AAG 2023 Symposium on Harnessing the Geospatial Data Revolution for Sustainability Solutions

Description

The Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE, https://i-guide.io) is supported by the National Science Foundation (NSF) as part of its Harnessing the Data Revolution Big Idea initiative (https://www.nsf.gov/news/special_reports/big_ideas/harnessing.jsp). Sponsored by I-GUIDE, this symposium will explore theories, concepts, methods, and tools focused on data-intensive geospatial understanding for driving innovative artificial intelligence (AI) and cyberGIS (cyber-based geographic information science and systems) approaches to address sustainability challenges such as aging infrastructure, biodiversity loss, and food and water insecurity.

At the AAG 2023 annual meeting, the Symposium on Harnessing the Geospatial Data Revolution for Sustainability Solutions will be held by building on the successes of previous Symposia focused on cyberGIS and geospatial data science at AAG annual meetings since 2011. A suite of paper and panel sessions will address cutting-edge advances of cyberGIS, geospatial AI and data science, and fundamental geospatial understanding derived from spatial and spatiotemporal data synthesis. The topical themes of the symposium will include, but are not limited to, frontiers of cyberGIS, geospatial AI and data science, high-performance computing approaches to geographic problem solving, geographic approaches to resilience and sustainability challenges enabled by AI and cyberGIS, and challenges and opportunities of education and workforce development in harnessing the geospatial data revolution.

Sponsorship

Cyberinfrastructure Specialty Group (CISG), Geographic Information Science and Systems (GISS) Specialty Group, Spatial Analysis and Modeling (SAM) Specialty Group, etc.

Panel Sessions

• Convergence of CyberGIS and Geospatial AI
• Data-Intensive Geospatial Understanding for Sustainability Solutions
• Ethics in Geospatial AI and Data Science

Paper Sessions 

• Big Data Computing for Geospatial Applications I
  • Creating consistent global definitions of urban populations with gridded population density models (Brice Hanberry, USDA Forest Service)
• Big Data Computing for Geospatial Applications II
• Computation and Uncertainty of Spatial Accessibility
  • Inclusive Accessibility: Translating person-based mobility perceptions into an aggregated measure (Armita Kar, Ohio State University)
  • A Transit-based Model Integrating Spatial and Nonspatial Factors to Measure Healthcare Accessibility (Wei-En Lo, Chinese Culture University)
  • Spatial delineation per longitudinal sequence in dynamic spatial accessibility: a case study of primary care in New York City (Jinwoo Park, University of Illinois Urbana-Champaign)
• CyberGIS and High-Performance Geospatial Computing
• CyberGIS and Spatial Decision Support Systems (UCGIS)
  • Near real-time survey analytics pipeline for adaptive community engagement (James Collins, City of Austin, Texas)
  • A Geospatial Cyberinfrastructure for Convergence Science – Sustainable Fishery Management (Zhe Zhang, Texas A&M University)
  • Designing Beescape NexGen: A Geovisualization Tool to Support Pollinator Health (Lily Houtman, The Pennsylvania State University)
  • Meeting Human and Biodiversity Needs for 30 × 30 and beyond: the Earthwise Framework and Tool (John A. Gallo, Conservation Biology Institute)
• Data-intensive and Computational Geography
  • A Big Data Exploration of Injustice: Twitter Data and Environmental Justice in New Jersey (Charles Christopher Knoble, Montclair State University)
  • Exploring Road Infrastructure Inequities Across the Conterminous U.S. (Alexander Michels, University of Illinois Urbana-Champaign)
  • Convergence Curriculum for Geospatial Data Science (Eric Shook, University of Minnesota)
• Data-intensive Spatial Modeling for Complex Geographic Problems
  • Multivariate outcome-based GSA to fix equifinality in ABM: pedestrian contact simulation indoor space (Moongi Choi, University of Utah)
  • CyberGIS-ABM: Scaling Complex Spatial Simulations to HPC (Rebecca Vandewalle, University of Illinois Urbana-Champaign)
• Emerging Geo-Data Applications in Road Safety Studies
  • Knowing the Journey to School: Mapping the dangers and violences for children (Michael Keith McCall, UNAM – CIGA)
• Geospatial Artificial Intelligence and Deep Learning
• Geospatial Social Science Approaches to Understanding Human-Environment Interactions in Hazards and Disasters
  • Disentangling the Distant Impacts of US Midwestern Drought on Land Change in Brazil (Nicholas Manning, Michigan State University)
  • River and Watershed Organizations are Key to Geospatial Understanding of Water-Related Hazards (Bailey Makele Holdaway, Utah State University)
  • Mapping Local and Metacoupled Vulnerabilities of Aging Dams (Courtney G Flint, Utah State University)
• Harnessing Geospatial Big Data for Infectious Diseases
  • Twitter sentiments on the stay-at-home orders in the United States (Connor Wu, Troy University)
• Harnessing Geospatial Information for Mental Health and Emotion Issues
• Harnessing Mobility Data for Spatial Knowledge Discovery
  • A Framework for the Comparative Analysis of Diverse Mobility Data (Jessica Embury, San Diego State University)
  • Integrating Mobile Phone Data and Travel Survey to Understand Gender Gap in Ride-hailing (Si Qiao, University of Hong Kong)
  • Modeling the place resilience with heterogeneous graph neural networks (Jiaxin Du, Texas A&M Univeristy)
  • Mining location and trajectory similarities from human mobility data using natural language processing methods (Xiaohuan Zeng, University of Minnesota)
• Human Mobility Analytics in Big Data Era
  • Local perceptions of human mobility in a context of environmental degradation (Carla Sofia Ferreira Fernandes, Universidade Aberta)
• Human-Environment Interactions and Spatial Data Science
  • Urban computing cyberinfrastructure: visualizing human sentiment using social media and augmented reality (Diya Li, Texas A&M University)
  • Texas Highway Network Congestion Analysis (Zhenlei Song, Texas A&M University)
  • Remote sensing monitoring and analysis of space-time evolution of vegetation coverage in Lengshuijiang Tin Mining area (Yanping Wang, Institute of Disaster Prevention)
  • A Human Environment Interaction Modeling Tool for Sustainable Coastal and Ocean Management (Yuhang Xie, Texas A&M University)
• Multimodal Learning with Geospatial Big Data
• Reproducibility and Replicability in the Human-Environment and Geographical Sciences I
  • Insights from Two Surveys on the Reproducibility and Replicability of Geographic Research (Peter Kedron, Arizona State University)
  • Provenance as a prerequisite for reproducibility and replicability in GIScience (Jason Tullis, University of Arkansas)
• Reproducibility and Replicability in the Human-Environment and Geographical Sciences II
  • Workflow Based Tools for Integrated Spatiotemporal Research (Wendy Guan, Harvard University)
  • Framework and Infrastructure for Reproducible Research and Pedagogy in HEGS (Joseph Holler, Middlebury College)
  • Moving Beyond Computation: Reproducing Geographical Analyses of COVID-19 to Assess and Improve the Validity of Research (Sarah Bardin, Arizona State University)
  • Middlebury College Undergraduate Students Reproduce Three Spatial Analysis Studies in Health and Hazards (Junyi Zhou, Middlebury College)
• Social Sensing and Big Data Computing for Disaster Management
  • Translating Earth Observation and geospatially-explicit socio-economic datasets into useful indicators for monitoring progress on land degradation neutrality (Narcisa Pricope, University of North Carolina Wilmington)
• The Revenge of Unintended Consequences: Impacts of Managing and Modeling Geospatial Big Data
  • Geospatial Data and Trust: Privacy and Utility in the Decennial Census (Nicholas Nagle, University of Tennessee)
  • Leveraging Representation Learning for Urban Prediction Tasks (Julia Romero, University of Colorado Boulder)
  • Generalization Quality Metrics in the Age of Big Geospatial Data (Larry Stanislawski, USGS – CEGIS)
• Urban Sensing and Understanding via Big Data and GeoAI

