Field
Value
Language
dc.contributor.author
Munn, Kendra L.C.
datacite.creator.affiliationIdentifier
https://ror.org/0213rcc28
en_US
datacite.creator.affiliation
Simon Fraser University
en_US
datacite.creator.nameIdentifier
https://orcid.org/0000-0002-1589-9122
en_US
dc.contributor.author
Dragićević, Suzana
datacite.creator.affiliationIdentifier
https://ror.org/0213rcc28
en_US
datacite.creator.affiliation
Simon Fraser University
en_US
datacite.creator.nameIdentifier
https://orcid.org/0000-0003-4144-7530
en_US
dc.date.accessioned
2020-10-16T00:42:06Z
dc.date.available
2020-10-16T00:42:06Z
dc.date.issued
2020-10-15
dc.identifier.uri
https://www.frdr-dfdr.ca/repo/dataset/d81743da-ead5-4bc7-8b0b-4cde7b886a5f
dc.identifier.uri
https://doi.org/10.20383/101.0297
dc.description
The buildingrooms and New_5 shapefiles were derived from the City’s open data building footprint shapefiles to represent the base units for 1211 hypothetical residential units spanning 10 high-rise buildings in downtown Vancouver, British Columbia, Canada. Supporting geospatial data and ancillary information were used to conduct spatial analyses in ArcGIS and CityEngine software to calculate the attribute values for each unit for eight evaluation criteria: the proximity to parks, schools, water, and Skytrain stations, and view, duration of direct sunlight, noise and air pollution level. The eight criteria were combined using the proposed 3D multicriteria evaluation method to conduct a suitability analysis in a 3D environment to determine the overall level of suitability of each unit, under five alternative weighting scenarios including three based on the preferences of different ‘resident types’. CityEngine software was used to compute the overall suitability scores and create a 3D model of the urban residential units by extruding unit shapefiles to their height (here termed ‘voxelization’). These tasks were performed by writing rule files using Computer-Generated Architecture (CGA), CityEngine’s unique programming language. The rule files used to calculate the overall suitability scores under the five alternative weighting scenarios, as well as those used to investigate the suitability of each unit based on each individual criterion, are included in the repository as text files.
The data files used to support the analysis are also included. These data were derived from the following publicly available resources:
• Bbbike Extracts OpenStreetMap
https://extract.bbbike.org/
Contains information licensed under the Open Data Commons Open Database License and following a fair usage policy
• 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 the 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
Any reuse or redistribution of the data must acknowledge the original data sources accordingly.
As some sources prohibit data redistribution and publication, some of the geospatial data files used to conduct the research are not available.
en_US
dc.publisher
Federated Research Data Repository / dépôt fédéré de données de recherche
dc.rights
Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
en_US
dc.rights.uri
https://creativecommons.org/licenses/by-sa/4.0/
en_US
dc.subject
GIS
en_US
dc.subject
3D
en_US
dc.subject
Multicriteria evaluation
en_US
dc.subject
Suitability analysis
en_US
dc.subject
3D spatial analysis
en_US
dc.title
3D Multicriteria Evaluation Dataset
en_US
globus.shared_endpoint.name
f163c1b3-9c88-42f6-a7bb-5839ed6c4063
globus.shared_endpoint.path
/8/published/publication_292/
frdr.preservation.status
AIP generation and transfer successful
frdr.preservation.datetime
2020-10-15
datacite.publicationyear
2020
datacite.date.Collected
2017-05-01/2020-08-30
datacite.resourcetype
Dataset
en_US
datacite.fundingReference.funderName
Natural Sciences and Engineering Research Council of Canada (NSERC)
en_US
datacite.fundingReference.awardNumber
RGPIN-2017-03939
en_US
datacite.fundingReference.awardTitle
Discovery Grant
en_US
datacite.fundingReference.funderName
Natural Sciences and Engineering Research Council of Canada (NSERC)
en_US
datacite.fundingReference.awardNumber
en_US
datacite.fundingReference.awardTitle
Undergraduate Student Research Award (USRA)
en_US
frdr.crdc.code
RDF2080202
frdr.crdc.group_en
Environmental engineering and related engineering
en_US
frdr.crdc.class_en
Geomatics engineering
en_US
frdr.crdc.field_en
Geospatial information systems
en_US
frdr.crdc.group_fr
Génie de l'environnement et techniques d'ingénierie connexes
fr_CA
frdr.crdc.class_fr
Génie géomatique
fr_CA
frdr.crdc.field_fr
Systèmes d'information géospatiale
fr_CA
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