Comparative analysis of machine learning algorithms and statistical models for predicting crown width of Larix olgensis

Qiu, Siyu; Liang, Ruiting; Wang, Yifu; Luo, Ming; Sun, Yong

doi:10.1007/s12145-022-00854-z

Cited by 2 publications

(1 citation statement)

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“…Many works have focused on the relationship between the size of the crown and other features of the tree [35][36][37][38]. Diameter at breast height (DBH) is the most commonly used independent variable in crown width modelling, since the relationship between DBH and the crown width has been well established in the literature [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54].…”

Section: Introductionmentioning

confidence: 99%

Allometric Model of Crown Length for Pinus sylvestris L. Stands in South-Western Poland

Sporek,

Sporek

2023

Forests

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The growth of a tree depends on the size, shape, and functioning of the crown. The length of the crown is a somewhat subjective value because the base of the crown is often difficult to determine. The aim of this study was to develop an allometric model to calculate the crown length of Pinus sylvestris L., which might serve as an alternative to the current equations used especially for stands of variable density. The model used three predictive variables, i.e., diameter at breast height, tree height, and density. The developed crown length model showed high compatibility with empirical data within the studied stands differing in diameter at breast height, height, age, biosocial position, and, above all, density (SD = 1.786). The correlation coefficient between the empirical crown length for the stand (Hemp*) and the calculated model (Hcal*) was r = 0.974, with a discrepancy of (±) 3.17%. The derived crown length model can be one of the components used to estimate the mass of needles or leaf area index (LAI) and, consequently, the amount of transpiration or the amount of carbon dioxide bound, which is crucial in the context of climate change.

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