Spatial multi-criteria evaluation in 3D context: suitability analysis of urban vertical development

ABSTRACT

Urban densification is often seen as a process that aims to limit the negative environmental impacts of urban sprawl in rapidly growing cities by prioritizing planning policies stimulating vertical growth (or high-rise development) over expansion along the urban fringe. Densification of major Canadian urban areas has led to the proliferation of high-rises with an increasing proportion of residents occupying these buildings rather than traditional individual housing. Thus, there is a need for analytical methods that can evaluate the suitability of different residential units in vertical urban developments based on unique criteria for different stakeholders such as prospective residents, developers, or municipal planners. Multi-criteria evaluation (MCE) analysis with weighted linear combination (WLC) is frequently implemented in geographic information systems (GIS) to identify the appropriate solution(s) for a decision problem. However, there are currently no available MCE methods for spatial analysis that can provide evaluation in a three-dimensional (3D) GIS environment, such as for urban vertical development. Therefore, the main objective of this study is to propose a 3D WLC-MCE suitability analysis method for suitability of high-rise residential units in a dense urban area. Five preference scenarios were developed and applied to data from City of Vancouver, Canada. The results indicate that south-facing units and units on higher floors generally exhibit higher levels of suitability as they are less affected by the noise and pollution of the urban road network and receive more sunlight and ocean views. The proposed 3D MCE approach can be used for urban planning and property tax assessment.

KEYWORDS:

• Three dimensions (3D)
• geographic information systems (GIS)
• multicriteria evaluation (MCE)
• 3D spatial analysis
• vertical urban development
• 3D suitability analysis

Acknowledgments

The authors would like to thank the BC Assessment Data Services team for providing necessary information to conduct a portion of this study. They are also thankful to the journal Editor and the two anonymous reviewers for their constructive feedback which has been invaluable in the revision process of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data Availability Statement

As some sources prohibit data redistribution and publication, some of the geospatial data files used to conduct the research are not available. However other data supporting the findings of this study including the created CGA rule files are available in the Federated Research Data Repository at [https://doi.org/10.20383/101.0297]. These data were obtained or derived from publicly available resources; if you use data from one of these resources, please also provide attribution to the original data source, as indicated below:

• Bbbike Extracts OpenStreetMap

https://extract.bbbike.org/

Contains information licensed under the Open Data Commons Open Database License and following a fair usage policy ; data from © OpenStreetMap contributors

• City of Vancouver Open Data Portal

https://opendata.vancouver.ca/pages/home/

Contains information licensed under the Open Government Licence – Vancouver

• City of Vancouver VanMap

https://maps.vancouver.ca/portal/apps/sites/#/vanmap/

Contains information licensed under the Open Government Licence – Vancouver

• Metro Vancouver Open Data Catalogue

http://www.metrovancouver.org/data

Contains information under provisions of the Copyright Act for Metro Vancouver Regional District

• OpenStreetMap

https://www.openstreetmap.org/#map=2/71.3/-96.8

Contains information licensed under the Open Data Commons Open Database License

• Statistics Canada

https://www150.statcan.gc.ca/n1/en/catalogue/92-169-X

Contains information licensed under the Statistics Canada Open License Agreement

Additional information

Funding

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) under Discovery Grant [RGPIN-2017-03939] and Undergraduate Student Research Award (URSA) programs.