An article describing the production of this data set has been prepared for peer-review. A link will be provided here following publication. Please contact project lead Alex Henshaw (a.henshaw@qmul.ac.uk) for further information in the interim. We are releasing our 'Knepp WildVeg’ geodatabase to support future research on rewilding and landscape change. The geodatabase was co-produced by geographers at Queen Mary University of London and ecologists and conservationists at the Knepp Estate, UK. The data set quantifies vegetation regeneration (vegetation cover, height, density and type) at 20 years since the start of rewilding at Knepp Wildland, West Sussex, UK. The Knepp Estate was previously a 3,500 acre intensive arable and dairy farm, but has been devoted to landscape rewilding since 2001. The unique nature of Knepp provides vast opportunities for environmental research but the scale of the project generates research design challenges. Future research on the environmental and ecological effects of rewilding requires baseline data on vegetation structure and dynamics to inform sampling design. Furthermore, the rewilding agenda has, to date, been largely driven by biodiversity goals (with dramatic results achieved) but the fundamental principles that underpin the approach offer potential for much wider-ranging ecosystem services benefits including natural flood management, nutrient cycling, and climate and soil quality regulation. These outcomes are less well understood and this data set is intended to support their investigation. We analysed Environment Agency airborne LiDAR surveys1 from 2001 and 2019 to produce spatial data on vegetation extent, height and density for both pre-existing vegetation (hedgerows, woodland) and new vegetation that has regenerated in former arable fields following rewilding. We used this information in combination with spectral reflectance data from high resolution satellite imagery2 to classify the new vegetation into three distinct types (thorny scrub, bramble scrub, sallows). Further information on our project is available here arcg.is/C5mDP. The project was funded by Queen Mary University of London via an HSS Collaboration Fund grant. 1 LiDAR data supplied by Environment Agency under Open Government License v3.0. 2 Multispectral satellite image data used in new vegetation classification supplied by Planet Team (2017) under Education and Research Program license. Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.com.