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Tuesday, July 19 • 11:00am - 11:30am
AD/VIS: UrbanFlow: Large-scale Framework to Integrate Social Media and Authoritative Landuse Maps

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Users of micro-blogging services and content sharing platforms are generating massive amount of Geotagged information on a daily basis. Although these big data streams are not intended as a source of Geospatial information, researchers have found that ambient geographic information (AGI) complements authoritative sources. In this regard, the digital footprints of users provides a real time monitoring of people activities and their spatial interaction, while more traditional sources such as remote sensing and land use maps provide a synoptic view of the physical infrastructure of the urban environment. Traditionally trained scientists in social science and geography usually face great challenges when experimenting with new methods to synthesize big data sources because of the data volume and its lack of a structure. In order to overcome these challenges we developed UrbanFlow, a platform that allows scientists to synthesize massive Geolocated Twitter data with detailed land use maps. This platform would allow scientists to gather observations to better understand human mobility patterns in relation to urban land use, study cities’ spatial networks based on identifying common frequent visitors between different urban neighborhoods and monitoring the patterns of urban land use change. A key aspect of UrbanFlow is utilizing the power of distributed computing (using Apache Hadoop and cloud-based services) to process massive number of tweets and integrate them with authoritative datasets, as well as efficiently store them in a database cluster to facilitate fast interaction with users.

Tuesday July 19, 2016 11:00am - 11:30am EDT
Chopin Ballroom