319
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

A saliency mapping approach to understanding the visual impact of wind and solar infrastructure in amenity landscapes

, ORCID Icon, ORCID Icon & ORCID Icon
Pages 154-161 | Received 23 Jun 2022, Accepted 12 Jan 2023, Published online: 01 Feb 2023

References

  • Alphan H. 2021. Modelling potential visibility of wind turbines: a geospatial approach for planning and impact mitigation. Renew Sustain Energy Rev. 152(May):111675. doi:10.1016/j.rser.2021.111675.
  • Balomenou N, Garrod B. 2019. Photographs in tourism research: prejudice, power, performance and participant-generated images. Tour Manag. 70(April2018):201–217. doi:10.1016/j.tourman.2018.08.014.
  • Beer M, Rybár R, Kaľavský M. 2018. Renewable energy sources as an attractive element of industrial tourism. Curr Issues Tour. 21(18):2147–2159. doi:10.1080/13683500.2017.1316971.
  • Bishop ID. 2019. Evidence synthesis in landscape aesthetics: an honourable endeavour yet insufficient applicable knowledge. Socio-Ecol Pract Res. 1(2):93–108. doi:10.1007/s42532-019-00011-9.
  • Bishop ID, Miller DR. 2007. Visual assessment of off-shore wind turbines: the influence of distance, contrast, movement and social variables. Renew Energy. 32(5):814–831. doi:10.1016/j.renene.2006.03.009.
  • Calvert K, Smit E, Wassmansdorf D, Smithers J. 2021. Energy transition, rural transformation and local land-use planning: insights from Ontario, Canada. Environ Plan E Nature Space. 5:251484862110249. doi:10.1177/25148486211024909.
  • Chen Y, Sherren K, Smit M, Lee KY. 2021. Using social media images as data in social science research. New Media Soc. 146144482110387. doi:10.1177/14614448211038761.
  • Corry RC. 2011. A case study on visual impact assessment for wind energy development. Impact Assess Proj Apprais. 29(4):303–315.
  • Dai K, Bergot A, Liang C, Xiang WN, Huang Z. 2015. Environmental issues associated with wind energy - A review. Renew Energy. 75:911–921. doi:10.1016/j.renene.2014.10.074
  • de Sousa AJG, Kastenholz E. 2015. Wind farms and the rural tourism experience – problem or possible productive integration? The views of visitors and residents of a Portuguese village. J Sustain Tour. 23(8–9):1236–1256. doi:10.1080/09669582.2015.1008499.
  • Dougherty PH. 2012. The Geography of Wine. Geogr Wine. doi:10.1007/978-94-007-0464-0.
  • Dupont L, Ooms K, Antrop M, van Eetvelde V. 2016. Comparing saliency maps and eye-tracking focus maps: the potential use in visual impact assessment based on landscape photographs. Landsc Urban Plan. 148:17–26. doi:10.1016/j.landurbplan.2015.12.007
  • Dupont L, Ooms K, Antrop M, van Etvelde V. 2017. Testing the validity of a saliency-based method for visual assessment of constructions in the landscape. Landsc Urban Plan. 167(June):325–338. doi:10.1016/j.landurbplan.2017.07.005.
  • Fergen J, Jacquet J. 2016. Beauty in motion: expectations, attitudes, and values of wind energy development in the rural U.S. Energy Res Soc Sci. 11:133–141. doi:10.1016/j.erss.2015.09.003
  • Fooks JR, Messer KD, Duke JM, Johnson JB, Li T, Parsons GR. 2017. Tourist viewshed externalities and wind energy production. Agric Resour Econ Rev. 46(2):224–241. doi:10.1017/age.2017.18.
  • Frantál B, Kunc J. 2011. Wind turbines in tourism landscapes: czech Experience. Ann Tour Res. 38(2):499–519. doi:10.1016/j.annals.2010.10.007.
  • Fu H, Zhu H, Xue P, Hu X, Guo X, Liu B. 2022. Eye-tracking study of public acceptance of 5G base stations in the context of the COVID-19 pandemic. Eng Construct Architect Manag. ahead-of-print. doi:10.1108/ECAM-10-2021-0946.
