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Determination of thresholds of visual impact: the case of wind turbines


  • Ian D Bishop


Visual impact assessment using GIS (geographical information system) based viewshed mapping is commonly employed on major projects. However, there is typically little analysis of the possible range of impact based on the size of the introduced landscape element, its contrast with the surroundings, or the effect of typical levels of atmospheric scattering on the perceived contrast. A landscape element which is increasingly the subject of aesthetic scrutiny and visual analysis is the wind-energy turbine or -- when installed in large numbers -- the wind farm. I take the wind turbine as my subject partly because of its recent significance and also because, as a moving element, it is a special case. I report an Internet-based experiment to determine the relative perceived size of a turbine, image analysis to determine its typical contrast level, and the effect of atmospheric scattering on this contrast. With these three factors and equations derived in an earlier study, estimates are made for the probability of turbine detection, recognition, and visual impact at distances up to 30 km.

Suggested Citation

  • Ian D Bishop, 2002. "Determination of thresholds of visual impact: the case of wind turbines," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 29(5), pages 707-718, September.
  • Handle: RePEc:pio:envirb:v:29:y:2002:i:5:p:707-718

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    Cited by:

    1. Bishop, Ian D. & Miller, David R., 2007. "Visual assessment of off-shore wind turbines: The influence of distance, contrast, movement and social variables," Renewable Energy, Elsevier, vol. 32(5), pages 814-831.
    2. Betakova, Vendula & Vojar, Jiri & Sklenicka, Petr, 2015. "Wind turbines location: How many and how far?," Applied Energy, Elsevier, vol. 151(C), pages 23-31.
    3. Shafiullah, G.M. & M.T. Oo, Amanullah & Shawkat Ali, A.B.M. & Wolfs, Peter, 2013. "Potential challenges of integrating large-scale wind energy into the power grid–A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 306-321.
    4. Sklenicka, Petr & Zouhar, Jan, 2018. "Predicting the visual impact of onshore wind farms via landscape indices: A method for objectivizing planning and decision processes," Applied Energy, Elsevier, vol. 209(C), pages 445-454.
    5. Manchado, Cristina & Gomez-Jauregui, Valentin & Otero, César, 2015. "A review on the Spanish Method of visual impact assessment of wind farms: SPM2," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 756-767.
    6. Dai, Kaoshan & Bergot, Anthony & Liang, Chao & Xiang, Wei-Ning & Huang, Zhenhua, 2015. "Environmental issues associated with wind energy – A review," Renewable Energy, Elsevier, vol. 75(C), pages 911-921.
    7. Ambrey, Christopher L. & Fleming, Christopher M., 2011. "Valuing scenic amenity using life satisfaction data," Ecological Economics, Elsevier, vol. 72(C), pages 106-115.
    8. Tabassum-Abbasi, & Premalatha, M. & Abbasi, Tasneem & Abbasi, S.A., 2014. "Wind energy: Increasing deployment, rising environmental concerns," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 270-288.
    9. Liljenfeldt, Johanna & Pettersson, Örjan, 2017. "Distributional justice in Swedish wind power development – An odds ratio analysis of windmill localization and local residents’ socio-economic characteristics," Energy Policy, Elsevier, vol. 105(C), pages 648-657.
    10. Bishop, Ian D. & Stock, Christian, 2010. "Using collaborative virtual environments to plan wind energy installations," Renewable Energy, Elsevier, vol. 35(10), pages 2348-2355.
    11. Geißler, Gesa & Köppel, Johann & Gunther, Pamela, 2013. "Wind energy and environmental assessments – A hard look at two forerunners' approaches: Germany and the United States," Renewable Energy, Elsevier, vol. 51(C), pages 71-78.
    12. Ukashatu Abubakar & Saad Mekhilef & Hazlie Mokhlis & Mehdi Seyedmahmoudian & Ben Horan & Alex Stojcevski & Hussain Bassi & Muhyaddin Jamal Hosin Rawa, 2018. "Transient Faults in Wind Energy Conversion Systems: Analysis, Modelling Methodologies and Remedies," Energies, MDPI, Open Access Journal, vol. 11(9), pages 1-33, August.
    13. Sunak, Yasin & Madlener, Reinhard, 2016. "The impact of wind farm visibility on property values: A spatial difference-in-differences analysis," Energy Economics, Elsevier, vol. 55(C), pages 79-91.
    14. Möller, Bernd, 2006. "Changing wind-power landscapes: regional assessment of visual impact on land use and population in Northern Jutland, Denmark," Applied Energy, Elsevier, vol. 83(5), pages 477-494, May.
    15. Jacinto Garrido-Velarde & María Jesús Montero-Parejo & Julio Hernández-Blanco & Lorenzo García-Moruno, 2018. "Visual Analysis of the Height Ratio between Building and Background Vegetation. Two Rural Cases of Study: Spain and Sweden," Sustainability, MDPI, Open Access Journal, vol. 10(8), pages 1-17, July.
    16. Sunak, Yasin & Madlener, Reinhard, 2014. "Local Impacts of Wind Farms on Property Values: A Spatial Difference-in-Differences Analysis," FCN Working Papers 1/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Oct 2014.
    17. Manchado, Cristina & Gomez-Jauregui, Valentin & Lizcano, Piedad E. & Iglesias, Andres & Galvez, Akemi & Otero, Cesar, 2019. "Wind farm repowering guided by visual impact criteria," Renewable Energy, Elsevier, vol. 135(C), pages 197-207.
    18. Griffin, Robert & Chaumont, Nicolas & Denu, Douglas & Guerry, Anne & Kim, Choong-Ki & Ruckelshaus, Mary, 2015. "Incorporating the visibility of coastal energy infrastructure into multi-criteria siting decisions," Marine Policy, Elsevier, vol. 62(C), pages 218-223.
    19. Jallouli, J. & Moreau, G., 2009. "An immersive path-based study of wind turbines' landscape: A French case in Plouguin," Renewable Energy, Elsevier, vol. 34(3), pages 597-607.
    20. Wróżyński, Rafał & Sojka, Mariusz & Pyszny, Krzysztof, 2016. "The application of GIS and 3D graphic software to visual impact assessment of wind turbines," Renewable Energy, Elsevier, vol. 96(PA), pages 625-635.
    21. Molnarova, Kristina & Sklenicka, Petr & Stiborek, Jiri & Svobodova, Kamila & Salek, Miroslav & Brabec, Elizabeth, 2012. "Visual preferences for wind turbines: Location, numbers and respondent characteristics," Applied Energy, Elsevier, vol. 92(C), pages 269-278.
    22. Torres Sibille, Ana del Carmen & Cloquell-Ballester, Víctor-Andrés & Cloquell-Ballester, Vicente-Agustín & Darton, Richard, 2009. "Development and validation of a multicriteria indicator for the assessment of objective aesthetic impact of wind farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 40-66, January.
    23. Jones, Christopher R. & Richard Eiser, J., 2010. "Understanding 'local' opposition to wind development in the UK: How big is a backyard?," Energy Policy, Elsevier, vol. 38(6), pages 3106-3117, June.
    24. Chiabrando, Roberto & Fabrizio, Enrico & Garnero, Gabriele, 2011. "On the applicability of the visual impact assessment OAISPP tool to photovoltaic plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 845-850, January.

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