COMBINING ALLOMETRY AND UNMANNED AERIAL VEHICLE TO ESTIMATE ABOVEGROUND BIOMASS AT THE INDIVIDUAL TREE LEVEL

Marín Pompa-García, Jaime Roberto Padilla-Martínez, Eduardo Daniel Vivar-Vivar, Jose Israel Yerena-Yamallel

Abstract


Background: Forest ecosystems are sources of environmental services, not least their considerable capacity to sequester large amounts of carbon. Accurate measurements of aboveground biomass (AGB) are therefore gaining importance in the models implemented by climate change mitigation initiatives. Objective: To estimate the aboveground biomass of individual trees using allometric and photogrammetric techniques, with total tree height (TH) as a predictor variable calculated from images obtained by unmanned aerial vehicles (UAV). Methodology: The experiment included a natural stand of mixed and uneven-aged forest (PAW) and a forestry plantation (REB) as strategic areas to contribute to refining the knowledge regarding AGB estimation. Combining field data with the use of a DJI Phantom 4 Multispectral UAV, we explored TH as a predictor variable of AGB using regression procedures. Results: In the PAW were classified four genera: Pinus, Quercus, Arbutus, and Juniperus, the first was the most abundant genus. On the other hand, the REB site is composed of Pinus arizonica. Consequently, the models of AGB were highly accurate (R2 > 0.85, 0.90) for PAW and REB, respectively. Implications: To improve the estimates of AGB, we would not discount the future inclusion of more dasometric attributes, including spectral variables. It would also be advisable to refine these models by size and age ranges, as well as to apply other non-parametric statistical techniques. Conclusion: We argue that our methodology is useful for biomass estimation and acts to better facilitate the estimation of AGB compared to conventional techniques, as well as allowing subsequent calibration according to local conditions.

Keywords


tree height; regression; tree attributes; airborne observations

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References


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URN: http://www.revista.ccba.uady.mx/urn:ISSN:1870-0462-tsaes.v28i1.58693

DOI: http://dx.doi.org/10.56369/tsaes.5869

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Copyright (c) 2025 Jaime Roberto Padilla-Martínez, Marín Pompa-García, Jose Israel Yerena Yamallel, Eduardo Daniel Vivar-Vivar

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