The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 711–715, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-711-2018
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 711–715, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-711-2018

  19 Sep 2018

19 Sep 2018

THREE-DIMENSIONAL DATA MODELLING FOR UNDERGROUND UTILITY NETWORK MAPPING

J. Yan1, S. W. Jaw1,2,3, R. V. Son1, K. H. Soon4, and G. Schrotter5 J. Yan et al.
  • 1ETH Zurich, Future Cities Laboratory, Singapore-ETH Centre, Singapore
  • 2Geoscience & Digital Eaeth Centre (INSTeG), Research Institute for Sustainable Environment, Universiti Teknologi Malaysia, Malaysia
  • 3Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Malaysia
  • 4Singapore Land Authority, Singapore
  • 5Geomatik + Vermessung Stadt Zurich, Zurich, Switzerland

Keywords: 3D Data Modelling, Underground Utility Networks, Underground space planning, Underground mapping, Utility cadastre

Abstract. Cities around the world face an increasing need for land as density in urban areas increases rapidly. The pressure to expand a city’s space is especially acute for a city-state like Singapore. How to make better use of underground space? This issue becomes much more emergent in the urban development. In the big data era, a data-driven approach of underground spaces is necessary for the sustainable development of a city along with rapid urbanization. A reliable three dimensional (3D) digital map of utility networks is crucial for urban planners to understand one of the most impactful aspects of the underground space planning. The mapping underground utility networks is a challenging task, especially for cities with limited land resources, congested underground spaces, and a lack of uniform existing practices. This paper proposes a framework to organise the workflow from an underground utility data survey to data use. This framework includes two core parts: A 3D utility network data model that aims to convert utility survey data to 3D geospatial information, and a 3D utility cadastral data model that supports utility ownership management. It is expected that reliable and accurate information on underground utility networks can lead to a better understanding and management of underground space, which eventually contributes to better city planning, making the unseen structures visible.