IN002
Actionable AI Datasets, Tooling, and Workflows for Earth Informatics
Session ID#: 248365
Session Description:
Earth informatics is entering a new era powered by AI, but harnessing its full potential requires more than just algorithms—it depends on access to high-quality datasets, user-friendly tools, and scalable workflows. We invite submissions that focus on practical and innovative approaches to building, curating, and using AI-ready datasets, as well as developing the tools and workflows that make them actionable in real-world Earth science applications. Welcome contributions (not limited to): Curated or open-source Earth observation datasets for machine learning; Tools and pipelines for data labeling, cleaning, augmentation, and standardization; Dataset documentation, metadata practices, and benchmarks for AI readiness; End-to-end AI workflows for tasks; Visual, interactive, or map-based tools that make complex datasets accessible; Low-code or no-code platforms enabling broader access to Earth AI; Workflow orchestration and automation; Approaches for ensuring data quality, reproducibility, and safe use in AI systems; Collaborations between researchers, agencies, communities, and open-source contributors.
Co-Sponsor(s):
Index Terms:
1908 Cyberinfrastructure [INFORMATICS]
1942 Machine learning [INFORMATICS]
1976 Software tools and services [INFORMATICS]
1998 Workflow [INFORMATICS]
Primary Convener: Ziheng Sun, George Mason University Fairfax, Fairfax, VA, United States
Conveners: Douglas J Newman1, Stephen W Olding1 and Xiaogang Ma2, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States(2)University of Idaho, Moscow, ID, United States
An Enhanced Spectral Library Providing Tools for Spectra Pre-Processing (1878016)
Marco Solinas1, Massimo Musacchio1, Maria Fabrizia Buongiorno1, Malvina Silvestri1, Alessia Scalabrini1, Sergio Falcone1 and Loredana Modanesi2, (1)National Institute of Geophysics and Volcanology, Rome, Italy, (2)Cultural heritage conservator, Roma, Italy
Lossy Data Compression for the Energy Exascale Earth System Model (1896262)
Peter Martin Caldwell1, Robert L Jacob2, Finn Rebassoo1, Jungmin Lee1, Aaron Sheffield Donahue1, Danqing Wu2, Jayesh Krishna3 and Allison H Baker4, (1)Lawrence Livermore National Laboratory, Livermore, United States, (2)Argonne National Laboratory, Chicago, United States, (3)Argonne National Laboratory, Argonne, United States, (4)National Center for Atmospheric Research, Boulder, United States
Urban Heat MiniCubes: An AI-Ready Dataset for Urban Heat Research and Applications (1902711)
Jonathan Starfeldt1, Maria J Molina1, Alexander Kerr2, Adam Yang2 and Christopher Hain3, (1)University of Maryland College Park, Department of Atmospheric and Oceanic Science, College Park, United States, (2)University of Maryland College Park, Department of Computer Science, College Park, United States, (3)NASA Marshall Space Flight Cetner, Huntsville, United States
Laser or Lens? A Comparative Study of TLS and Video-Based 3D Gaussian Splatting for Tree Reconstruction (1904624)
Aisha Co, Rochester Institute of Technology, Rochester, NY, United States, Fei Zhang, Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, Rochester, United States, Robert Ormal Chancia, Rochester Institute of Technology, Imaging Science, Rochester, NY, United States and Jan van Aardt, Rochester Institute of Technology, Imaging Science, Rochester, United States
CRYSTRACT: A Comprehensive R Package for Batch Processing and Analysis of CIF Data (1935618)
Don Ngo, Carnegie Institution for Science, Earth and Planets Laboratory, Washington, United States, Julia Maria-Hubner, Dresden University of Technology, Dresden, Germany and Anirudh Prabhu, Carnegie Institution for Science, Earth and Planets Laboratory, Washington, DC, United States
HABITAT: High-resolution Arctic Built Infrastructure and Terran Analysis Tool (1949773)
