In this project, we investigate the potential for new sensing modalities to help drive progress on streetscape accessibility by reproducing a geographic section of a major city data collection exercise – the Broadway Curb Cut Survey – using updated technologies. We compare three data collection methods: (i) a smartphone-based field survey with photos; (ii) a 360-degree LiDAR scanner; and (iii) the mass-market 3D imaging device ‘Structure Sensor.’ Post-processing of the point-cloud data on Broadway curbs is conducted. Our work demonstrates the feasibility of using 3D imaging to acquire useful information – including slope width and steepness, presence of steep drops, and potholing. Having considered agency budget and the time / training requirements of the data collection methods, we make recommendations for a smartphone application.