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A cyberGIS framework for analyzing urban dynamics to support planning applications

Authors: Shakil Kashem*, University of Illinois at Urbana-Champaign, Shaowen Wang, University of Illinois at Urbana-Champaign
Topics: Geographic Information Science and Systems, Urban and Regional Planning, Cyberinfrastructure
Keywords: CyberGIS, Big Data, Urban Planning, Urban Informatics
Session Type: Paper
Presentation File: No File Uploaded


Despite wider availability of urban big data, thanks to rapidly advancing sensor networks and mobile technologies, urban planning practices are still highly dependent on census-based authoritative data. By relying on such static demographic data for dynamic urban systems, our planning and zoning regulations inherently ignore the uncertain geographic context problem (UGCoP) (Kwan, 2012). While the growth of big data is shifting our focus from long-term strategic planning to short-term thinking about how cities function (Batty, 2013), it can also help gain urban insights that might be absent from the authoritative static data. Big data can be used to visualize and analyze urban systems across multiple spatial and temporal scales, which that can help to better evaluate the efficacy of different planning and zoning regulations. For gaining such insights on patterns and dynamics of an urban system, data should be archived over time, enabling multi-scale and longitudinal spatio-temporal analytics (Thakuriah et al., 2017). CyberGIS is conceptually well positioned to enable such analytics through high-performance, distributed, and collaborative computing approaches (Wang, 2010). In this paper, we propose a novel cyberGIS framework for analyzing space-time dynamics of urban systems by integrating data from multiple sources (e.g., urban sensors, social media, Google map, transit data, etc.). The framework also synthesizes authoritative socio-economic and land use data for plan evaluation and formulation. We took the city of Chicago as a case study to apply this cyberGIS framework and demonstrate how multi-scale space-time analytics can be incorporated into several planning applications of the city.

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