Electric mobility is critical to reducing emissions from transport and dependency on Internal Combustion Engine vehicles. This study attempts to model the suitability of the built environment for electric vehicle (EV) adoption in urban areas based on sociodemographics and access to driveways for installing charging infrastructure. A novel approach using geospatial techniques is adopted to detect driveways from multispectral remote sensing information. A region in Dublin, Ireland, has been chosen as the study area. The region is further categorised based on the feasibility of EV adoption using hierarchical cluster analysis. Initial results highlight the disparity in access to low-emission modes to those not dependent on cars. Results from zero-inflated count models at the neighbourhood level reiterate the impact of driveways and sociodemographic factors on EV adoption. The proposed methodology can help evaluate infrastructure availability for widespread EV transition and inform strategic planning. The driveway detection framework may be adapted to other regions while accounting for geographic characteristics.