Workshops

• Getting Started with CyberGISX
• CyberGIS-Compute: Geospatial Middleware for High-Performance Computing
• Professional Development for Current and Future Geospatial Data Scientists

 

Co-Chairs

• Courtney Flint, Utah State University
• Eric Shook, University of Minnesota, Twin Cities
• Shaowen Wang, University of Illinois Urbana-Champaign

Program Co-Chairs

• Alexander Michels, University of Illinois Urbana-Champaign
• Jinwoo Park, University of Illinois Urbana-Champaign
• Zhe Zhang, Texas A&M University

Organizing Committee

• Luc Anselin, University of Chicago
• Marc Armstrong, the University of Iowa
• Peter Atkinson, Lancaster University
• Budhendra L. Bhaduri, Oak Ridge National Laboratory
• Ling Bian, University at Buffalo
• Christopher Brunsdon, Maynooth University
• Barbara P. Buttenfield, University of Colorado Boulder
• Guofeng Cao, University of Colorado, Boulder
• Xiang Chen, University of Connecticut
• Alexis Comber, the University of Leeds
• Fabio Duarte, Massachusetts Institute of Technology
• A. Stewart Fotheringham, Arizona State University
• Jing Gao, University of Delaware
• Song Gao, University of Wisconsin – Madison
• Daniel Goldberg, Texas A&M University
• Michael Goodchild, University of California, Santa Barbara
• Joseph Holler, Middlebury College
• Yingjie Hu, Department of Geography, University at Buffalo
• Xiao Huang, University of Arkansas
• Nattapon Jaroenchai, University of Illinois Urbana-Champaign
• Myeonghun Jeong, Chosun University
• Jeon-Young Kang, Kongju National University, South Korea
• Yuhao Kang, University of Wisconsin-Madison
• Peter Kedron, Arizona State University
• Mei-Po Kwan, The Chinese University of Hong Kong
• Wenwen Li, Arizona State University
• Xiao Li, University of Oxford
• Bahar Dadashova, Texas A&M Transportation Institute
• Zhenlong Li, University of South Carolina
• Steven Manson, University of Minnesota, Twin Cities
• Harvey Miller, The Ohio State University
• Shawn Newsam, University of California, Merced
• Anand Padmanabhan, University of Illinois Urbana-Champaign
• Ed Parsons, Google
• Serge Rey, University of California Riverside
• Shih-Lung Shaw, University of Tennessee Knoxville
• Xun Shi, Dartmouth College
• Renee Sieber, McGill University
• Diana Sinton, UCGIS
• Xiaopeng Song, Texas Tech University
• Lawrence Stanislawski, United States Geological Survey
• Kathleen Stewart, University of Maryland
• Wenwu Tang, University of North Carolina at Charlotte
• Ming-Hsiang (Ming) Tsou, San Diego State University
• Rebecca Vandewalle, University of Illinois Urbana-Champaign
• Fahui Wang, Louisiana State University
• Monica Wachowicz, the University of New Brunswick
• John Wilson, University of Southern California
• Dawn J. Wright, Esri
• Ningchuan Xiao, The Ohio State University
• Jin Xing, Newcastle University
• Chaowei (Phil) Yang, George Mason University
• Xinyue Ye, Texas A&M University
• May Yuan, National Science Foundation
• Chuanrong Zhang, University of Connecticut
• Fan Zhang, Hong Kong University of Science and Technology
• Di Zhu, University of Minnesota, Twin Cities