Digital transformation of land resource management in ukraine: from geographic information systems to intelligent agents
DOI:
https://doi.org/10.31548/zemleustriy2026.03.04Keywords:
digital transformation, land resource management, geographic information systems, machine learning, LLM agents, land cadastre, artificial intelligence, Autonomous GISAbstract
The article examines the evolution of digital tools for land resource management in Ukraine through the lens of changing technological paradigms. Three successive generations of digital solutions are distinguished: the first, based on geographic information systems and digital soil mapping; the second, on machine-learning methods and the digital-twin concept; and the third, on generative artificial intelligence and large-language-model (LLM) agents. The study analyses the state of the national regulatory framework, data infrastructure and human capacity in the land-cadastre domain. It is shown that the transition to the third generation is not merely a quantitative improvement of individual indicators but a qualitative redefinition of the human role in spatial analysis: the analyst shifts from operator to task-setter, while the agent autonomously plans and performs the analytical process. Using a unified set of parameters, a comparative characterisation of the three generations is compiled, and a matrix of barriers and opportunities is formed across five domains — data, human capacity, regulation, financing and security. Key prerequisites for a technological-leapfrogging trajectory are substantiated in the context of post-war reconstruction and European integration, together with the imperative of a human-in-the-loop principle for legally significant cadastral data.
Received: 08.06.2026;
Accepted: 22.06.2026;
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