Urban Data Science II: Methods & Models for our Changing Cities

Type: Paper
Theme:
Sponsor Groups: Spatial Analysis and Modeling Specialty Group, Geographic Information Science and Systems Specialty Group
Poster #:
Day: 4/3/2019
Start / End Time: 12:40 PM / 2:20 PM
Room: Harding, Marriott, Mezzanine Level
Organizers: Levi Wolf, Wei Kang, Taylor Oshan
Chairs: Taylor Oshan

Call for Submissions

The city is the darling of geographical data science. Population density often begets data density, so urban data science provides fertile ground for the development of new methods and models across many problem domains that span sociology, economics, political science, epidemiology, and geography. Specifically, urban data science is experiencing a significant bout of high-profile attention as exciting new dynamics are captured with increasing detail. This moment provides an immense opportunity for cutting-edge quantitative geographical research, with recent books, high-profile papers, and new research institutes & environments springing up at multiple institutions around the emerging domain of geographic data science. Thus, we aim to help define this new research frontier by fostering a wide-ranging series of sessions showcasing novel geographic data science for dynamic urban processes. We are seeking all folks interested in many of the different core topics in urban geographic data science, including:

Analysis, modelling, and prediction of movement through, across, and between cities
Modeling and analysis of social media in urban spaces, including text & image sentiment
New methods or applications for geo-social or spatial interaction models
Agent-based models & cellular automata for urban processes
Urban spatial counterfactuals, counterfactual demographies, & stochastic simulation
New methods for geodemographic segmentation and analysis
Applications of geodemographic classifications in urban data science
Place detection, regionalization, clustering, or boundary analysis
Spatial, temporal, or spatio-temporal neighborhood dynamics
Estimation and identification of neighborhood effects
Critical analysis of neighborhood effects, including validity & stationarity assumptions
Local models of neighborhood effects
Urban econometrics, causal inference, and urban program evaluation
Extreme event risk and crisis analysis for complex urban systems
Streetview image sentiment and analysis

Please submit your abstracts and registration PIN to levi.john.wolf@bristol.ac.uk, weikang@ucr.edu, & toshan@umd.edu by October 31, 2018. Please note the conference abstract submission deadline is earlier, on October 25th 2018. This symposium is hosted in conjunction with the University of Bristol Quantitative Spatial Sciences Research Group, the University of Maryland Center for Geospatial Information Science, and the University of California, Riverside Center for Geospatial Sciences.


Description

The city is the darling of geographical data science. Population density often begets data density, so urban data science provides fertile ground for the development of new methods and models across many problem domains that span sociology, economics, political science, epidemiology, and geography. Specifically, urban data science is experiencing a significant bout of high-profile attention as exciting new dynamics are captured with increasing detail. This moment provides an immense opportunity for cutting-edge quantitative geographical research, with recent books, high-profile papers, and new research institutes & environments springing up at multiple institutions around the emerging domain of geographic data science. Thus, we aim to help define this new research frontier by fostering a wide-ranging series of sessions showcasing novel geographic data science for dynamic urban processes. We are seeking all folks interested in many of the different core topics in urban geographic data science.


Agenda

Type Details Minutes Start Time
Presenter Levi Wolf*, University of Bristol, Sean Fox, University of Bristol, Sensing AURAs: Defining Apparent Urban Areas in Developing Countries 20 12:40 PM
Presenter Grant McKenzie, Department of Geography, McGill University, Zheng Liu*, Department of Geographical Sciences, University of Maryland, College Park, Yingjie Hu, Department of Geography, University at Buffalo, Myeong Lee, College of Information Studies, University of Maryland, College Park, Identifying Urban Neighborhood Names through User-Contributed Online Property Listings 20 1:00 PM
Presenter Melanie Green*, University of Liverpool, Dani Arribas-Bel, University of Liverpool, Comparing socioeconomic characteristics and the built environment using high resolution aerial imagery 20 1:20 PM
Presenter Christa Brelsford*, Oak Ridge National Laboratory, Rudy Arthur, University of Exeter, Hywel Williams, University of Exeter, Urban Boundary Detection from Digital Trace Data 20 1:40 PM
Presenter Meixu Chen*, University of liverpool, Dani Arribas-Bel, University of Liverpool, Alex Singleton, University of Liverpool, Exploring the composition of Urban Area of Interests through deep learning 20 2:00 PM

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