Degraded peatland makes up a tiny proportion of the global landmass on earth - at just 0.3% - but contributes disproportionately to carbon emissions, releasing approximately.9 gigatonnes of carbon dioxide equivalent every year, around 5% of annual anthropogenic emissions1. In fact, if managed properly, peatland is one of only a few select landcover types that can act as a carbon sink. With the price of carbon set to increase as we approach 2050, there is an opportunity for landowners to be rewarded for altering their land management practices through the introduction of financial incentives such as carbon credits. However, additionality, permanence, leakage and the co-benefits associated with a given project must all be properly assessed if a trusted carbon credit is to be generate. In-person manual assessment or the use of eddy covariance towers are both expensive assessment methods - limiting the ability of these techniques to provide ground-truth carbon storage information at the spatial/temporal resolution required. Use of remote sensing (RS) techniques provide a promising assessment option, affording the scalability necessary for large or inaccessible project areas. Although some research has previously applied RS to partially model greenhouse gas fluxes in peatlands, to our knowledge, there are still no published studies that use RS to examine the effects of peatland restoration on carbon sequestration. Furthermore, groundtruth data sources of improved spatial resolution are still required to validate these RS approaches. This PhD project will contribute towards developing an improved assessment method - allowing more accurate, scalable and ultimately lower cost assessment of peatland restoration projects.