Methane (CH₄) emissions from Arctic tundra are an important feedback to global climate. Currently, modelling and predicting CH₄ fluxes at broader scales is limited by the challenge of upscaling plot-scale measurements in spatially heterogeneous landscapes, and by uncertainties regarding key controls of CH₄ emissions. The research presented here addressed these issues through investigating the influence vegetation has on controlling CH₄ fluxes at the plot scale across a diverse range of arctic plant communities and using field and remotely sensed data to scale fluxes from the plot scale to the patch scale. The studies presented in this thesis have contributed to knowledge of scaling CH₄ fluxes through using detailed vegetation data across a variety of different arctic tundra ecosystems in a several important ways; 1) improved knowledge on the controls of CH₄ fluxes at the plot scale across heterogeneous landscapes, 2) tested the feasibility of using field spectroscopy to distinguish between different tundra vegetation types, 3) demonstrated different mapping methodologies to identify the distribution of these vegetation communities across four different EC tower footprints, and used these distributions to successfully upscale plot level fluxes simply in order to compare to EC tower measurements and finally, 4) provided new insight into potential rapid vegetation community changes due to increasing pressures from climate change. As climate across the Arctic continues to change dramatically, tundra ecosystems are expected to undergo dramatic changes. By understanding linkages between vegetation and CH₄ emissions, our ability to predict future CH₄ dynamics and potential feedbacks to climate are strengthened.