Chandi Witharana1, Elias Manos1, Amal Perera2, Michael Pimenta1 and Anna K Liljedahl3, (1)University of Connecticut, Natural Resources and the Environment, Storrs, United States, (2)University of Connecticut, Natural Resources and Environment, Storrs Mansfield, United States, (3)Woodwell Climate Research Center, Falmouth, United States
California-wide High-Resolution Building Footprint Mapping Using Scalable Deep Learning (1950386)
Akash Awasthi1, Kyle Kristian Kabasares2, Hirofumi Hashimoto3, Khuong H Tran4, Pratima Khatri-Chhetri5, Scott Horner6, Wen Yip2, Ian G Brosnan7, Taejin Park8 and akash awasthi, (1)University of Houston, Houston, United States, (2)Bay Area Environmental Research Institute, Moffett Field, United States, (3)NASA Ames Research Center, Moffett Field, CA, United States, (4)South Dakota State University, Geospatial Sciences Center of Excellence (GSCE), Department of Geography & Geospatial Sciences, Brookings, SD, United States, (5)Bay Area Environmental Research Institute Moffett Field, Moffett Field, United States, (6)NASA Ames Research Center, Moffett Field, United States, (7)NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States, (8)NASA Ames Research Center/Bay Area Environmental Research Institute, Moffett Field, United States
AI-Powered Air Quality Monitoring Using ESP32 and BME280 Sensors for Incense Smoke Classification (1978941)
Rahul Premanand, Broad Run High School, Loudon, United States; George Mason University Fairfax, Fairfax, United States and Ziheng Sun, George Mason University, Center for Spatial Information Science and Systems, Fairfax, VA, United States
AmeriFlux Data Services: Advancing flux science through high-quality data processing and data management practices (1984011)
You-Wei Cheah1, Danielle S Christianson1, Housen Chu2, Gilberto Pastorello1, Fianna O'Brien2, Sy Toan Ngo2, Brian Wang2, Sigrid Dengel1, Stephen Chan2, Sebastien Biraud2 and Margaret S Torn3, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Lawrence Berkeley National Laboratory, Berkeley, United States, (3)Berkeley Lab/UC Berkeley, Berkeley, United States
Transforming Ozone Forecasting: A Deep Learning Approach Using Temporal Fusion Transformers (1987988)
María Paz Dakota Ormeño Vasquez, Duke Kunshan University, Kunshan, China, Saatvik Sunilraj, Broad Run High School, Ashburn, United States, Ziheng Sun, George Mason University, Center for Spatial Information Science and Systems, Fairfax, VA, United States and Dylan Amin, Mount Hebron High School, Ellicott City, United States
The A-KBS Arctic Knowledge Based System: Science Gateway Integration for Exascale Arctic Data Processing and Geospatial Feature Prediction (1990287)
Meisam Shayeghmoradi1, Andrew Wilcox1, Sheridan Parker2, Aaron Bergstrom2, Ian Nesbitt3, Naima Kaabouch2 and Timothy Pasch4, (1)University of North Dakota, Grand Forks, ND, United States, (2)University of North Dakota, Grand Forks, United States, (3)National Center for Ecological Analysis and Synthesis, Santa Barbara, United States, (4)The University of North Dakota, Department of Communication, Grand Forks, United States
Spatiotemporal Modeling of Human Cancer and Avian Influenza Using Air Quality Predictor (1990535)
Anna Deng, BASIS Independent Silicon Valley, San Jose, United States, Athena Xing, Oxford Academy, Cypress, United States and Ziheng Sun, George Mason University, Center for Spatial Information Science and Systems, Fairfax, VA, United States
HydroRAG: A Prototype Knowledge-Based Research Assistant for Intelligent Querying, Gap Analysis, and Hypothesis Generation in Hydrological Science (1997756)
Md Ubayeid Ullah, University of Alabama, Tuscaloosa, United States, Aditya Sharma, University of Southern Mississippi, Stennis Space Center, MS, United States, Jiaqi Gong, University of Alabama, Department of Computer Science, Tuscaloosa, United States, Steven J Burian, Cooperative Institute for Research to Operations in Hydrology (CIROH), Alabama Water Institute, The University of Alabama, Tuscaloosa, AL, Alabama Water Institute, Tuscaloosa, United States and Travis Loof, The University of Alabama, Tuscaloosa, United States
