Constructing a eucalyptus identification model based on NDVI time-series remote sensing images

Xu, Nianxu; Cai, Dong; Zhao, Xiaoqiao

doi:10.1016/j.catena.2024.107846

CATENA

2024

DOI: 10.1016/j.catena.2024.107846

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Constructing a eucalyptus identification model based on NDVI time-series remote sensing images

Nianxu Xu,

Dong Cai,

Xiaoqiao Zhao

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Individual Carbon Modeling in Eucalyptus Stands in the Cerrado Region

Ribeiro,

de Sousa,

Silva

et al. 2024

Forests

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In the context of global climate change, eucalyptus stands in the planted forest sector have become a viable alternative for reducing greenhouse gas (GHG) emissions, in addition to presenting great potential for the carbon (C) stock. Thus, the objective of this study was to quantify C stocks in different eucalyptus compartments, in addition to evaluating three mathematical models at the individual tree level. We evaluated four areas of eucalyptus stands located in the Federal District, Brazil. The data were collected from the forest inventory and rigorous cubing procedures using the following statistical models: Spurr, Schumacher–Hall, and adapted Schumacher–Hall. The highest Pearson’s linear modification coefficient, lowest root means square error percentage (RMSE%), and lowest Akaike information criterion (AIC) were used to select the best model. The C content and stock varied between the compartments and areas studied owing to age and, above all, genetic differences. Clone I224 had the highest carbon concentration per acre at 233.35 Mg ha−1 and carbon difference per compartment. The adapted Schumacher–Hall was the best model. It included data on biometric factors, such as the diameter at breast height, height, and age. The contribution of eucalyptus plantations to carbon sequestration is fundamental to socioenvironmental enhancement.

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Individual Carbon Modeling in Eucalyptus Stands in the Cerrado Region

Ribeiro,

de Sousa,

Silva

et al. 2024

Forests

View full text Add to dashboard Cite

show abstract

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Constructing a eucalyptus identification model based on NDVI time-series remote sensing images

Cited by 1 publication

References 74 publications

Individual Carbon Modeling in Eucalyptus Stands in the Cerrado Region

Individual Carbon Modeling in Eucalyptus Stands in the Cerrado Region

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