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Landscape features, such as hedgerows, can play a role in enhancing terrestrial carbon (C) sinks, especially in North-western Europe, where they form a large part of the agricultural landscape. To date, there are few studies relating aerial imagery to ground-truthed biomass measurements and relating changes in biomass to hedgerow management. This study sought to develop relationships between measured biomass of hedgerows and digital elevation model (DEM) data from drones and aircraft. Furthermore, changes in hedgerow above-ground and below-ground biomass stocks were assessed using a systematic grid sample, DEM data and developed volume-biomass regression models. The developed inventory framework was then applied to a pilot study area of 419,701 ha in Ireland. Robust relationships were developed relating DEM data to volume and above-ground biomass. Model equations were also developed linking above-ground and below-ground biomass. However, these were less robust due to the confounding impacts of hedgerow management intensity, hedgerow type and dominant species. Above-ground biomass density was linearly correlated with hedge volume. Wider, less intensively managed, irregular hedges exhibit a higher biomass stocks per km, when compared to regular, more intensively managed hedgerows. When the models were extrapolated to the county level, hedgerow biomass C pools for Co Wexford and Waterford are suggested to be a net emission of -0.3 tC ha -1 year -1 due to hedgerow removals and management. Flailing or coppicing of hedgerows, in particular irregular profile hedgerows, had the largest impact on the biomass C balance in the pilot study area. Re-introduction of traditional management practices such as layering and increasing the allowable hedgerow width in areas qualifying for farm payments could be considered with the aim of increasing the maximum sink potential of established hedgerows., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)