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Computational Urban Science
Publishing model:
Open access

Computational Urban Science - Call for papers: Spatial Science Applications in Promoting Urban Safety, Well-Being, and Health

The following special issue in Computational Urban Science is open for submissions. 

Submission Deadline

Abstract submission: May 31st, 2024

Full submission: July 1st, 2024

Guest Editors

  • Armita Kar (Postdoctoral researcher, Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children’s Hospital) kar.34@osu.edu 
  • Dong Liu (Research Assistant Professor, Institute of Space and Earth Information Science & Institute of Future Cities, The Chinese University of Hong Kong) dongliu@cuhk.edu.hk 
  • Wataru Morioka (Postdoctoral researcher, Department of Geography & GIScience, University of Illinois at Urbana-Champaign) watarum2@illinois.edu

Details

As cities continue to evolve and modernize through new technologies and innovations, the task of providing a safe and healthy urban environment for our communities has become increasingly complex. Beyond the existing health challenges, such as disease outbreaks and epidemics, contemporary cities face a multitude of intertwined social, environmental, and climatic issues, including pollution, natural disasters, crime, hazardous roads, and inequalities. These challenges collectively impact the safety, well-being, and health of urban populations. Effectively addressing these complexities necessitates multidisciplinary, innovative solutions.

Recent advancements in emerging data technologies, computational methods, geospatial data science, and artificial intelligence have empowered us to quantify and assess community health status and outcomes with greater precision. This special issue is dedicated to showcasing innovative research that harnesses the combined power of data science, spatial analytics, and geographic information systems (GIS) to analyze, gauge, and enhance urban safety, well-being, and health.

Topics of interest include, but are not limited to:

  • Predictive modeling of activity and health using spatial big data (e.g., mobile data, social media analytics, and electronic health records)
  • Advancements in spatial epidemiology and associated disparities in health outcomes
  • Data science applications in measuring healthcare perceptions, access, utilization, and associated disparities.
  • Health and safety implications of urban transportation innovations, including smart, shared, and connected mobility solutions. 
  • Crowd-sourced data-driven applications for crime mapping, urban safety assessments, and predictive policing. 
  • Applications of large-scale IoT sensors and satellite imagery-based environmental data, such as air quality, green spaces, and pollution levels, in understanding their influence on urban health and well-being.
  • Integration of geospatial data with sensor data for real-time monitoring and early warning systems in urban health emergencies
  • Applications of machine learning and deep learning techniques in urban health and well-being research
  • Spatial-temporal analysis of urban health disparities and their underlying causes
  • Ethical considerations and privacy-preserving techniques in handling geospatial and health data for urban research

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