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A Concise Approach to Characterizing the Distribution of Canopy Leaf Mass per Area in Broad-Leaf Species Based on Crown Three-Dimensional Position and Vegetation Index

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1Pays d’affiliation déclarés

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Le résumé fourni par la source

Leaf mass per area (LMA) represents the allocation of carbon resources per unit leaf area, which is closely related to the photosynthetic capacity of tree leaves. Clarifying the distribution features of LMA is very useful in understanding nutrient and energy transmission and photosynthetic capacity in the canopy. To this aim, the leaf samples of varied forest types were collected, and LMA and related spectral data were measured. The Partial Least Squares (PLS), Linear Mixed Models (LMM), Support Vector Machine Regression (SVM), and Random Forest (RF) methods were used to establish a new model of three-dimension LMA prediction by using vegetation index, DBH, and the vertical and horizontal position of leaves in this study. The results found that the LMA varies significantly with the change in the spatial position of the leaves and horizontal distance to the tree trunk. Statistically speaking, changes in LMA were not significantly related to the direction where the leaves were located. The best model of 3D LMA estimation was RF with a 10-fold R2 value of 0.939. Compared to the RF model, the maximum and minimum of R2 of 10-fold testing of other models increased by 23.75% and 55.87%. The results indicated that RF has a strong generalization ability and can predict the LMA distribution in 3D with a high accuracy. This study showed a reference for LMA 3D feature distribution and is helpful in clarifying the photosynthetic capacity of the canopy.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
A Concise Approach to Characterizing the Distribution of Canopy Leaf Mass per Area in Broad-Leaf Species Based on Crown Three-Dimensional Position and Vegetation Index
Date Crossref
18/05/2025
Éditeur
MDPI AG
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

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Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Leaf Properties and Growth MeasurementRemote Sensing in AgricultureLand Use and Ecosystem Services

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