Abstract
The objective of this paper is to present a method that qualifies the degree of visibility of an offshore wind farm from an observer located along the coast. In many cases, the deployment of an offshore wind farm leads to public opposition. This entails the need for the development of appropriate methods that might present in the most intelligible way the impacts of an offshore wind farm. Amongst many factors to take into account, the visual impact of such farms is surely a factor to take into account. We introduce a visual operator that integrates several parameters that mainly depend on the distance of the wind farm to the cost. We apply a measure that evaluates the horizon surface impact modulated by the number of distinguishable turbines and an aesthetic index based on turbine alignments. The whole method is implemented on top of a Geographical Information System (GIS) and provides a decision-aid mechanism oriented to decision-makers. The whole approach is experimented in the context of a wind farm in North West France.
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References
Horn, M., Krupp, F.: Earth: The Sequel: The Race to Reinvent Energy and Stop Global Warming. WW Norton & Company, New York (2009)
Jeffrey, H., Jay, B., Winskel, M.: Accelerating the development of marine energy: exploring the prospects, benefits and challenges. Technol. Forecast. Soc. Change 80, 1306–1316 (2013)
Brown, M.T., Cohen, M.J., Sweeney, S.: Predicting national sustainability: the convergence of energetic, economic and environmental realities. Ecol. Model. 220, 3424–3438 (2009)
Douvere, F.: The importance of marine spatial planning in advancing ecosystem-based sea use management. Mar. Policy 32, 762–771 (2008)
Gill, A.B.: Offshore renewable energy: ecological implications of generating electricity in the coastal zone. J. Appl. Ecol. 42, 605–615 (2005)
Boehlert, G.W., Andrew, B.G.: Environmental and ecological effects of ocean renewable energy development: a current synthesis. J. Oceanogr. 23, 68–81 (2010)
Sullivan, R.G., Kirchler, L.B., Cothren, J., Winters, S.L.: Offshore wind turbine visibility and visual impact threshold distances. Environ. Pract. 15, 33–49 (2013)
Barrow, C. J.: Environmental Impact Assessment: Curring Edge for the Twenty-First Century, A. Gilpin. Cabridge University Press, Cambridge (1995)
Bishop, I.D.: What do we really know? A meta-analysis of studies into public responses to wind energy. In: World Renewable Energy Congress, pp. 4161–4169. Linköping University Electronic Press, Linköping (2011)
Ladenburg, J.: Visual impact assessment of offshore wind farms and prior experience. Appl. Energy 86, 380–387 (2009)
Molnarova, K., Sklenicka, P., Stiborek, J., Svobodova, K., Salek, M., Brabec, E.: Visual preferences for wind turbines: location, numbers and respondent characteristics. Appl. Energy 92, 269–278 (2012)
Paar, P.: Landscape visualizations: applications and requirements of 3D visualization software for environmental planning. Comput. Environ. Urban Syst. 30, 815–839 (2006)
Shang, H., Bishop, I.D.: Visual thresholds for detection, recognition and visual impact in landscape settings. J. Environ. Psychol. 20, 125–140 (2000)
Sibille, A.C.T., Cloquell-Ballester, V.A., Cloquell-Ballester, V.A., Darton, R.: Development and validation of a multicriteria indicator for the assessment of objective aesthetic impact of wind farms. Renew. Sustain. Energy Rev. 13, 40–66 (2009)
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Maslov, N., Wang, T., Tang, T., Claramunt, C. (2017). Offshore Wind Turbines Visual Impact Estimation. In: Brosset, D., Claramunt, C., Li, X., Wang, T. (eds) Web and Wireless Geographical Information Systems. W2GIS 2017. Lecture Notes in Computer Science(), vol 10181. Springer, Cham. https://doi.org/10.1007/978-3-319-55998-8_11
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DOI: https://doi.org/10.1007/978-3-319-55998-8_11
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