  • Grima Murcia MD, Sánchez Ferrer F, Sorinas J, Ferrandez JM, Fernandez E. 2017. Application of electroencephalographic techniques to the study of visual impact of renewable energies. J Environ Manage. 200:484–489. doi:10.1016/j.jenvman.2017.05.096
  • Harel J, Koch C, Perona P. 2006. Graph-based visual saliency. Proce Neural Infor- Mat Proces Syst. 19:545–552.
  • Hasan A, Megantara EN, Withaningsih S, Supyandi D, Utama GL, Malik AD. 2021. The public participation shifting of environmental impact assessment during Covid-19 Outbreak. E3S Web Conf. 249:01009. doi:10.1051/e3sconf/202124901009.
  • Ioannidis R, Koutsoyiannis D. 2020. A review of land use, visibility and public perception of renewable energy in the context of landscape impact. Appl Energy. 276(August):115367. doi:10.1016/j.apenergy.2020.115367.
  • Itti L, Koch C, Niebur E. 1998. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis. Hist Econ Soc Bull. 20(2):1254–1259. doi:10.1017/S1042771600010292.
  • Jovanovic M, Campbell M. 2022. Generative Artificial Intelligence: trends and Prospects. Computer. 55(10):107–112. doi:10.1109/MC.2022.3192720.
  • Langbroek M, Vanclay F. 2012. Learning from the social impacts associated with initiating a windfarm near the former island of Urk, The Netherlands. Impact Assess Proj Apprais. 30(3):167–178. doi:10.1080/14615517.2012.706943.
  • Lei L, Hilton B. 2013. A spatially intelligent public participation system for the environmental impact assessment process. ISPRS Int J Geo-Inf. 2(2):480–506. doi:10.3390/ijgi2020480.
  • Li Y, Gao X, Huang J, Wu M. 2020. Visual behavior analysis of tourists based on photography and eye-tracking experiment-a case of Xiamen University. Tour Tribune. 35(9):41–52.
  • Liu D, Upchurch RS. 2020. A glimpse into energy tourism via application of eye-tracking technology. J Leis Res. 51(2):230–244. doi:10.1080/00222216.2019.1649098.
  • Lothian A. 2008. Scenic perceptions of the visual effects of wind farms on South Australian landscapes. Geogr Res. 46(2):196–207. doi:10.1111/j.1745-5871.2008.00510.x.
  • Maslov N, Claramunt C, Wang T, Tang T. 2017. Method to estimate the visual impact of an offshore wind farm. Appl Energy. 204:1422–1430. doi:10.1016/j.apenergy.2017.05.053
  • McCarthy J. 2015. A socioecological fix to capitalist crisis and climate change? The possibilities and limits of renewable energy. Environ Plan A Econom Space. 47(12):2485–2502. doi:10.1177/0308518X15602491.
  • Misthos L-M, Menegaki M. 2021. Novel techniques for anticipating the focus of visual attention across different mining landscapes. Mater Proce. 5(1):20. doi:10.3390/materproc2021005020.
  • Mohammadi M. 2021. Landscape discourses of amenity and renewable energy development in viticulture regions in Canada. MES thesis, Dalhousie University; [accessed 2023 Jan 12]. https://dalspace.library.dal.ca/handle/10222/81114
  • Molnarova K, Sklenicka P, Stiborek J, Svobodova K, Salek M, Brabec E. 2012. Visual preferences for wind turbines: location, numbers and respondent characteristics. Appl Energy. 92:269–278. doi:10.1016/j.apenergy.2011.11.001.
  • Muthoora T, Fischer TB. 2019. Power and perception - from paradigms of specialist disciplines and opinions of expert groups to an acceptance for the planning of onshore windfarms in England. Land Use Policy. 89:104198. doi:10.1016/j.landusepol.2019.104198
  • Palmer JF. 2015. Effect size as a basis for evaluating the acceptability of scenic impacts: ten wind energy projects from Maine, USA. Landsc Urban Plan. 140:56–66. doi:10.1016/j.landurbplan.2015.04.004
  • Pedersen E, Larsman P. 2008. The impact of visual factors on noise annoyance among people living in the vicinity of wind turbines. J Environ Psychol. 28(4):379–389. doi:10.1016/j.jenvp.2008.02.009.
