CISUC

Mining point-of-interest data from social networks for urban land use classification and disaggregation

Authors

Abstract

Over the last few years, much online volunteered geographic information (VGI) has emerged and has been increasingly analyzed to understand places and cities, as well as human mobility and activity. However, there are concerns about the quality and usability of such VGI. In this study, we demonstrate a complete process that comprises the collection, unification, classification and validation of a type of VGI—online point-of-interest (POI) data—and develop methods to utilize such POI data to estimate disaggregated land use (i.e., employment size by category) at a very high spatial resolution (census block level) using part of the Boston metropolitan area as an example. With recent advances in activity-based land use, transportation, and environment (LUTE) models, such disaggregated land use data become important to allow LUTE models to analyze and simulate a person’s choices of work location and activity destinations and to understand policy impacts on future cities. These data can also be used as alternatives to explore economic activities at the local level, especially as government-published census-based disaggregated employment data have become less available in the recent decade. Our new approach provides opportunities for cities to estimate land use at high resolution with low cost by utilizing VGI while ensuring its quality with a certain accuracy threshold. The automatic classification of POI can also be utilized for other types of analyses on cities.

Keywords

Information extraction; Machine learning; Points of interest; Land use; Volunteered geographic information

Related Project

InfoCrowds - Social Web Information Retrieval for crowds mobility management

Journal

Computers, Environment and Urban Systems, J.C. Thill, January 2015

DOI


Cited by

Year 2018 : 16 citations

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Year 2017 : 24 citations

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volume 160, issue , year 2017, pp. 48 - 60

Year 2016 : 11 citations

 Muhammad Adnan, Francisco C. Pereira, Carlos Lima Azevedo, Kakali Basak, Milan Lovric, Sebastián Raveau, Yi Zhu, Joseph Ferreira, Christopher Zegras, Moshe Ben-Akiva, SimMobility: A Multi-scale Integrated Agent-Based Simulation Platform (2016)

 Yao, Yao, et al. "Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model." International Journal of Geographical Information Science (2016): 1-24.

 Vedernikov, Oleksii, Lars Kulik, and Kotagiri Ramamohanarao. "The Hitchhiker’s guide to the pick-up locations." Open Geospatial Data, Software and Standards 1.1 (2016): 12.

 Gong, X. "Exploring Human Activity Patterns Across Cities through Social Media Data." MSc Thesis. TU Delft. Netherlands (2016).

 Umwelt, Ingenieurfakultät Bau Geo. "Visual Analysis of Large Floating Car Data-A Bridge-Maker between Thematic Mapping and Scientific Visualization." Master Thesis. 2016 TECHNISCHE UNIVERSITÄT MÜNCHEN

 Psyllidis, Achilleas. "Revisiting Urban Dynamics through Social Urban Data." A+ BE| Architecture and the Built Environment 6.18 (2016): 1-334.

 Ricciato, Fabio, et al. "Beyond the “single-operator, CDR-only” paradigm: An interoperable framework for mobile phone network data analyses and population density estimation." Pervasive and Mobile Computing (2016).

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 Guy Lansley, Paul A. Longley, The geography of Twitter topics in London, Computers, Environment and Urban Systems, Volume 58, July 2016, Pages 85-96, ISSN 0198-9715, http://dx.doi.org/10.1016/j.compenvurbsys.2016.04.002.

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 Yimin Chen, Xiaoping Liu, Xia Li, Xingjian Liu, Yao Yao, Guohua Hu, Xiaocong Xu, Fengsong Pei, Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method, Landscape and Urban Planning, Volume 160, April 2017, Pages 48-60, ISSN 0169-2046, http://dx.doi.org/10.1016/j.landurbplan.2016.12.001.

Year 2015 : 1 citations

 E. Chaniotakis, C. Antoniou and E. Mitsakis.Data for Leisure Travel Demand from Social Networking Services. hEART 2015. 4th symposium of European Association for Research in Transportation. September 2015. http://www.heart2015.transport.dtu.dk/-/media/Sites/hEART2015/abstracts hEART/hEART_2015_submission_60.ashx?la=da