Linking interactive optimization for urban planning with a semantic 3D city model

Journal Article (2018)
Author(s)

Nils Schüler (École Polytechnique Fédérale de Lausanne)

Giorgio Agugiaro (Austrian Institute of Technology)

Sebastien Cajot (École Polytechnique Fédérale de Lausanne)

Francois Marechal (École Polytechnique Fédérale de Lausanne)

Affiliation
External organisation
DOI related publication
https://doi.org/10.5194/isprs-annals-IV-4-179-2018 Final published version
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Publication Year
2018
Language
English
Affiliation
External organisation
Journal title
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume number
IV-4
Pages (from-to)
179-186
Event
ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change” (2018-10-01 - 2018-10-05), Delft, Netherlands
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Abstract

The cities in which we live are constantly evolving. The active management of this evolution is referred to as urban planning. The according development process could go in many directions resulting in a large number of potential future scenarios of a city. The planning support system URBio adopts interactive optimization to assist urban planners in generating and exploring those various scenarios. As a computer-based system it needs to be able to efficiently handle all underlying data of this exploration process, which includes both methodology-specific and context-specific information. This article describes the work carried out to link URBio with a semantic city model. Therefore, two key requirements were identified and implemented: (a) the extension of the CityGML data model to cope with many scenarios by the proposition of the Scenario Application Domain Extension (ADE) and (b) the definition of a data model for interactive optimization. Classes and features of the developed data models are motivated, depicted and explained. Their usability is demonstrated by walking through a typical workflow of URBio and laying out the induced data flows. The article is concluded with stating further potential applications of both the Scenario ADE and the data model for interactive optimization.