A Preliminary Exploration of Uber Data as an Indicator of Urban Liveability

Abstract

Urban liveability is a key concept in the New Urban Agenda (NUA) adopted by the United Nations (UN) in 2016. The UN has recognized that effective benchmarks and monitoring mechanisms are essential for the successful implementation of the NUA. However, the timely and cost effective collection of objective international quality of life urban data remains a significant challenge. Urban liveability indexes are often complex, resource intensive and time consuming to collect, and as a result costly. At the same time, competing methodologies and agendas may result in subjective or non-comparable data. Historically, transit has been a central organizing factor around which communities have been built. This paper explores the use of Uber data as a simple real-time indicator of urban liveability. Using data from the Uber Ride Request (URR) API for the Brazilian city of Natal, our preliminary findings suggest that Uber Estimated Time to Arrive (ETA) data is strongly correlated with selected quality of life indicators at a neighborhood and region level. Furthermore, unlike other urban liveability indicators, our findings suggest that Uber ETA data is context-sensitive reflecting daily and seasonal factors thereby providing more granular insights. This preliminary study finds strong evidence that Uber data can provide a simple, comparable, low cost, international urban liveability indicator at both city and neighborhood level for urban policy setting and planning.