Farmland play an important role in the Earth's carbon cycle, but tracking how carbon fluxes moves in and out of agricultural fields is challenging due to crop rotation and changing management practices. In this study, we used drones to capture high-resolution images of a winter wheat field on five different dates during the growing season. From these images, we estimated the amount of green leaf area—an important indicator of plant growth and how much carbon the crops absorb through photosynthesis.

We then used a crop growth model to simulate how carbon moved in and out of the wheat field. We tested different versions of the model: some used standard settings for winter wheat crop, while others included additional leaf area information collected by the drones. Our findings showed that combining drone imagery with crop models can achieve 1m and hourly frequence carbon fluxes mornitoing in farm fields. This approach can further help researchers and farmers better understand how agriculture impacts the environment and support more sustainable farming practices.