Where to go in Brooklyn: NYC mobility patterns from taxi rides

Abstract

Urban centers attractive for local citizens commonly house local cuisine restaurants or commercial areas. Local authorities are interested in discovering pattern to explain why city residents go to different areas of the city at a given time of the day. We explore a massive dataset of taxi rides, 69 million records in New York city, to uncover attractive places for local residents when going to Brooklyn. First, we obtain the origin destination matrix for New York boroughs. Second, we apply a density based clustering algorithm to detect popular drop-off locations. Next, we automatically find the closest venue, using the Foursquare API, to the most popular destination in each cluster. Our methodology let us to uncover popular destinations in urban areas in any city for which taxi rides information is available.