A vegetation carbon sink prediction method based on fine characterization of crown layer three-dimensional structure

By constructing a three-dimensional canopy structure and employing ray tracing technology and Monte Carlo integration based on multiple importance sampling, the problem of low accuracy of leaf-scale information in canopy photosynthesis models was solved, enabling high-precision prediction of carbon sinks in large-area complex vegetation.

CN122449540APending Publication Date: 2026-07-24BEIJING NORMAL UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING NORMAL UNIVERSITY
Filing Date
2026-03-31
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing canopy photosynthesis models suffer from low accuracy in simulating canopy photosynthesis information at the leaf scale, especially in carbon sink estimation of large-area complex vegetation, where undersampling leads to insufficient accuracy.

Method used

A method based on the fine characterization of the canopy three-dimensional structure was adopted. The three-dimensional structure of the canopy was constructed by lidar point cloud data and surface hyperspectral reflectance orthophotos. The photosynthetic photon flux absorbed point by point in the turbid medium was calculated by using ray tracing technology combined with Monte Carlo integration of multiple importance sampling. The leaves were divided into shaded leaves and sun-sun leaves for vertical layering, and the photosynthetic rate of each layer was calculated. Finally, the total carbon sink was obtained by summing them up.

Benefits of technology

It improves the accuracy of carbon sink prediction for large-area complex vegetation, realizes the precise quantification of leaf distribution density and key photosynthetic parameters within the canopy, enhances the sampling density and uniformity of photosynthetic photon absorption calculation, and improves the accuracy of carbon sink estimation.

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Abstract

The application discloses a vegetation carbon sink prediction method based on fine characterization of crown layer three-dimensional structure and relates to the field of remote sensing ecological monitoring. The method comprises the following steps: regarding a leaf gathering area in the crown layer three-dimensional structure as a turbid medium, and marking the turbid area through leaf area density and chlorophyll concentration; for each turbid medium, calculating point-by-point absorbed photosynthetic photon flux in the turbid medium; layering the turbid medium according to the vertical direction, dividing the leaves in each layer into shade leaves and sun leaves, and calculating the photosynthetic rate of each layer based on the area of the shade leaves, the area of the sun leaves, the photosynthetic photon flux of the sun leaves and the photosynthetic photon flux of the shade leaves in each layer; accumulating the photosynthetic rates of all layers in the turbid medium to obtain the carbon sink amount of the turbid medium, and accumulating the carbon sink amounts of all turbid media in a region to be predicted to obtain the total carbon sink of the region to be predicted. The method improves the carbon sink prediction precision of large-area complex vegetation.
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