The use of remote sensing data for mapping and characterising hedgerows and other field boundary features is increasing. At national scales, high resolution imagery and lidar- or radar-derived three-dimensional surface models have been used to map hedgerow networks using both pixel- and object-based methods, often incorporating ancillary data such as field boundary vector layers. At landscape or local scales, airborne lidar provides highly detailed mapping and allows the modelling of characteristics such as height and biomass. However, challenges remain in separating hedgerows from other linear features such as stone walls and limited research has been undertaken to assess the potential to characterise hedgerow structural condition. Unmanned aerial vehicles and terrestrial or mobile laser scanning offer new opportunities to develop methods for measuring hedgerow properties, such as gappiness, leaf biochemistry or species composition. This chapter reviews the current use of remotely sensed data in hedgerow applications and examines future potential opportunities.