This session broadly welcomes applied and theoretical studies that focus on interdisciplinary information and visualization-based techniques for (a) fostering a better understanding of the urban complexity and (b) supporting the decision-making in the urban planning and management sector. All methodologies related to scientific and information visualization, geovisual analytics, human-computer interaction, and web mapping and web GIS are welcomed. Application areas include building energy systems, infrastructure and asset management, urban crime, urban mobility, urban microclimate, health geography, intelligent transportation system, situational awareness, land and resource management, multi-hazard mitigations, urban water management, socio-economic development, urban food-energy-water nexus, and coupled human and natural systems. Target audiences of this session include urban and regional planners, transportation practitioners, regional policymakers, data scientists, emergency responders, and urban geographers.
Haowen Xu, Oak Ridge National Laboratory (firstname.lastname@example.org)
Anne Berres, Oak Ridge National Laboratory (email@example.com)
Jibonananda Sanyal, Oak Ridge National Laboratory (firstname.lastname@example.org)
If you are interested in participating in this session, please submit your abstract (maximum 250 words) and PIN before Nov 19th, 2020. Detailed instructions on the registration and abstract submission can be found on the web page of the Association of American Geographers (http://www.aag.org).
In recent decades, geovisualization and geovisual analytics are often applied to improve the understanding of and solutions to complex decision problems in urban science through the synergy of computational techniques and human reasoning capabilities. These approaches mainly focus on the development of novel computational applications, such as machine learning, statistical models, and simulation models, to identify, abstract, and predict complex patterns (e.g., spatiotemporal, multivariate, and multivalued) in large geospatial data, as well as interactive visual interfaces that enable data-driven inferences and cognitive processes for (1) exploring the underlying dynamics and mechanism of a complex urban problem as the system of systems, (2) generating new hypotheses for guiding future investigative efforts, (3) solving complex decision problems that involve multiple (conflicting) criteria and objectives from a holistic perspective, and (4) facilitating the public engagement and education in urban planning and management.
|Presenter||Melissa Allen-Dumas*, Oak Ridge National Laboratory, William Pendergrass, National Oceanic and Atmospheric Administration Atmospheric Turbulence and Dispersion Division, Planetary Boundary Layer Schemes for Sub-kilometer Urban Canopy Simulations||12||9:35 AM|
|Presenter||Sarah Tennille*, Oak Ridge National Laboratory, Blake King, Oak Ridge National Laboratory, Sangkeun Lee, Oak Ridge National Laboratory, Determining the Geospatial Reach of Critical Infrastructure Interdependencies||12||9:47 AM|
|Presenter||Jeff Allen*, University of Toronto, Extending demographic dot maps for temporal visual analytics||12||9:59 AM|
|Presenter||Zachery Slocum*, University of North Carolina - Charlotte, Eric Delmelle, University of North Carolina - Charlotte, Wenwu Tang, University of North Carolina - Charlotte, Development of reproducible scientific workflows for web GIS dashboards||12||10:11 AM|
|Presenter||Brittany Krzyzanowski*, University of Minnesota - Minneapolis, Ruthie Burrows, University of Minnesota, Where are the Maps in Studies of Neighborhood Health?||12||10:23 AM|
|Presenter||Anne Berres*, Computational Urban Sciences Group, Oak Ridge National Laboratory, Haowen Xu, Computational Urban Sciences Group, Oak Ridge National Laboratory, Christa Brelsford, Human Geography Group, Oak Ridge National Laboratory, Kevin Sparks, Geoinformatics Engineering Group, Oak Ridge National Laboratory, Sarah Tennille, Computational Urban Sciences Group, Oak Ridge National Laboratory, Jibonananda Sanyal, Computational Urban Sciences Group, Oak Ridge National Laboratory, A Spatiotemporal Visual Analysis of Urban Traffic Pattern Changes during COVID-19||12||10:35 AM|
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