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.