Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/45189
Title: Height-diameter models: a comprehensive review with new insights on relationships to generalized linear models and differential equations
Authors: DA SILVA, Breno 
Demetrio, C. G. B.
Sermarini, R. A.
MOLENBERGHS, Geert 
VERBEKE, Geert 
Behling, A.
Marques, ERG.
Accioly, Y.
Figura, M. A.
Issue Date: 2024
Publisher: COMMONWEALTH FORESTRY ASSOC
Source: International forestry review, 26 (4) , p. 398 -419
Abstract: Forest scientists use regression models widely, particularly for height-diameter modeling. These models offer several benefits for estimating height in homogeneous or non-homogeneous stands. The original models for height estimation based on diameter at breast height have been extended to include other variables, thanks to technological advancements. The purpose of this article is to provide a literature review using the methodology outlined by Cervo and Bervian (2011), providing helpful information to forest biometricians in selecting a height-diameter model that utilizes historical data. The models can be classified into four main groups and extended to include other covariates besides diameter at breast height. Many of the models used data transformation but results showed that with the exception of one group (nonlinear models), all other models can be considered a generalized linear model, with corresponding linear predictors and link functions. The paper also discusses the generation process of these models, the species to which they are commonly applied, and how they can be created using general ordinary differential equations.
Notes: DA Silva, BG (corresponding author), Luiz de Queiroz Coll Agr ESALQ, Av Padua Dias 11, Piracicaba, Brazil.
brenogsilva@usp.br; clarice.demetrio@usp.br; ralcarde@usp.br;
geert.molenberghs@uhasselt.be; geert.verbeke@kuleuven.be;
alexandre.behling@yahoo.com.br; eduardo.girardi@klabin.com.br;
yuri.accioly@klabin.com.br; mafigura@klabin.com.br
Keywords: height-diameter relationship;height estimation;forestry data models;forest biometrics;sustainable forest practices
Document URI: http://hdl.handle.net/1942/45189
ISSN: 1465-5489
e-ISSN: 2053-7778
DOI: 10.1505/146554824839334687
ISI #: 001390311100002
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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