INTELLIGENT ANALYSIS OF CADASTRAL DATA FOR SUBSTANTIATING MASTER PLAN DECISIONS

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

Publication Details

Journal
Mezhdunarodnyi sel skokhozyaistvennyi zhurnal
Published
2026-10-18
DOI
https://doi.org/10.55186/25880209_2026_10_5_52
Primary Topic
3D Modeling in Geospatial Applications
Type
article
Field-Weighted Citation Impact
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article

INTELLIGENT ANALYSIS OF CADASTRAL DATA FOR SUBSTANTIATING MASTER PLAN DECISIONS

Mihail Lavrenenkov, Egor Nakaryakov
Mezhdunarodnyi sel skokhozyaistvennyi zhurnal
3D Modeling in Geospatial Applications
article

INTELLIGENT ANALYSIS OF CADASTRAL DATA FOR SUBSTANTIATING MASTER PLAN DECISIONS

Mihail Lavrenenkov, Egor Nakaryakov
article en

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.

Mezhdunarodnyi sel skokhozyaistvennyi zhurnal
Openalex Percentile: Top 15%
3D Modeling in Geospatial Applications
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