In the face of unprecedented environmental challenges, Earth's dynamic systems are increasingly shaped by both natural and human-driven forces. From declining air quality and rising sea levels to intensifying natural hazards and biodiversity loss, these interconnected crises demand innovative, scalable, and actionable geospatial solutions.
This session invites contributions that harness the power of artificial intelligence (AI), Earth observation (EO), and integrated geospatial infrastructures to address local and global environmental challenges. We focus on the practical application of time-series aerial and satellite remote sensing data, combined with advanced geospatial technologies, to monitor, model, and mitigate impacts related to climate change, natural hazards, and resource management.
We welcome submissions from applied and theoretical domains that emphasize:
• AI and machine learning for land cover change, biomass estimation, and hazard mapping
• Time-series analysis of multi-modal data (optical, SAR, hyperspectral, in-situ)
• Scalable, open-source, and cloud-native geospatial workflows
• 3D geological modeling and dynamic image management
• Integrated geospatial infrastructures for collaborative science and decision-making
Submissions should highlight innovative methodologies and real-world applications using analysis-ready data across the electromagnetic spectrum. The session aims to foster interdisciplinary collaboration and showcase how geospatial technologies can support science-based strategies for resilience and sustainability.