and forest height, an accurate estimation of canopy scattering center and ground phase center is an important prerequisite. The addition of polarization information is more conducive to the identification of different scattering mechanisms. In biomass estimation, the application of a 3-D structure can significantly improve the accuracy of inversion.The 3-D structure of forests plays an important role in the estimation of forest parameters. TomoSAR can reconstruct the 3-D structure of forests through specific imaging techniques. In general, high-resolution imaging algorithms are beneficial to distinguish and identify scatterers with different heights and are widely used in underlying topography and forest height estimation. However, for biomass estimation, radiation accuracy is more of a concern for researchers. At present, the most critical challenge of TomoSAR is the data processing and application of spaceborne data. The main difficulties include the correction of time decoherence and atmospheric delay errors. In the future, long-wavelength TomoSAR systems will become one of the most important approaches for forest biomass estimation on a global scale.

ключеви́че слова́

remote sensing;SAR Tomography;three-dimensional imaging;underlying topography;forest height;forest vertical structure;forest biomass

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