Visual, seascape and landscape analysis to support coastal aquaculture site selection

The visual impact of aquaculture is a controversial issue and in some countries must be assessed prior to any new development. However, at present, there are no definitive, objective methods used to evaluate the potential visual impacts of new aquatic farms and therefore assessment is difficult for both developers and regulators. This study presents a GIS based methodology for use in the visual assessment of a potential new coastal fish farm development, focusing on both sea cages and the associated land based structures. The methodology has been applied to a case study area, the Western Isles located off the North West coast of Scotland, which already has an extensive aquaculture industry and significant potential for future growth.Using a two stage sequential modelling process, the methodology combines visual, seascape and landscape analysis within a GIS environment to produce spatial models indicating where there is the potential for new aquaculture development with minimal visual impact. The preliminary visual assessment model combines a series of Boolean viewsheds with landscape and seascape sensitivity models to assess the potential visibility across different user groups and the sensitivity of the area to visual change. The second stage focuses on an area identified from the preliminary model as having potential for development and then performs a more detailed analysis using a site specific proportional visual impact model. This model quantifies the impact by assessing the proportion of viewpoints from which the proposed development can actually be seen. Both stages of the modelling process provide valuable information and support for decision makers regarding the potential visual impacts of aquaculture.

► Development of a GIS based methodology for visual impact assessment of aquaculture.
► Preliminary model combines landscape/seascape sensitivity with Boolean viewsheds.
► Site-specific model uses proportional viewsheds for quantitative analysis.