  Open space grassland is being increasingly farmed or built upon, leading to a
ramping up of conservation efforts targeting roadside verges. Approximately
half of all UK grassland species can be found along the country's 500,000 km of
roads, with some 91 species either threatened or near threatened. Careful
management of these "wildlife corridors" is therefore essential to preventing
species extinction and maintaining biodiversity in grassland habitats. Wildlife
trusts have often enlisted the support of volunteers to survey roadside verges
and identify new "Local Wildlife Sites" as areas of high conservation
potential. Using volunteer survey data from 3,900 km of roadside verges
alongside publicly available street-view imagery, we present DeepVerge; a deep
learning-based method that can automatically survey sections of roadside verges
by detecting the presence of positive indicator species. Using images and
ground truth survey data from the rural county of Lincolnshire, DeepVerge
achieved a mean accuracy of 88%. Such a method may be used by local authorities
to identify new local wildlife sites, and aid management and environmental
planning in line with legal and government policy obligations, saving thousands
of hours of manual labour.
