Year: 2026
Type: article
Abstract: Cadastral data make it possible to assess territories at the level of individual land parcels, capital construction facilities and established restrictions; however, their analytical potential in master planning is not fully utilized. The main difficulty lies not in the lack of information, but in the need to simultaneously compare permitted land use, functional and territorial zoning, actual land use, zones with special conditions for the use of territories, existing development and infrastructure. The purpose of the study is to develop a methodological approach to intelligent cadastral data analysis for the preliminary identification of land parcels requiring additional examination during master plan development and adjustment. The study employs systems analysis, cadastral interpretation, spatial comparison, classification and multi-criteria assessment. A system of attributes grouped into cadastral-legal, urban planning, actual-use and infrastructure-spatial blocks is proposed. Functional, urban planning, spatial-legal and infrastructural inconsistencies are identified. An algorithm is developed that includes source data preparation, formation of a feature description of a land parcel, intelligent detection of atypical combinations of characteristics, classification of identified inconsistencies and ranking of parcels according to the need for expert review. It is established that artificial intelligence in such a system should not automatically determine the admissibility of land use or substitute professional urban planning decisions. Its function is the preliminary diagnostics of large cadastral datasets and the identification of objects whose combination of characteristics requires more detailed analysis.
Authors: Egor Nakaryakov, Mihail Lavrenenkov
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7222873069