AAG 2019 Symposium on Frontiers in Geospatial Data Science

Posted on: October 15, 2018

Geospatial data science represents an emerging interdisciplinary and transdisciplinary field intersecting among three broad knowledge domains: geospatial sciences and technologies, mathematical and statistical sciences, and cyberinfrastructure and computational sciences. The core of this intersection encompasses the synergies and interactions between big data and cyberGIS with geospatial principles guiding discovery and innovation (Figure 1) (Wang and Goodchild, 2018).

 

Figure 1: The scope of geospatial data science

 

CyberGIS is defined as geographic information science and systems (GIS) based on advanced computing and cyberinfrastructure. Though geospatial big data have played important roles in many domains with significant societal impacts, geospatial data science remains to be established for advancing data-intensive geographic research and education in the era of big data and cyberGIS.  At AAG 2019 annual meeting, the Symposium on Frontiers in Geospatial Data Science will be held to provide an exciting and timely forum for sharing recent progress and future trends on geospatial data science and related fields.  A suite of paper and panel sessions will address cutting-edge advances of geospatial data science with a particular focus placed on the following themes: foundations, principles, and theories of geospatial data science; data-driven geography; artificial intelligence and data-intensive approaches to geographic problem solving; geographic knowledge discovery enabled by cyberGIS; education advances and challenges; and spatial cyberinfrastructure.

 

Sponsorship

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

 

Panel Sessions (Incomplete)

* CyberGIS and Geospatial Data Science Curriculum

* Geospatial Data Science: Frontiers and Opportunities

* Uncertainty and Bias in Geospatial Data Science

 

Paper Sessions (Incomplete)

* Geospatial Artificial Intelligence: Machine Learning and Deep Learning

* Data-Intensive Geography

* Education Advances and Challenges in Geospatial Data Science

* Foundations, Principles, and Theories of Geospatial Data Science

* Spatial Prediction

* Synergizing Geospatial Data Science with Domain Applications I: Climate Science

* Synergizing Geospatial Data Science with Domain Applications II: Public Health

* Synergizing Geospatial Data Science with Domain Applications III: Remote Sensing

* Synergizing Geospatial Data Science with Domain Applications III: Disaster Management

If you are interested in organizing any sessions or panels as part of the Symposium, please contact Dandong Yin via dyin4@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 dyin4@illinois.edu by the AAG submission deadline (October 25, 2018).  We look forward to your submissions and participation!


Co-Chairs

 

Program Committee

 

References