Link to Session Platform

Chairs(s):

Rebecca Vandewalle, University of Illinois Urbana Champaign

; Shaowen Wang, University of Illinois Urbana Champaign

Description:

As increasingly massive amounts of human and environmental data are generated from sources such as mobile phones, urban sensors, UAV, and satellites, these data resources provide rich opportunities for generating insights on complex modern problems such as the impact of movement patterns on COVID-19 disease spread. This intersection of complex spatially explicit problems and intensive data access provides both challenges and opportunities for spatial modelers such as for handling data processing, integration, and visualization at scale while benefiting from the potential to for example better set model parameters values and better capture ranges in environmental conditions and behaviors. While rich datasets provide foundation for greater insights into urgent problems, incorporating data at scale and integrating such data into existing spatial models can be challenging.

In this session, we aim to explore new approaches, such as high performance computing methods, modeling needs such as visualization, and application-driven examples, such as modeling the COVID-19 pandemic, for applying big data, as expressed using the 5 V’s (Velocity, Volume, Value, Variety, and Veracity), to models of pressing geospatial concerns for more robust coupling between data, models, and knowledge.

Non-Presenting Participants Agenda