Acta Geodaetica et Cartographica Sinica ›› 2023, Vol. 52 ›› Issue (1): 51-60.doi: 10.11947/j.AGCS.2023.20200581

• Geodesy and Navigation • Previous Articles     Next Articles

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

LIN Dongfang1,2, ZHU Jianjun3, LI Zhiwei3, FU Haiqiang3, LIANG Ji1, ZHOU Fangbin4, ZHANG Bing5   

  1. 1. Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China;
    2. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    3. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;
    4. Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway, Changsha University of Science & Technology, Changsha 410114, China;
    5. School of Geomatics, Liaoning Technical University, Fuxin 123000, China
  • Received:2021-12-31 Revised:2022-11-12 Published:2023-02-09
  • Supported by:
    The National Natural Science Foundation of China (No.42104025);Foundation for Innovative Research Groups of the Natural Science Foundation of Hunan Province (No.2020JJ1003);China Postdoctoral Science Foundation (No.2021M702509);The Natural Resources Sciences and Technology Project of Hunan Province (No.2022-07);Surveying and Mapping Basic Research Foundation of Key Laboratory of Geospace Environment and Geodesy, Ministry of Education (No.20-01-04);The Natural Science Foundation of Hunan Province (Nos. 2021JJ30244;2022JJ30254);Open Fund of Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway (Changsha University of Science & Technology) (No.kfj190805)

Abstract: 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.

Key words: multi-baseline, vegetation height, GVR, PolInSAR, ill-posed problem

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