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Big Data Methods and Volunteered Geographic Information in Urban Studies

With the development of information and communications technology, a huge volume of volunteered geographic information (VGI) and user-generated content (UGC) are created. Sources of Volunteered Geographic Information include collaborative mapping projects (e.g., OpenStreetMap and WikiMapia) and social media (e.g., Flickr, Foursquare, Twitter, Facebook). On the one hand, VGI is densely distributed in urban areas, offering new opportunities to undertake researches in urban studies, including transport, urban planning, tourism and mobility/migration. On the other hand, collection, preprocessing and analysis of VGI data are different with those of common geo-data. Particularly, VGI and UGC contain a large volume of noisy and unstructured information. To better use VGI in urban studies, new methods and techniques need to be found and discussed. Big data methods & techniques dedicated to dealing with large-sized and complex data sets pave a way to collection, preprocessing and analysis of VGI. Moreover, data mining methods which are widely used to extract useful information from a huge volume of information could assist in analysis of VGI in the context of urban studies.

This special issue is dedicated to disseminate new progress on utilization of big data methods and VGI in urban studies.

Guest Editors

Dr. Yeran Sun, University of Glasgow, Scotland (
Dr. Yunyan Du, Chinese Academy of Sciences, China (

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