Sensory Aspects of Simulation and Representation in Landscape and Environmental Planning: A Soundscape Perspective

Part of the Sxi — Springer per l’Innovazione / Sxi — Springer for Innovation book series (SXIINNO, volume 10)


The complexity of human spatial experience is often taken for granted. According to Gibson, we perceive the world in a dynamic way (Gibson 1979), thus, due to the phenomenon of movement, perception is not static. Moreover perception itself involves a variety of senses: hearing, touch, smell, taste, sight, the kinaesthetic system (the ability to perceive and coordinate movement) and the vestibular system (the sense of balance). It is clear that pictures do not provide a multi-sensory experience (no smell, no sound, no humidity). Nevertheless, one must say that most of human perception is based on visual information processing, through sight. At the same time, the language of planners, designers and engineers is a form of abstraction, made of images and means of spatial visualization (such as maps) that must convey information and sometimes generate emotions.

This paper provides an overview and outlook of research demonstrating the potential for using multisensory experience for the design, evaluation and assessment of landscape, facilitated by environmental simulation. Conventionally depicted visually, landscape is experienced as a multisensory phenomenon. Research has demonstrated that while visually dominated, all perception is multisensory. The most promising sensory modalities to investigate in combination are sound and vision. Simulation hardware, tools and techniques have reached the point where combining 3D landscape models and acoustic stimuli is achievable and affordable, with the potential to contribute significantly to the future of the planning and design process.


Wind Turbine Geographic Information System Environmental Simulation Acoustic Environment Background Sound 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty of Environmental DesignUniversity of CalgaryCalgaryCanada
  2. 2.Department of LandscapeThe University of SheffieldSheffieldUK

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