OSMsc: a framework for semantic 3D city modeling using OpenStreetMap

Abstract

Semantic 3D city models have been widely used in computer graphics, geomatics, planning, construction, and urban simulation. While traditional geometric models are used only for visualization purposes, semantic 3D city models contain abundant detailed information, such as location, classification, and functional aspects. Such semantics can facilitate a better interpretation of the built environment by computers. However, the current semantic 3D city models are mostly specific to particular city object types and features, with unclear spatial semantics, which limits their broader applications. This study, therefore, proposes a novel framework called OSMsc, where OSM refers to OpenStreetMap and sc refers to semantic city. The OSMsc framework considers OSM as the primary data source to construct city objects within the specified study area, construct semantic connectors, enrich spatial semantics, and generate the CityJSON-formatted model. The case studies demonstrate that semantic 3D city models constructed by OSMsc are free from geometric and semantic errors, applicable to any city worldwide, and have potential for urban studies, such as urban morphology and urban microclimate analysis.

Keywords:

• Semantic 3D city model
• spatial semantics
• CityJSON
• OpenStreetMap

Authors’ contributions

Rui Ma: conceptualization, data collection, coding design, analysis, manuscript writing and subsequent revisions. Jiayu Chen: conceptualization, manuscript review and subsequent revisions. Chendi Yang: data acquisition and visualization. Xin Li: project administration, conceptualization, manuscript writing, reviewing, and revisions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data and codes availability statement

The source code for OSMsc is available at GitHub (https://github.com/ruirzma/osmsc) and the Semantic 3D City Models (S3CMs) of 25 cities in the US and Europe are available at Figshare (https://doi.org/10.6084/m9.figshare.21779507.v2).

Additional information

Notes on contributors

Rui Ma

Rui Ma is a PhD candidate in the Department of Architecture and Civil Engineering, City University of Hong Kong. His research interests include urban energy modeling, GIS spatial analysis and semantic city modeling.

Jiayu Chen

Jiayu Chen is an Associate Professor in the Department of Construction Management at Tsinghua University. His research focuses on human-centric intelligent construction systems, human-machine collaboration, and urban building digital modeling.

Chendi Yang

Chendi Yang is a PhD candidate in the Department of Architecture and Civil Engineering, City University of Hong Kong. Her main research interests include the built environment, spatial analysis, human behavior and urban analytics.

Xin Li

Xin Li is an Associate Professor of Urban Planning at the Department of Architecture and Civil Engineering, City University of Hong Kong. Her research uses economic theories and statistical and GIS tools to study a wide range of urban issues, including socio-economic changes, brownfield redevelopment, land use regulations, and public housing policies in different institutional settings.