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- IN31B-0350: HABITAT: High-resolution Arctic Built Infrastructure and Terran Analysis Tool
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Board 0350‚ Hall EFG (Poster Hall)NOLA CC
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Chandi Witharana, University of Connecticut (First Author, Presenting Author)
Elias Manos, University of Connecticut
Amal Perera, University of Connecticut
Michael Pimenta, University of Connecticut
Anna Liljedahl, Woodwell Climate Research Center
Accurate monitoring of Arctic permafrost landforms and thaw disturbances is critical for understanding environmental change and assessing risks to human-built infrastructure. Although the Arctic has been extensively imaged by very high spatial resolution (VHSR) satellite sensors, such as Maxar over the past two decades, pan-Arctic geospatial products derived from this rich imagery remain limited. The complexity of remote sensing data, combined with the growing demand for large-scale permafrost modeling, highlights the need for scalable, GeoAI-driven analysis methods. We introduce the High-resolution Arctic Built Infrastructure and Terrain Analysis Tool (HABITAT), a novel GeoAI pipeline that integrates deep learning models with high-performance computing (HPC) to enable automated, extensible, large-scale VHSR image analysis tasks across heterogeneous Arctic landscapes. HABITAT has successfully been deployed on multiple HPC resources for generating first-of-its-kind pan-Arctic geospatial products, such as ice-wedge polygons, human-built infrastructure, and tundra capillary networks. This work demonstrates the potential of AI-powered workflows to accelerate permafrost science and inform infrastructure resilience across the Arctic.
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