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Leaf area index inversion method and device

A technology of leaf area index and inversion, applied in measurement devices, neural learning methods, material analysis by optical means, etc., to achieve the effect of improving accuracy

Active Publication Date: 2019-07-05
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI +1
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Problems solved by technology

[0006] This application provides a leaf area index inversion method and device, the purpose of which is to solve the problem of how to balance data dimensionality reduction and inversion accuracy in the case of using a deep neural network model for leaf area index inversion scenarios

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  • Leaf area index inversion method and device
  • Leaf area index inversion method and device
  • Leaf area index inversion method and device

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Embodiment Construction

[0035] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0036] figure 1 The schematic diagram of the structure of the deep neural network model provided by the embodiment of the present application includes 6 network layers, specifically including: two convolutional layers, one pooling layer and three fully connected layers. Among them, the first convolutional layer of the two convolutional layers is connected to the second convolutional layer, the second convolutional layer is connected to the pooling layer, the pooling layer is connect...

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Abstract

The invention discloses a leaf area index inversion method and device, wherein the method comprises the following steps of obtaining remote sensing vegetation canopy spectral reflectance data, and inputting the remote sensing vegetation canopy spectral reflectance data into a pre-trained deep neural network model to obtain a leaf area index output by the depth neural network model, wherein the deep neural network model comprises at least a convolutional layer, and the sampling stride of the convolutional layer is greater than 1 and takes no more than the maximum value of the scale value of thefilter used by the convolutional layer. Through this application, the leaf area index with high precision can be reversed.

Description

technical field [0001] The present application relates to the field of remote sensing data processing, in particular to a leaf area index inversion method and device. Background technique [0002] The leaf area index of vegetation is defined as: the sum of the leaf area of ​​all vegetation on a unit surface area. The leaf area index of vegetation is one of the key parameters to characterize the vegetation canopy structure. It is closely related to many biological and physical processes of vegetation, such as photosynthesis, respiration, carbon cycle, transpiration, and surface net primary productivity. The leaf area index of vegetation is usually determined by using the remote sensing spectral reflectance data of vegetation, and this process is called the inversion process of leaf area index. [0003] At present, the commonly used leaf area index is obtained based on the inversion of statistical methods. Specifically, the statistical methods include: firstly, the vegetatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/552G06N3/04G06N3/08
CPCG01N21/55G06N3/04G06N3/08
Inventor 董莹莹李雪玲朱溢佞叶回春黄文江
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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