Vegetation leaf parameter inversion method and device based on remote sensing

A technology of parameter inversion and remote sensing data, applied in the field of remote sensing, to achieve high accuracy, high reliability and accuracy, and strong physical mechanism

Pending Publication Date: 2022-07-29
AEROSPACE INFORMATION RES INST CAS +1
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

[0004] However, the accuracy of the traditional deep learning-based blade parameter inversion method still has room for improvement.

Method used

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  • Vegetation leaf parameter inversion method and device based on remote sensing
  • Vegetation leaf parameter inversion method and device based on remote sensing
  • Vegetation leaf parameter inversion method and device based on remote sensing

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Embodiment Construction

[0055] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0056] A deep neural network can find out the intrinsic relationship between input and output through learning and training based on the provided sample data.

[0057] In the process of research, the inventor found that the use of deep neural networks in the blade parameter inversion problem has the following problems:

[0058] Deep neural networks (equivalent to "black boxes") lack physical mechanisms and are less interpretable. Th...

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Abstract

The invention provides a vegetation leaf parameter inversion device based on remote sensing, which is obtained based on an inverse process of expressing a PROSAIL model by using a deep neural network, and not only has a relatively strong physical mechanism, but also has relatively high accuracy. According to the remote sensing-based vegetation leaf parameter inversion method provided by the invention, the remote sensing data of the vegetation leaf is inversed to obtain the parameters of the vegetation leaf by using the remote sensing-based vegetation leaf parameter inversion device provided by the invention, and the method has relatively high credibility and accuracy.

Description

technical field [0001] The invention relates to the field of remote sensing, and more particularly, to a method and device for inversion of vegetation leaf parameters based on remote sensing. Background technique [0002] Leaf parameters are important indicators to characterize the growth state of vegetation. Quantitatively obtaining leaf parameters is an important field of precision agriculture research, which is of great significance for supporting carbon cycle research. [0003] At present, the application of remote sensing based on deep learning is increasingly widespread, especially in the problem of nonlinear parameter inversion. The deep neural network model can find the intrinsic relationship between the input parameters and output parameters of the model through continuous learning and training. parameter inversion. [0004] However, there is still room for improvement in the accuracy of traditional deep learning-based blade parameter inversion methods. SUMMARY O...

Claims

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Application Information

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IPC IPC(8): G01N21/17G06N3/04G06N3/08
CPCG01N21/17G06N3/08G01N2021/1797G06N3/048G06N3/045G06N3/084G06V20/188G06N3/0464G06N3/09G06V10/82G06V10/454G06V10/764G06V20/194G06N3/04G06N3/063
Inventor 董莹莹韩芸俐朱溢佞李雪玲
Owner AEROSPACE INFORMATION RES INST CAS
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