Urban attractors: Discovering patterns in regions of attraction in cities

Understanding the dynamics by which urban areas attract visitors is important in today’s cities that are continuously increasing population towards higher densities. Identifying services relate to highly attractive districts useful make policies regarding placement of such places. Thus, we present a framework for classifying their attractiveness daily commuters and relating Points Interests (POIs) types districts’ attraction patterns. We used Origin-Destination matrices (ODs) mined from cell phone data capture flow trips between each pair places Riyadh, Saudi Arabia. define profile place based on three main statistical features: The number received, distribution distance traveled road network, spatial spread locations where started. hierarchical clustering algorithm classify all city features attraction. discovered Urban Attractors Riyadh during morning period: G lobal, significant city, D owntown, contains central business district, Residential attractors. In addition, uncovered what makes possess certain significance testing approach quantify relationship (services) patterns detected.