Greetings from our lab!
It is with great excitement that we extend an invitation to everyone to participate in the upcoming American Geophysical Union (AGU) Fall Meeting 2023. This prestigious event is scheduled to occur from 11th to 15th December 2023 in San Francisco, with flexible online participation options.
This year, we are thrilled to present our session on "Empowering Disaster Resilience with Big Data, GeoAI, and Digital Twins (NH015)" under the Natural Hazards Section.
As we witness an alarming escalation in the frequency and severity of natural disasters, our societal duty lies in leveraging modern technologies and advances in GIScience to fortify community resilience and mitigate disaster risks.
Our session is a platform for innovative contributions across disciplines that harness these advancements to model and manage disaster risks and resilience. We eagerly invite research that utilizes geospatial big data, such as drone footage, nighttime light images, and social media, for disaster assessment; or explores advanced techniques for modeling and enhancing disaster resilience, such as urban digital twin systems, virtual reality, augmented reality, GeoAI-assisted analysis, and much more. We can't wait to learn about and share your cutting-edge work with our extensive community.
Potential topics may include but are not limited to:
Novel frameworks for assessing and modeling individual and community vulnerability, risk, and resilience to multiple types of disasters.
Emerging geospatial big data for disaster vulnerability, risk, and resilience assessment, prediction, and management, e.g., drone footage, nighttime light images, social media, street view images, mobility data, etc.
Social, geographical, and environmental injustice in disaster vulnerability, risk, and resilience.
Advanced techniques in modeling and enhancing disaster resilience, e.g., urban digital twin systems, virtual reality, augmented reality, etc.
Development of cyberinfrastructure, tools, and platforms for disaster risk, vulnerability, and resilience modeling and visualization
Applications to empower different phases of disaster management, i.e., preparedness, response, recovery, and mitigation, using big data analytics and strategies, deep learning approaches, and responsible AI.
Insights into disaster impacts, e.g., food and water insecurity, infrastructure malfunctions, fatalities, injuries, economic impacts, etc., using big data sources and cloud-based architecture
AI-aided (e.g., deep learning, computer vision, natural language processing) remote sensing and social media data mining in disaster management and resilience assessment.
Time series modeling and prediction for disaster management and resilience assessment.
Multi-modal data fusion (e.g., social media text, images, remote sensing images, street view images) in disaster management and resilience assessment.
Please mark these key dates in your calendar:
Abstract submissions close on August 2 at 23:59 ET/03:59 +1 GMT.
From August 17-31, conveners will review and schedule abstracts in allocated sessions.
By early October, authors will be notified of the acceptance, format, and schedule of their abstracts.

The AGU Fall Meeting 2023 is set to be a stimulating event offering numerous opportunities for learning, networking, and contributing to important discussions. We eagerly anticipate your participation and contributions to our session. If you have any questions or need additional information, don't hesitate to get in touch.
Thank you for your attention. We can't wait to see what innovative contributions you bring to the table!
Link to session details: Empowering Disaster Resilience with Big Data, GeoAI, and Digital Twins (confex.com)
Link to submit abstracts: https://agu.confex.com/agu/fm23/nh/papers/index.cgi?sessionid=191096
Best regards,
Dr. Lei Zou,
Mr. Debayan Mandal,
Dr. Yi Qiang,
Mr. Rohan Singh Wilkho (EC),
Mr. Bing Zhou
Together, let's use technology to build a more resilient world.
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