I-GUIDE sessions at AGU 2022

GC081 – Telecoupling: Interdisciplinary Frontier in Convergence Science

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The world is increasingly telecoupled (environmentally and socioeconomically interconnected) through the flows of species, people, goods, information, services, water, air, energy, and capital, among others. These flows are made possible through processes such as trade, tourism, water transfer, technology transfer, disease spread, migration, and information dissemination. Furthermore, events tied to climate change, environmental change, hazards, human activities, war, and critical infrastructure failure in one place could have socioeconomic and environmental impacts in places far away around the world, which in turn form feedbacks. Such distant interactions also have broad societal implications for policy making, resource management, disaster control, planning, design, governance, and sustainable development. This session welcomes contributions that address various aspects of distant interactions, such as dynamics, causes, flows, and effects. This session will be of interest to several AGU sections, including  Biogeosciences, Earth and Space Science Informatics, Global Environmental Change, Hydrology, Natural Hazards, and Science and Society.

Primary Convener

  • Nicholas Manning, Michigan State University

Conveners

  • Shaowen Wang, University of Illinois at Urbana Champaign
  • Jianguo Liu, Michigan State University

Student/Early Career Convener

  • Nicholas Manning, Michigan State University

Index Terms

0402 Agricultural systems; 1630 Impacts of global change; 1803 Anthropogenic effects; 4306 Multihazards


ED013 – Education and Workforce Development for Convergence and Data Sciences in the Era of Artificial Intelligence and Machine Learning

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We are witnessing unprecedented advances and increased applications of artificial intelligence (AI), machine learning (ML), and data sciences in all areas of science and society and are facing a critical need for professionals with expertise in data and information technologies, along with domain knowledge. Academia has begun producing and modifying curriculum to include enhanced training in AI/ML and data science so that students graduate with the requisite skills, literacies, and competencies. This session welcomes contributions from thought leaders and practitioners in multiple earth sciences disciplines and information science to discuss challenges, opportunities and best practices for educators, learners, and researchers to create a workforce for advancing convergence science. The proposed session will be of interest to several AGU sections, including but not limited to Atmospheric Sciences, Hydrology, Education, and Earth and Space Science Informatics.

Primary Convener

  • Mohan K Ramamurthy, University Corporation for Atmospheric Research

Conveners

  • Venkatesh Merwade, Purdue University
  • Anthony Castronova, Consortium of Universities for the Advancement of Hydrological Science
  • Deanna A Hence, University of Illinois at Urbana Champaign

Index Terms

0825 Teaching methods; 1817 Extreme events; 1928 GIS science; 1942 Machine learning


IN015 – Harnessing the Geospatial Data Revolution to Advance Sustainability Science

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Many sustainability challenges, including for example biodiversity loss, and food and water insecurity, among others, are interdependent across space and over time. Tackling these challenges, as a geospatial data deluge permeates broad scientific and societal realms, requires transformative understanding of the complex interactions between driving processes and local sustainability stresses across the full range of spatial, temporal, and domain-specific scales. How to harness geospatial data for multi-scale discoveries aimed at the sustainable development goals is a grand challenge. Conventional scientific approaches tend to be fragmented in space and time, and too frequently they fail to extend beyond siloed domains. These limitations preclude the full and informed use of complex geospatial data, making multi-scale inference and prediction difficult or infeasible. This session invites submissions that address how to holistically integrate heterogeneous geospatial data, innovative artificial intelligence and data science approaches, and domain-specific models with computational reproducibility to advance sustainability science.

Primary Convener

  • Shaowen Wang, University of Illinois at Urbana Champaign

Conveners

  • Thomas W Hertel, Purdue University
  • Upmanu Lall, Columbia University

Student/Early Career Convener

  • Deanna A Hence, University of Illinois at Urbana Champaign

Index Terms

1630 Impacts of global change; 1808 Dams; 1926 Geospatial; 4329 Sustainable development

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