Towards intelligent land administration systems: Research challenges, applications and prospects in AI-driven approaches

Hamid Hosseini, Behnam Atazadeh and Abbas Rajabifard

Land Use Policy, 2025, vol. 157, issue C

Abstract: Due to emerging sustainability and resilience issues, particularly in rapidly urbanising areas, managing land information necessitates more effective approaches by adopting innovative digital and intelligent technologies. Many land administration systems (LASs) worldwide still rely on manual and rigid methods, resulting in inadequacies and inefficiencies. Alternatively, artificial intelligence (AI) has received significant attention in (geospatial) information systems. However, adopting AI in LASs is a major challenge from technical, legal, and institutional perspectives. This study investigates current approaches for AI applications across four critical land administration functions: tenure, value, use, and development through a review of the body of knowledge. The main contributions include offering a comprehensive overview of current AI developments in land administration, outlining critical research challenges, and providing future visions in AI-driven LASs. The review indicates the full potential of AI across the entire landscape of land administration has not yet been fully realised, with certain areas still in the early stages of adoption and facing significant challenges. Moreover, AI has been utilised across various discrete research areas. Therefore, this research introduces a conceptual framework for building intelligent LASs using AI-driven approaches. Its novelty lies in aligning with the land information management paradigm, whereby AI is holistically integrated into the land administration functions to enhance consistency. Furthermore, the framework’s two layers show how the functionality of LASs depends on the robustness of data infrastructure powered by AI technologies. Ultimately, the framework supports the shift from static record-keeping to more responsive and data-driven LASs.

Keywords: Land information management; Artificial intelligence; GeoAI; Machine learning; Land administration (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264837725001863
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:lauspo:v:157:y:2025:i:c:s0264837725001863

DOI: 10.1016/j.landusepol.2025.107652

Access Statistics for this article

Land Use Policy is currently edited by Jaap Zevenbergen

More articles in Land Use Policy from Elsevier
Bibliographic data for series maintained by Joice Jiang ().