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Quantifying visual landscape quality in rural Wales: A GIS-enabled method for extensive monitoring of a valued cultural ecosystem service

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  • Swetnam, R.D.
  • Harrison-Curran, S.K.
  • Smith, G.R.

Abstract

Landscape views and the enjoyment people derive from them, represent an important cultural ecosystem service (CES) as recognised in frameworks such as the Millennium Ecosystem Assessment (2005) and TEEB (2010). We present a method to evaluate the quality of the landscape view, created for the assessment and monitoring of Welsh rural landscapes. This consists of: (i) a Visual Quality Index (VQI) and (ii) a viewshed model to calculate a Zone of Visual Influence (ZVI). From existing literature, we selected 19 landscape components commonly found to influence landscape quality ratings. Using vegetation surveys and GIS datasets each component was measured and assigned a numeric value based either on presence or quantity and/or extent for 150, 1km2 survey sites across Wales. Totalling these values, then scaling and weighting them provided an index for each site between 0 and 1 (VQI). Each site was then evaluated for a range of potential users (pedestrians, cyclists, car-users) to calculate a modelled viewshed (ZVI). By combining the VQI and the ZVI, we capture two elements: firstly the intrinsic landscape quality (its aesthetics) and secondly, how much of the landscape can be seen by the public in order to enjoy the view.

Suggested Citation

  • Swetnam, R.D. & Harrison-Curran, S.K. & Smith, G.R., 2017. "Quantifying visual landscape quality in rural Wales: A GIS-enabled method for extensive monitoring of a valued cultural ecosystem service," Ecosystem Services, Elsevier, vol. 26(PB), pages 451-464.
    • Handle: RePEc:eee:ecoser:v:26:y:2017:i:pb:p:451-464
    DOI: 10.1016/j.ecoser.2016.11.004
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    References listed on IDEAS

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    Cited by:

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    2. Marina García-Llorente & Antonio J. Castro & Cristina Quintas-Soriano & Elisa Oteros-Rozas & Irene Iniesta-Arandia & José A. González & David García del Amo & Marta Hernández-Arroyo & Izaskun Casado-A, 2020. "Local Perceptions of Ecosystem Services Across Multiple Ecosystem Types in Spain," Land, MDPI, vol. 9(9), pages 1-20, September.
    3. Shulong Dong & Jiangming Ma & Yanhua Mo & Hao Yang, 2022. "GIS-Based Watershed Unit Forest Landscape Visual Quality Assessment in Yangshuo Section of Lijiang River Basin, China," Sustainability, MDPI, vol. 14(22), pages 1-28, November.
    4. Bin Wen & Jon Bryan Burley, 2020. "Expert Opinion Dimensions of Rural Landscape Quality in Xiangxi, Hunan, China: Principal Component Analysis and Factor Analysis," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    5. Xiaodong Xu & Jingping Liu & Ning Xu & Wei Wang & Hui Yang, 2018. "Quantitative Study on the Evolution Trend and Driving Factors of Typical Rural Spatial Morphology in Southern Jiangsu Province, China," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
    6. Vieira, Felipe A.S. & Bragagnolo, Chiara & Correia, Ricardo A. & Malhado, Ana C.M. & Ladle, Richard J., 2018. "A salience index for integrating multiple user perspectives in cultural ecosystem service assessments," Ecosystem Services, Elsevier, vol. 32(PB), pages 182-192.
    7. Federico Benjamín Galacho-Jiménez & Pablo Quesada-Molina & David Carruana-Herrera & Sergio Reyes-Corredera, 2022. "Application of the Analysis Time Series and Multispectral Images for the Estimation of the Conditions of the Vegetation Covers of the Natural Areas of Southern Spain," Land, MDPI, vol. 12(1), pages 1-33, December.
    8. Karasov, Oleksandr & Heremans, Stien & Külvik, Mart & Domnich, Artem & Burdun, Iuliia & Kull, Ain & Helm, Aveliina & Uuemaa, Evelyn, 2022. "Beyond land cover: How integrated remote sensing and social media data analysis facilitates assessment of cultural ecosystem services," Ecosystem Services, Elsevier, vol. 53(C).

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