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ISPRS Int. J. Geo-Inf. 2018, 7(8), 307; https://doi.org/10.3390/ijgi7080307

Automation of Building Permission by Integration of BIM and Geospatial Data

1
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, SE-223 62 Lund, Sweden
2
Sweco Position, Drottningtorget 14, SE-201 22 Malmö, Sweden
*
Author to whom correspondence should be addressed.
Received: 31 May 2018 / Revised: 1 July 2018 / Accepted: 25 July 2018 / Published: 31 July 2018
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Abstract

The building permission process is to a large extent an analogue process where much information is handled in paper format or as pdf files. With the ongoing digitalisation in society, there is a potential to automate this process by integrating Building Information Models (BIM) of planned buildings and geospatial data to check if a building conforms to the building permission regulations. In this study, an inventory of which regulations in the (Swedish) detailed development plans that can be automatically checked or supported by 3D visualisation was conducted. Then, two of these regulations, the building height and the building footprint area, were studied in detail to find to which extent they can be automatically checked by integration of BIM and geospatial data. In addition, a feasibility study of one visual criterion was conducted. One concern when automating the building permission process is the variability of content within the Industry Foundation Classes (IFC) data model. Variations in modelling methods and model content leads to differences in IFC models’ content and structure; these differences complicate automated processes. To facilitate automated processes, requirements on the production of IFC models for building permission applications could be defined in the form of model view definitions or delivery specifications. View Full-Text
Keywords: BIM; geospatial data; building permission BIM; geospatial data; building permission
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Olsson, P.-O.; Axelsson, J.; Hooper, M.; Harrie, L. Automation of Building Permission by Integration of BIM and Geospatial Data. ISPRS Int. J. Geo-Inf. 2018, 7, 307.

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