Volume IV-4/W3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W3, 71-78, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W3-71-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W3, 71-78, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W3-71-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  25 Sep 2017

25 Sep 2017

HOW TO PINPOINT ENERGY-INEFFICIENT BUILDINGS? AN APPROACH BASED ON THE 3D CITY MODEL OF VIENNA

B. Skarbal1, J. Peters-Anders1, A. Faizan Malik2, and G. Agugiaro1 B. Skarbal et al.
  • 1Austrian Institute of Technology, Smart Citites and Regions Research Field, Giefinggasse 2, 1210 Vienna, Austria
  • 2Vienna University of Economics and Business, Institute for Economic Geography and GIScienceInstitute (WU Wien), Welthandelsplatz 1, 1020 Vienna, Austria

Keywords: CityGML, 3D city modelling, Urban Energy Modelling, 3D Visualisation, Energy Performance of Buildings

Abstract. This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account.

The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine.

While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper.

The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities.

The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements.