Tracking Urban Activity Growth Globally with Big Location Data
Matthew Daggitt, Anastasios Noulas, Blake Shaw, Cecilia Mascolo

TL;DR
This study analyzes global urban growth patterns using Foursquare data, revealing spatial correlations, local growth variations, and competitive or cooperative effects among different venue types across cities.
Contribution
It provides a comprehensive analysis of urban growth and venue interactions worldwide using large-scale location data, highlighting spatial and local growth dynamics.
Findings
Nearby cities share similar growth profiles
Local density influences growth patterns
Venue types exhibit competitive or cooperative effects
Abstract
In recent decades the world has experienced rates of urban growth unparalleled in any other period of history and this growth is shaping the environment in which an increasing proportion of us live. In this paper we use a longitudinal dataset from Foursquare, a location-based social network, to analyse urban growth across 100 major cities worldwide. Initially we explore how urban growth differs in cities across the world. We show that there exists a strong spatial correlation, with nearby pairs of cities more likely to share similar growth profiles than remote pairs of cities. Subsequently we investigate how growth varies inside cities and demonstrate that, given the existing local density of places, higher-than-expected growth is highly localised while lower-than-expected growth is more diffuse. Finally we attempt to use the dataset to characterise competition between new and…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · Land Use and Ecosystem Services · Urban Design and Spatial Analysis
