Digital Twins for Land Use Change

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dc.contributor.authorKussul, Nataliia
dc.contributor.authorGiuliani, Gregory
dc.contributor.authorShelestov, Andrii
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.accessioned2025-11-25T14:37:07Z
dc.date.available2025-11-25T14:37:07Z
dc.date.issued2025
dc.description.abstractRapid environmental, socio-economic, and geopolitical changes are accelerating transformations in land use patterns worldwide. To effectively monitor and predict these dynamics, DTs offer a promising approach by integrating real-time Earth observation data, climate models, AI-driven analytics, and socio-economic indicators. This paper identifies a critical gap in the application of Digital Twins (DT) frameworks for land use change monitoring, which remains underexplored. We propose a novel two-timescale DT architecture designed to track both rapid event-driven land cover changes (such as floods, wildfires, war-induced damage) and gradual long-term transformations, such as climate-induced agricultural shifts and urban expansion. By bridging the gap between advanced Earth observation technologies and decision-making processes, the proposed framework contributes to the development of AI-enhanced DT systems that facilitate climate adaptation, disaster response, and long-term sustainability in dynamic land systems.
dc.description.sponsorshipThis research was conducted within the “DT4LC—Developing Scalable Digital Twin Models for Land Cover Change Detection Using Machine Learning” project, supported by the Swiss National Science Foundation (SNSF) as part of the Ukrainian-Swiss Joint Research Programme (USJRP).
dc.format.pagerangeP. 371-389
dc.identifier.citationDigital Twins for Land Use Change / Nataliia Kussul, Gregory Giuliani, Andrii Shelestov, Sofiia Drozd, Andrii Kolotii, Yevhenii Salii, Anton Cherniatevych, Oleksandr Yavorskyi, Volodymyr Malyniak, Charlotte Poussin // System Analysis and Data Mining. Studies in Systems, Decision and Control / ed. by M. Zgurovsky, N. Pankratova. - Vol 609. – Cham : Springer, 2025. – Pp. 371-389. – Bibliogr.: 30 ref.
dc.identifier.doihttps://doi.org/10.1007/978-3-031-97529-5_22
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/77382
dc.language.isoen
dc.publisherSpringer Cham
dc.relation.ispartofSystem Analysis and Data Mining, Studies in Systems, Decision and Control
dc.subjectDigital Twins
dc.subjectLand use change
dc.subjectEarth observation
dc.titleDigital Twins for Land Use Change
dc.title.alternativeЦифрові двійники для зміни землекористування
dc.typeBook chapter

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