A call for viewshed ecology: Advancing our understanding of the ecology of information through viewshed analysis

Job Aben* (Corresponding Author), Petri Pellikka, Justin M J Travis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)
29 Downloads (Pure)

Abstract

1. There has been rapid increase of interest in the role that information acquisition plays in ecological process and in shaping life histories and their evolution. Compared to auditory and olfactory cues, the range at which visual cues are likely to be informative to animals is particularly sensitive to the spatial structure of the environment. However, quantification of and accounting for availability of visual information in fundamental and applied ecological research remains extremely limited.

2. We argue that a comprehensive understanding of animal behaviour in a spatial context would greatly benefit from objective quantification of the area an animal can potentially obtain visual information from and therefore draw broad attention to viewshed analysis. This analysis identifies all cells of a gridded surface that are connected by lines-of-sight to a viewpoint, hence, providing information on how much of the environment surrounding a location can be seen given the structure of the environment. Although heavily used in non-ecological disciplines including civil planning and archaeology, viewshed analysis has seldom been applied in an ecological context.

3. Here, we highlight the opportunity to make use of viewshed approaches in conjunction with three-dimensional remote sensing data and (3D) data from animal tracking to make major progress in understanding how visual information influences animal spatial behaviour, ecology and evolution.
Original languageEnglish
Pages (from-to)624-633
Number of pages10
JournalMethods in Ecology and Evolution
Volume9
Issue number3
Early online date16 Oct 2017
DOIs
Publication statusPublished - Mar 2018

Bibliographical note

JA was supported by funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 661211, and JMJT by NERC grant NE/J008001/1.

Keywords

  • viewshed analysis
  • LiDAR
  • visual information
  • animal behaviour
  • visual ecology
  • distance sampling
  • perceptual range
  • conservation planning

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