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.

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