Automatic Functional Classification of Buildings Supported by a POI Semantic Characterization Knowledge Graph

The division of urban functional zones is crucial for understanding urban characteristics and aiding in urban management and planning. Traditional methods, like dividing based on blocks and grids, are insufficient for modern demands. To address this, a knowledge-graph-supported method for building f...

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Bibliographic Details
Published inISPRS international journal of geo-information Vol. 13; no. 8; p. 285
Main Authors Su, Youneng, Xu, Qing, Zhu, Xinming, Zhang, Fubing, Liu, Yi
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2024
Subjects
Automation
Buffer zones
building
building functional classification
Buildings
Classification
Construction
knowledge graph
Knowledge representation
points of interest
Semantics
Software engineering
Standard scores
Triangulation
urban functional zone
Urban planning
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Summary:The division of urban functional zones is crucial for understanding urban characteristics and aiding in urban management and planning. Traditional methods, like dividing based on blocks and grids, are insufficient for modern demands. To address this, a knowledge-graph-supported method for building functional category division is proposed. Firstly, the associations between points of interest (POI) and buildings are established using triangulation and buffer zones. Then, a knowledge graph of buildings is constructed through entity and relationship extraction. A functional category classification model supported by the Z-score is designed using the semantic characterizations of surrounding POIs for inference rules. The results demonstrate high accuracy in building functional category division, supporting the refinement and intelligent expression of urban functional zones for urban construction, planning, and management.
ISSN:2220-9964
DOI:10.3390/ijgi13080285