Monitoring Carbon Fluxes Using Eddy Covariance Flux Tower and Satellite Data in Southern Texas, USA

The eddy covariance (EC) technique is a precise and reliable method for quantifying net ecosystem exchange (NEE) of carbon dioxide (CO 2 ) at the field scale. Despite the sustained increase in atmospheric CO 2 levels, seasonality in NEE remains substantial, driven by the absorption and emission dynamics of terrestrial ecosystems. This study monitors seasonal variability in NEE using EC flux-tower data and Sentinel-2A multispectral satellite imagery. Flux tower data from six Prairie View A&M University sites and Sentinel-2A data were integrated to estimate gross primary production (GPP) using an empirically derived Light Use Efficiency (LUE) model. The R 2 values ranged from 0.53 to 0.68 across the flux tower locations, with RMSE of 40.93 gC m 2 and MAE of 33.19 gC m⁻ 2 10 d⁻ 1 , indicating the LUE model captured the seasonal dynamics of GPP with moderate skill between EC and Sentinel-2A satellite observations. Seasonally, the carbon sink increased markedly during spring and summer, corresponding to the hottest and wettest periods, and decreased post-harvest, such as fall and winter, reflecting the influence of agricultural practices. In addition, pastureland exhibits more stable and sustained carbon uptake, whereas croplands show greater variability driven by phenological cycles and management practices. This study underscores the potential of integrating satellite observations with EC data to scale up local flux tower measurements to broader ecosystem assessments. Such approaches provide valuable insights into the spatiotemporal dynamics of carbon fluxes, advancing our understanding of ecosystem responses to environmental and anthropogenic drivers.