Recording Plan: 

Curated Track: 

, 

Call For Participation
We invite researchers, practitioners, and thought leaders to join us for the AAG 2025 Symposium on Spatial AI & Data Science for Sustainability. Our session will spotlight Geospatial Artificial Intelligence (GeoAI), Remote Sensing, and Deep Learning, with a focus on how cutting-edge AI, cyberGIS, and remote sensing methods are transforming our ability to address critical sustainability challenges.

Presentations are encouraged on topics including, but not limited to:

* Novel AI and deep learning methods tailored for processing and analyzing remote sensing data

* Challenges in applying AI to large-scale geospatial datasets generated by remote sensing and other sensor networks

* Integrating AI with scientific principles for enhanced interpretability and accuracy in geospatial analysis

* Innovations in supervised deep learning models, such as convolutional neural networks (CNNs), for spatial and spatiotemporal data, especially from remote sensing platforms

* Computational strategies for handling and analyzing big geospatial and remote sensing data, leveraging high-performance computing resources

* Applications of GeoAI and remote sensing in addressing sustainability challenges, such as urban infrastructure resilience, biodiversity conservation, climate adaptation, food security, and water resource management

Description:

As the availability of spatial and remote sensing data grows, Geospatial AI (GeoAI) and deep learning offer powerful tools for unlocking insights from these vast, complex datasets. This symposium, sponsored by the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE), brings together researchers to discuss the theories, methods, and applications of data-intensive GeoAI, remote sensing, and deep learning in tackling global sustainability issues.

With rapid advancements in remote sensing technologies, an unprecedented influx of spatial and temporal data has become available, opening new frontiers in environmental monitoring, land use analysis, disaster management, and more. Deep learning, particularly through convolutional neural networks, has become central to processing and extracting actionable knowledge from these data. However, despite remarkable progress, the application of AI and deep learning to remote sensing data presents unique challenges. Questions remain about how to effectively design and train these models for geospatial data, balancing computational efficiency with interpretability, especially in environmental and geographic contexts.

Building on previous symposia that have explored intersections of cyberGIS, GeoAI, remote sensing, and sustainability, this session at AAG 2025 will emphasize:

* Frontiers of AI, deep learning, and remote sensing in geographic information science and spatial analysis

* High-performance computing applications in processing complex geographic and remote sensing data

* Innovations in spatial AI and remote sensing that contribute to resilient and sustainable communities

* Education and workforce development in the age of spatial data science, AI, and remote sensing

Join us as we navigate the challenges and opportunities presented by GeoAI, remote sensing, and deep learning in spatial research. Whether your work is rooted in theory, method development, or application, this symposium offers a platform to contribute to the ongoing conversation on using spatial AI and remote sensing to create a sustainable future.

Non-Presenting Participants