AAG 2024 Symposium on Geospatial Data Science for Sustainability


The Symposium on Geospatial Data Science for Sustainability will explore theories, concepts, methods, and tools focused on data-intensive geospatial understanding for driving innovative cyberGIS (cyber-based geographic information science and systems) and geospatial data science approaches to address sustainability challenges such as aging infrastructure, biodiversity loss, and food and water insecurity. The Symposium is sponsored by the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE, https://i-guide.io), funded 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).


Geospatial data science is an emerging interdisciplinary and transdisciplinary field that rests at the intersection of three broad knowledge domains: (1) geospatial science and technologies, (2) mathematical and statistical sciences, and (3) cyberinfrastructure and computational sciences. This disciplinary intersection is defined by the synergy and interaction that exist between cyberGIS and data science with geospatial principles guiding critical thinking, discovery, and innovation.


The Symposium on Geospatial Data Science for Sustainability will build on the successes of previous Symposia focused on cyberGIS and geospatial data science at AAG annual meetings since 2011. A suite of paper/panel sessions and workshops 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, multiscale mapping and analysis, geographic approaches to resilience and sustainability challenges enabled by cyberGIS and geospatial data science, and challenges and opportunities of education and workforce development in geospatial data science.



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


Panel Sessions

Paper Sessions


  • Geospatial data science curriculum
  • Geospatial Cyberinfrastructure Workshop: Building High-Performance, Ethical, and Secured Geospatial Software


If you are interested in organizing any sessions or panels as part of the Symposium, please contact Fangzheng Lyu via flu8@illinois.edu. To present a paper in any of the Symposium sessions, please register and submit your abstract online, and email your presenter identification number (PIN), paper title, and abstract to michels9@illinois.edu by the AAG submission deadline (November 16, 2023). We look forward to your submissions and participation!



  • Eric Shook, University of Minnesota, Twin Cities
  • Shaowen Wang, University of Illinois Urbana-Champaign (UIUC)
  • Zhe Zhang, Texas A&M University


  • Alexander Michels, UIUC
  • Fangzheng Lyu, UIUC
  • Zhaonan Wang, UIUC

Organizing Committee

  • Li An, Auburn University
  • Luc Anselin, University of Chicago
  • Marc Armstrong, the University of Iowa
  • Peter Atkinson, Lancaster University
  • David Bennett, the University of Iowa
  • Budhendra L. Bhaduri, Oak Ridge National Laboratory
  • 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
  • Zhenhong Du, Zhejiang University
  • Fabio Duarte, Massachusetts Institute of Technology
  • Chen-Chieh Feng, National University of Singapore
  • 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, Emory University
  • Nattapon Jaroenchai, UIUC
  • Myeonghun Jeong, Chosun University
  • Jeon-Young Kang, Kyung Hee University, South Korea
  • Yuhao Kang, University of South Carolina
  • Peter Kedron, University of California, Santa Barbara
  • Barry Kronenfeld, Eastern Illinois 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
  • Trisalyn Nelson, University of California, Santa Barbara
  • Shawn Newsam, University of California, Merced
  • Anand Padmanabhan, UIUC
  • Jinwoo Park, University of North Dakota
  • Ed Parsons, Google
  • Kun Qin, Wuhan University
  • Ethan Shavers, United States Geological Survey
  • Shih-Lung Shaw, University of Tennessee Knoxville
  • Xun Shi, Dartmouth College
  • Renee Sieber, McGill University
  • Diana Sinton, University Consortium for Geographic Information Science
  • Conghe Song, University of North Carolina at Chapel Hill
  • Xiaopeng Song, Texas Tech University
  • Lawrence Stanislawski, United States Geological Survey
  • Kathleen Stewart, University of Maryland
  • Daniel Sui, Virginia Tech
  • Wenwu Tang, University of North Carolina at Charlotte
  • Ming-Hsiang (Ming) Tsou, San Diego State University
  • Rebecca Vandewalle, UIUC
  • Monica Wachowicz, the University of New Brunswick
  • John Wilson, University of Southern California
  • Dawn J. Wright, Esri
  • Ningchuan Xiao, The Ohio State 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, Peking University
  • Di Zhu, University of Minnesota, Twin Cities
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