Use of unmanned aerial vehicles for estimating carbon storage in subtropical shrubland aboveground biomass

Masuly G. Vega-Puga, José R. Romo-León*, Alejandro E. Castellanos, Reyna A. Castillo-Gámez, Jaime Garatuza-Payán

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Carbon storage studies in arid and semi-arid zones are limited. The use of UAVs (unmanned aerial vehicles) has made it easier to monitor areas of interest, which is difficult with more costly techniques. Objective: The aim of this study is to develop predictive models, using aerial images, to estimate aboveground carbon biomass (ABCS) in subtropical shrub species of Sonora. Materials and methods: ABCS of tree species (>2 m in height) was estimated using field-collected metrics and allometric equations. Remote vegetation metrics (camera mounted on UAV) were obtained using both manual methods (digitization) and automated methods (ForestTools algorithm). Non-parametric tests (Wilcoxon) were conducted to determine differences between field metrics and aerial image metrics. These were used to construct predictive models of individual-level ABCS. Results and discussion: The Wilcoxon test indicated that the maximum crown height estimated in the field and with both approaches is similar (P > 0.05), while crown area and crown volume in situ showed no significant differences (P > 0.05) with the manual approach but shows significant differences with the automated approach (P < 0.05). The predictive models of aboveground carbon biomass (ABCS) with remote approaches were statistically significant (P < 0.001). This suggests that carbon estimation using images can explain the variability of the reference method at the individual level. Conclusion: Aerial imagery is a viable and practical tool for estimating ABCS of trees and shrubs in arid/ semiarid communities.

Translated title of the contributionUso de vehículos aéreos no tripulados para la estimación de almacén de carbono en biomasa aérea de matorral subtropical
Original languageEnglish
JournalRevista Chapingo, Serie Ciencias Forestales y del Ambiente
Volume30
Issue number2
DOIs
StatePublished - May 2024

Bibliographical note

Publisher Copyright:
© 2024 Universidad Autonoma Chapingo. All rights reserved.

Keywords

  • aerial imagery
  • allometric equations
  • arid zones
  • ForestTools algorithm
  • manual digitizing

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