A new method based on the BP neural network to improve the accuracy of inversion of the vegetation height

Li Tingwei, L. Diannong, Hu Haifeng, Z. Jubo
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引用次数: 1

Abstract

The error in the estimation of the ground interferometric phase will reduce the accuracy of the inversion of the vegetation height in three-stage vegetation inversion method. Aiming at this problem, the new vegetation height inversion method based on the BP neural network is proposed. The new method directly fits the nonlinear mapping relationship between the complex correction coefficients and the vegetation height, so it reduces the height inversion error caused by the error in the estimated ground interferometric phase. The new method has better performance than the three-stage vegetation height inversion method, and the experiment results validate the superiority of the new method.
提出了一种基于BP神经网络提高植被高度反演精度的新方法
在三级植被反演方法中,地面干涉相位估计的误差会降低反演植被高度的精度。针对这一问题,提出了一种基于BP神经网络的植被高度反演方法。该方法直接拟合了复校正系数与植被高度之间的非线性映射关系,减小了地面干涉相位估计误差引起的高度反演误差。新方法比三段式植被高度反演方法具有更好的性能,实验结果验证了新方法的优越性。
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