Foundation Model Integration in a Multi-Instance Digital Twin System for Land Use Change

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dc.contributor.authorKussul, Nataliia
dc.contributor.authorShelestov, Andrii
dc.contributor.authorGiuliani, Gregory
dc.contributor.authorDrozd, Sofiia
dc.contributor.authorKolotii, Andrii
dc.contributor.authorSalii, Yevhenii
dc.contributor.authorCherniatevych, Anton
dc.contributor.authorYavorskyi, Oleksandr
dc.contributor.authorMalyniak, Volodymyr
dc.contributor.authorPoussin, Charlotte
dc.date.accessioned2026-01-22T10:30:38Z
dc.date.available2026-01-22T10:30:38Z
dc.date.issued2025-09
dc.description.abstractThis paper presents a novel approach to monitoring land use change by integrating foundation models within a dual-timescale Digital Twin (DT) framework. While existing Earth system DTs primarily focus on atmospheric variables, our architecture explicitly addresses the dynamics of land use transformation. The proposed system utilizes a hierarchical structure of Digital Twin Instances and Aggregators that operate on two temporal scales: a rapid change component for near real-time vegetation monitoring and a gradual change component for long-term land use classification. O ur i mplementation r elies o n cloud-based data pipelines and foundation models for analyzing satellite imagery. It features a cognitive user interface that transforms complex geospatial data into contextually relevant insights. By incorporating pre-trained foundation models and physics-informed neural networks, our framework is designed to improve change detection accuracy while reducing computational requirements. Implementation experiences in Ukrainian and Swiss landscapes demonstrate the framework’s effectiveness across diverse geographic contexts.
dc.format.pagerangeP. 132-136
dc.identifier.citationFoundation Model Integration in a Multi-Instance Digital Twin System for Land Use Change / Nataliia Kussul, Andrii Shelestov, Gregory Giuliani, Sofiia Drozd, Andrii Kolotii, Yevhenii Salii, Anton Cherniatevych, Oleksandr Yavorskyi, Volodymyr Malyniak, Charlotte Poussin // The 13th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, [Gliwice], 4-6 September, 2025. - Gliwice, 2025. - P. 132-136.
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/78331
dc.language.isoen
dc.publisherIEEE
dc.publisher.placeGliwice, Poland
dc.relation.ispartofThe 13th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications 4-6 September, 2025, Gliwice, Poland
dc.subjectDigital Twin
dc.subjectFoundation Models
dc.subjectLand Use Change
dc.subjectEarth Observation
dc.subjectPhysics-Informed Neural Networks
dc.titleFoundation Model Integration in a Multi-Instance Digital Twin System for Land Use Change
dc.typeArticle

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