UAV-based method for measuring CO2 emissions in forest ecosystems

Accurate quantification of carbon dioxide (CO₂) emissions in forest ecosystems remains challenging because of pronounced spatial heterogeneity, complex terrain, and the coexistence of vertical and horizontal transport processes in the lower atmosphere. Conventional approaches, including eddy covariance (EC) towers, satellite remote sensing, and manned aircraft measurements, are typically limited to two-dimensional or spatially constrained observations and therefore cannot fully resolve three-dimensional CO₂ exchange. In this study, a UAV-based observational platform is developed and evaluated to quantify CO₂ transport in both horizontal and vertical directions over forest ecosystems. The system integrates a high-precision closed-path CO₂ analyzer with a calibrated ultrasonic anemometer and applies complementary box-pattern and profile-pattern flight strategies within a mass-balance framework. Field experiments were conducted at the Qianyanzhou Experimental Station in southern China between 2023 and 2024, and UAV-derived fluxes were compared with long-term EC tower measurements. Vertical CO₂ fluxes derived from profile-pattern measurements using the gradient method show strong agreement with EC observations across all seasons, demonstrating the capability of the platform to capture canopy-scale turbulent exchange. Box-pattern measurements further enable direct estimation of horizontal CO₂ transport and reveal pronounced diurnal contrasts, with lateral advection dominating during morning and evening periods and vertical uptake prevailing under well-mixed midday conditions. Sensitivity analyses using multiple box sizes indicate that area-normalized net CO₂ emissions are robust with respect to control-volume dimensions. Overall, this study demonstrates that UAV-based measurements provide a reliable and flexible approach for resolving three-dimensional CO₂ transport in forest ecosystems, offering a valuable complement to conventional flux-tower observations, particularly in heterogeneous and complex terrains.