Visualisation and Auralisation for Perception-Driven Decision Supports in Planning: A Comparative Review

Introduction

Perception-driven evaluation, assessment and design assess the quality of the environment based on human perceptual response to the biophysical features of the environment. Advantage of the perception-driven approaches for landscape planning (Daniel, 2001; Lothian, 1999) and soundscape planning (De Coensel et al., 2009, Ruotolo et al., 2013) is that they highlight human experience in the environment, instead of simply examining measured indicators of the biophysical features. Moreover, perception-driven approaches can help involve the public as equal and capable partners in decision-making in landscape planning (Lange & Hehl-Lange, 2005; Orland, 2015) and soundscape planning (Finne & Fryd, 2016; Stienen & Vorländer, 2015), since it does not require expert knowledge or skills to make perceptual judgements on the environment.

Visualisation and auralisation are among the vital technologies to enable and to improve perception-driven decision-support in landscape planning and soundscape planning respectively. Visualisation in landscape planning is a collection of technologies for graphical representations of proposed developments and/or impacts on landscape (Schroth, Wissen Hayek, Lange, Sheppard, & Schmid 2011; Sheppard, 2001). For the scope of perception-driven decision support, visualisation in this chapter refers specifically to creation of landscape surrogates which are used to portray perspective views of landscapes, rather than visualisation in forms of design plans, mappings or information visualisation. Figure 1 gives an example of the concerned visualization. Visualisation traditionally included drawings and scale models. Since the 1960s, photographs and photomontages have been widely used (Lovett et al., 2015). Examples can be found in Smardon, Palmer, & Felleman. (1986, pp. 193) and Landscape Institute & Institute of Environmental Management and Assessment (2002, pp. 57). Photo-based visualisations are effective and straightforward solutions for highly detailed and realistic landscape representations. However, in situations where a larger number of viewpoints or alternative scenarios are needed, they can be quite time-consuming. More recently, computer-based 3D visualisation has enjoyed rapid development and become the most common approach of visualisation today (Lovett, Appleton, Warren-Kretzschmar, & Von Haaren, 2015). Computer-based 3D visualisation has advantageous in links with GIS data (Ode, Fry, Tveit, Messager, & Miller, 2009) and scenario manipulation (Bishop & Miller, 2007). In addition, the real-time rendering capability of computer-based visualisation has increased the interactivity of presented landscape, e.g. free navigation (Appleton & Lovett, 2009) and display control (Salter, Campbell, Journeay, & Sheppard, 2009). However, computer-based visualisation requires abstractions and simplifications due to technology and resource limits, and the achieved levels of realism can be more questionable (Ervin & Hasbrouck, 2001, Lovett et al., 2015).

Figure 1.

An example of the visulisation that portrays a perspective view of the landscape

Source: the author