Information measures for terrain visualization

Xavier Bonaventura*, Aleksandra A. Sima, Miquel Feixas, Simon J. Buckley, Mateu Sbert, John A. Howell

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Many quantitative and qualitative studies in geoscience research are based on digital elevation models (DEMs) and 3D surfaces to aid understanding of natural and anthropogenically-influenced topography. As well as their quantitative uses, the visual representation of DEMs can add valuable information for identifying and interpreting topographic features. However, choice of viewpoints and rendering styles may not always be intuitive, especially when terrain data are augmented with digital image texture. In this paper, an information-theoretic framework for object understanding is applied to terrain visualization and terrain view selection. From a visibility channel between a set of viewpoints and the component polygons of a 3D terrain model, we obtain three polygonal information measures. These measures are used to visualize the information associated with each polygon of the terrain model. In order to enhance the perception of the terrain's shape, we explore the effect of combining the calculated information measures with the supplementary digital image texture. From polygonal information, we also introduce a method to select a set of representative views of the terrain model. Finally, we evaluate the behaviour of the proposed techniques using example datasets. A publicly available framework for both the visualization and the view selection of a terrain has been created in order to provide the possibility to analyse any terrain model.

Original languageEnglish
Pages (from-to)9-18
Number of pages10
JournalComputers & Geosciences
Early online date28 Oct 2016
Publication statusPublished - 1 Feb 2017

Bibliographical note

This work has been founded in part by grant number TIN2010-21089-C03-01, TIN2013-47276-C6-1-R and BES-2011-045252 of Spanish Government, grant number 2014-SGR-1232 of Generalitat de Catalunya (Catalan Government). The data is sponsored by the Research Council of Norway Petromaks programme (project #193059/E30), together with the Norwegian Petroleum Directorate and the FORCE consortium of oil companies. Riegl LMS GmbH is thanked for ongoing hardware and software support.


  • Best view selection
  • Elevation model
  • Information measures
  • Lidar
  • Photorealistic


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