Abstract
Understanding the dynamics by which urban areas attract visitors is important in today’s cities that are continuously increasing in population towards higher densities. Identifying services that relate to highly attractive districts is useful to make policies regarding the placement of such places. Thus, we present a framework for classifying districts in cities by their attractiveness to daily commuters and relating Points of Interests (POIs) types to districts’ attraction patterns. We used Origin-Destination matrices (ODs) mined from cell phone data that capture the flow of trips between each pair of places in Riyadh, Saudi Arabia. We define the attraction profile for a place based on three main statistical features: The number of visitors a place received, the distribution of distance traveled by visitors on the road network, and the spatial spread of locations from where trips started. We used a hierarchical clustering algorithm to classify all places in the city by their features of attraction. We discovered three main types of Urban Attractors in Riyadh during the morning period: Global, which are significant places in the city, Downtown, which contains the central business district, and Residential attractors. In addition, we uncovered what makes districts possess certain attraction patterns. We used a statistical significance testing approach to quantify the relationship between Points of Interests (POIs) types (services) and the patterns of Urban Attractors detected.
Highlights
According to the United Nations’ 2018 World Urbanization Prospects report, 55% of the planet’s population lives in an urban area and expects the proportion to increase to 68% by 2050 [1]
We investigate if Points of Interests (POIs) can explain why such patterns emerge
We present a computational framework for detecting attraction patterns and further relating POI types to each pattern of attraction
Summary
According to the United Nations’ 2018 World Urbanization Prospects report, 55% of the planet’s population lives in an urban area and expects the proportion to increase to 68% by 2050 [1]. The density of cities brings economic productivity, provides cultural amenities, and facilitates sustainability. It is the root of problems related to congestion, health, and safety. A pressing need, in complex and congested cities is a deeper breakdown and understanding of the major flows of people in a city. Understanding how different places in the city influence human mobility is important for urban planning and transportation operations. It extends to other domains such as epidemiology where the way people move has a significant
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