Artificial Intelligence and Deep Learning Symposium: Applications and Frontiers in Coupled Natural Human Systems

Type: Paper
Theme: Hazards, Geography, and GIScience
Sponsor Groups: Geographic Information Science and Systems Specialty Group, Spatial Analysis and Modeling Specialty Group, Hazards, Risks, and Disasters Specialty Group
Poster #:
Day: 4/12/2018
Start / End Time: 8:00 AM / 9:40 AM
Room: Grand Ballroom A, Astor, 2nd Floor
Organizers: Yi Qiang, Nina Lam
Chairs: Yi Qiang

Description

In the context of climate change, the understanding of human-environment interaction is vital for decision-makers to develop sustainable and resilient communities. In the fields of geography and environmental sciences, it is increasingly recognized that social and natural systems have to be coupled to be fully understood. However, the intra- and inter-system interactions are typically high-dimensional, non-linear and include complex feedback loops, which are difficult to model using traditional statistical methods and machine learning techniques. The advancement of deep learning, complex systems, and, cyberinfrastructure provides opportunities to model the complex interactions in large-scale coupled natural and human (CNH) systems. Meanwhile, geospatial data generated at an amazing speed enable us to investigate the dynamics of CNH systems from multiple perspectives at nearly real-time. This session calls for paper participation with a focus on CNH modeling using artificial intelligence, geospatial big data, dynamic modeling, and high-performance computing techniques. Example topics include but are not limited to:

(1) Deep learning and artificial intelligence in CNH modeling
(2) Dynamic modeling (e.g. cellular automata and agent based modeling)
(3) Resilience and vulnerability assessment
(4) Social media and crowdsourced geospatial data in CNH modeling
(5) High-performance computing in CNH modeling


To present your paper in the session, please submit your abstract to the AAG annual meeting website, and then send the title, abstract and your PIN to Yi Qiang (yiqiang@hawaii.edu).

Organizing committee
Yi Qiang, University of Hawaii – Manoa, yiqiang@hawaii.edu
Nina Lam, Louisiana State University, nlam@lsu.edu






Agenda

Type Details Minutes Start Time
Presenter Elizabeth Doran*, Duke University, Asim Zia, University of Vermont, Donna M. Rizzo, University of Vermont, Christopher J. Koliba, University of Vermont, Douglas Denu, University of Vermont, Yushiou Tsai, University of Vermont, John Hanley, University of Vermon, Comparative Review of Approaches to Modeling Human Behavior in Agent-based Social-Ecological System Models 20 8:00 AM
Presenter Bhanu Kanwar, Missouri University of Science and Technology, Steven Corns*, Missouri University of Science and Technology, Suzanna Long, Missouri University of Science and Technology, Tom Shoberg, U.S. Geological Survey, CEGIS, Mapping Influential Nodes for Transportation Network Post-Disaster Restoration Planning Using Real-World Data 20 8:20 AM
Presenter Yi Qiang*, University of Hawaii - Manoa, Artificial Intelligence and Deep Learning in the Modeling of Coupled Natural and Human Dynamics 20 8:40 AM
Presenter Lyndon Estes*, Clark University, Kelly Caylor, Earth Resources Institute and Department of Geography, University of California Santa Barbara, Stephanie Debat, Descartes Labs, Ron Eastman, Clark Labs and Graduate School of Geography, Clark University, David R Thompson, Jet Propulsion Lab, Integrating Humans and Machines to Map Smallholder-Dominated Agricultural Frontiers 20 9:00 AM
Presenter Christopher Bone*, Department of Geography, Identifying local-scale drivers of broad-scale emergence in CNH models 20 9:20 AM

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