  • Poggi F, Firmino A, Amado M. 2018. Planning renewable energy in rural areas: impacts on occupation and land use. Energy. 155:630–640. doi:10.1016/j.energy.2018.05.009.
  • Rid W, Ezeuduji IO, Pröbstl-Haider U. 2014. Segmentation by motivation for rural tourism activities in The Gambia. Tour Manag. 40(2014):102–116. doi:10.1016/j.tourman.2013.05.006.
  • Sæþórsdóttir AD, Ólafsdóttir R. 2020. Not in my back yard or not on my playground: residents and tourists’ attitudes towards wind turbines in Icelandic landscapes. Energy Sustain Dev. 54:127–138. doi:10.1016/j.esd.2019.11.004
  • Salak B, Lindberg K, Kienast F, Hunziker M. 2021. How landscape-technology fit affects public evaluations of renewable energy infrastructure scenarios. A hybrid choice model. Renew Sustain Energy Rev. 143:110896. doi:10.1016/j.rser.2021.110896
  • Schirpke U, Tasser E, Lavdas AA, Wan J-Z. 2022. Potential of eye-tracking simulation software for analyzing landscape preferences. PLoS ONE. 17(10):e0273519. doi:10.1371/journal.pone.0273519.
  • Scott N, Le D, Becken S, Connolly RM. 2020. Measuring perceived beauty of the Great Barrier Reef using eye-tracking technology. Curr Issues Tour. 23(20):2492–2502. doi:10.1080/13683500.2019.1626812.
  • Sherren K, Chen Y, Mohammadi M, Zhao Q, Gone KP, Rahman HMT, Smit M. 2019. Social media and social impact assessment: evolving methods in a shifting context. In consideration for special issue of Current Sociology. Br J Educ Technol. 50(3):987–1004.
  • Sherren K, Parkins JR, Owen T, Terashima M. 2019. Does noticing energy infrastructure influence public support for energy development? Evidence from a national survey in Canada. Energy Res Soc Sci. 51:176–186. doi:10.1016/j.erss.2019.01.014.
  • Sherren K, Parkins JR, Smit M, Holmlund M, Chen Y. 2017. Digital archives, big data and image-based culturomics for social impact assessment: opportunities and challenges. Environ Impact Assess Rev. 67:23–30. doi:10.1016/j.eiar.2017.08.002.
  • Sinclair AJ, Peirson-Smith TJ, Boerchers M. 2017. Environmental assessments in the Internet age: the role of e-governance and social media in creating platforms for meaningful participation. Impact Assess Proj Apprais. 35(2):148–157. doi:10.1080/14615517.2016.1251697.
  • Smythe T, Bidwell D, Moore A, Smith H, McCann J. 2020. Beyond the beach: tradeoffs in tourism and recreation at the first offshore wind farm in the United States. Energy Res Soc Sci. 70(August):101726. doi:10.1016/j.erss.2020.101726.
  • Spielhofer R, Hunziker M, Kienast F, Wissen Hayek U, Grêt-Regamey A. 2021. Does rated visual landscape quality match visual features? An analysis for renewable energy landscapes. Landsc Urban Plan. 209(January):104000. doi:10.1016/j.landurbplan.2020.104000.
  • Wissen Hayek U, Müller K, Göbel F, Kiefer P, Spielhofer R, Grêt-Regamey A. 2019. 3D point clouds and eye tracking for investigating the perception and acceptance of power lines in different landscapes. Multimodal Technol Interact. 3(2):40. doi:10.3390/mti3020040.
  • Wrózyński R, Sojka M, Pyszny K. 2016. The application of GIS and 3D graphic software to visual impact assessment of wind turbines. Renew Energy. 96(A):625–635. doi:10.1016/j.renene.2016.05.016.
  • Xu R, Wittkopf S. 2015. Visual assessment of BIPV retrofit design proposals for selected historical buildings using the saliency map method. J Facade Des Eng. 2(3–4):235–254. doi:10.3233/fde-150022.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.