AGU 2026 Session ED019 Launch of the Applied Artificial Intelligence and Deep Learning Book

[tjm0042]

Hello Geo-AI Working Group, 

Thrilled to share that our AGU 2026 session ED019. Frontiers of Geospatial Artificial Intelligence and Capacity Building: Translating Research to Action that Biplov, David, and I are chairing has been accepted. Full abstract and flyer below. 

This session will serve as the launch for the Geo-AI Working Group's grass roots efforts to create and develop the Applied Artificial Intelligence and Deep Learning Book. This Launch will be aligned with NASA HQ's efforts to promote the book! We achieved these milestones together and my hope is that we as a community can leverage this session to promote the hard work, celebrate the efforts, highlight contributors and leaders, and also look forward as a working group. 

We are asking all chapter authors to submit abstracts to highlight their work. But it does not stop there, I know this working group also provides endless reviews, code trouble shooting, content scoping etc. This session is open all, in addition to the chapter authors. So if you would like to submit an abstract, please join us!  

AGU abstracts are due 8/5. Feel free to reach out if you have questions and also please share with your colleagues if possible. 

Best,

Tim

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ED019. Frontiers of Geospatial Artificial Intelligence and Capacity Building: Translating Research to Action 

Session Abstract: 

Rapid advancements in Earth observation (EO) systems, combined with geospatial artificial intelligence (Geo-AI), large language models, foundational models, deep learning, and machine learning, are transforming how environmental data are analyzed and applied to address complex environmental challenges. Yet, a persistent gap remains between technical innovation and the capacity of scientists, practitioners, and decision-makers to effectively utilize these tools. This session focuses on bridging that gap through scalable capacity-building approaches that integrate EO data with applied Geo-AI methodologies. We highlight the role of structured knowledge-sharing mechanisms including open-access books, handbooks, training curricula, community-driven educational resources, and open-source software to democratize access to advanced analytical capabilities. We aim to foster collaboration in leveraging cutting-edge Geo-AI technologies for practical applications, emphasizing designed capacity-building and knowledge-sharing strategies for the geospatial community and workforce. The session will showcase pathways for enabling broader participation in EO-driven decision-making and accelerating the translation of data into actionable insights.