Date:
Location:
Sponsor Group(s):
Cyberinfrastructure Specialty Group, Geographic Information Science and Systems Specialty Group, Remote Sensing Specialty Group, Spatial Analysis and Modeling Specialty Group
Organizer(s):
Siqin (Sisi) Wang Spatial Sciences Institute, University of Southern California
Peter Kedron Department of Geography, University of California, Santa Barbara
Joseph Holler Middlebury College
Chair(s):
Siqin (Sisi) Wang Spatial Sciences Institute, University of Southern California
Wendy Guan Center of Geographic Analysis, Harvard University
Geospatial artificial intelligence (GeoAI) has brough a significant revolution to GIScience, leading us toward an era that emphasizes studying complexity and resolving real-world issues with the spirit of sharing, sustainability, repeatability, and reproducibility.
Sustainable spatiotemporal simulation empowed by GeoAI-based techniques is a critical aspect of understanding social and environmental processes and predicting their long-term outcomes. To achieve this, frameworks and designs that are repeatable, reproducible, and easily re-employed by a wide range of end-users, policymakers, and individuals without technical expertise are required. A sustainable approach to spatiotemporal spatiotemporal simulation involves considering the persistence and sharing of data collection, management, methodologies and workflows. This requires proper training and practice in data collection, including minimizing data errors and biases, using open data standards, and appropriately documenting the data and methods. Additionally, a repeatable and reproducible framework for data analysis ensures that results can be validated and replicated, thus increasing confidence in the findings. In essence, sustainable spatiotemporal data analytics promotes the cutting-edge frontier of human-centered GeoAI as well as open and citizen science, thereby advancing the field and leading us toward a more sustainable and equitable future.
As such, this AAG 2024 paper session aims to promote the development of repeatable, reproducible, and expandable (RRE) frameworks, methodologies, and technologies (e.g., use of KNIME workflow) to intergrate with GeoAI techniques, spatiotemporal simulation and data sharing, and applied research in the fields of spatiotemporal innovation. Welcome on board for presenters, panelists, and discussants if you have the interests on the below topics:
1. Review on the development of RRE frameworks, methodologies, and technologies
2. Technical development of new RRE frameworks and methodologies centered around GeoAI and spatiotemporal simulation
3. Empirical studies using GeoAI and spatiotemporal simulation as well as RRE frameworks and methodologies in the cross-subdomain of geography and sustainability science, including but not limited to:
• Human geography
• Computation social science
• Human-environment interaction
• Sustainable society
• Urban and environmental sustainability
If you have the interests to join us, please send the abstract ID to Sisi Wang at siqinwan@usc.edu.
Series 1: https://aag.secure-platform.com/aag2024/solicitations/57/sessiongallery/7588
Series 2: https://aag.secure-platform.com/aag2024/solicitations/57/sessiongallery/7677