Prediction of the visual impact of motorways using GIS

Abstract

Large scale transportation projects can adversely affect the visual perception of environmental quality and require adequate visual impact assessment. In this study, we investigated the effects of the characteristics of the road project and the character of the existing landscape on the perceived visual impact of motorways, and developed a GIS-based prediction model based on the findings. An online survey using computer-visualised scenes of different motorway and landscape scenarios were carried out to obtain perception-based judgements on the visual impact. Motorway scenarios simulated included the baseline scenario without road, original motorway, motorways with timber noise barriers, transparent noise barriers and tree screen; different landscape scenarios were created by changing land cover of buildings and trees in three distance zones. The landscape content of each scene was measured in GIS. The result shows that presence of a motorway especially with the timber barrier significantly decreases the visual quality of the view. The resulted visual impact tends to be lower where it is less visually pleasant with more buildings in the view, and can be slightly reduced by the visual absorption effect of the scattered trees between the motorway and the viewpoint. Based on the survey result, eleven predictors were identified for the visual impact prediction model which was applied in GIS to generate maps of visual impact of motorways in different scenarios. The proposed prediction model can be used to achieve efficient and reliable assessment of visual impact of motorways.

Combined acoustical and visual performance of noise barriers in mitigating the environmental impact of motorways

“…As for how beneficial they were, the barriers did not show much advantage over tree belt, which was shown to be effective in reducing negative visual impact of motorways (Jiang et al, 2015), but did not offer any actual noise reduction and could even increase the possible noise impact by increasing people's sensitivity to the noise (Watts et al 1999). The similar overall environmental benefits of berries and tree belt found in this study indicate the high importance of visual factors in mitigating environmental impact of motorways.…”

“…2 m in Hong &Jeon (2014)), since relatively far receiver positions are more common in cases of motorways and 100 m was thought to be more typical for the majority of the affected population, and noise reduction by barriers can still be significant at 100 m even when the ground is absorbing (Highways Agency, 2001a). 300 m was chosen for the longer distance scenario because this is around the threshold beyond which barriers may only offer negligible noise reduction (Highways Agency, 2001a) while people can still be adversely affected by noise of high volume traffic (Kotzen & English, 2009) and be visually affected by the barrier (Highways Agency, 1993;Jiang et al, 2015). People in the 300 m distance scenarios are not likely to be the group that the barriers are aimed to benefit, the idea is to see what potential environmental effects, positive or negative, that barriers can still have on this group.…”

Road landscape modelling

“…Geodesign is often used for planning purposes as it includes project analysis, design specification, stakeholder participation, design creation, simulation, and evaluation. Perception-based studies of road project and road planning for scenic environment have been carried out by using ArcGIS software (Jiang, Kang, & Schroth, 2015;Yangyang & Yuning, 2017). ArcGIS has developed 3D visualization possibilities, but our assumption is that GIS based modelling is more appropriate for analysis by experts and does not look realistic enough for landscape evaluation by non-experts.…”

Integrated GIS software for computing landscape visibility metrics

“…In the first group, Idrisi was used very early on for defining viewsheds (Fisher, 1992) and more recently for assessing the visible impact of development projects (Falconer, Hunter, Telfer, & Ross, 2013). However, in the last decade ArcGIS has proved the most popular software in studies of landscape visibility for evaluating the visible impact of new developments (Mouflis, Gitas, Iliadou, & Mitri, 2008), the visual incidence of built elements (Rød & van der Meer, 2009), freeways (Jiang, Kang, & Schroth, 2015), forests (Store, Karjalainen, Haara, Leskinen, & Nivala, 2015), or for assessing the visual quality of landscapes (Palmer, 2004;Schirpke, Tasser, & Tappeiner, 2013). This software is also used in archeology to define intervisibility models (Sevenant & Antrop, 2007) and produce visibility graphs (De Montis & Caschili, 2012).…”