The assessment of scenic attractiveness on coastal ways: a case study of Persembe-Bolaman (Ordu-Turkey)
Abstract
The biophysical characteristics of the areas that can be seen while travelling on motorways have an impact on the perception of the landscape. Highways provide diverse landscape experiences to travellers according to their natural and cultural qualities. Especially coastal ways that combine with nature and the sea have a high potential for scenic attractiveness. This study aims to analyse the scenic attractiveness of coastal ways using GIS and RS techniques. Persembe-Bolaman coastal way in the Black Sea Region of Turkey was selected as a case study. Three road features and seven viewshed features that are assumed to affect landscape attractiveness on the Persembe-Bolaman coastal road were selected. The data set of these features was categorised into three clusters by k-means clustering, one of the unsupervised learning algorithms. The most attractive cluster in terms of scenic attractiveness was selected by determining the characteristics of the clusters. In conclusion, it was found that the scenic attractiveness was the highest in Cluster-1, which corresponds to 46.3% of the selected route.
Keyword : coastal way, GIS, k-means clustering, remote sensing, scenic attractiveness
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alibuhtto, M., & Mahat, N. (2020). Distance based k-means clustering algorithm for determining number of clusters for high dimensional data. Decision Science Letters, 9, 51–58. https://doi.org/10.5267/j.dsl.2019.8.002
Arriaza, M., Cañas, J. F., Cañas, J. A., & Ruiz-Aviles, P. (2004). Assessing the visual quality of rural landscapes. Landscape and Urban Planning, 69(1), 115–125. https://doi.org/10.1016/j.landurbplan.2003.10.029
Beddows, D., Dall’Osto, M., & Harrison, R. (2009). Cluster analysis of rural, urban, and curbside atmospheric particle size data. Environmental Science & Technology, 43(13), 4694–4700. https://doi.org/10.1021/es803121t
Bishop, I. D. (1996). Comparing regression and neural net-based approaches to modelling of scenic beauty. Landscape and Urban Planning, 34(2), 125–134. https://doi.org/10.1016/0169-2046(95)00210-3
Bishop, I. D., & Miller, D. R. (2007). Visual assessment of off-shore wind turbines: The influence of distance, contrast, movement and social variables. Renewable Energy, 32(5), 814–831. https://doi.org/10.1016/j.renene.2006.03.009
Bishop, I. D., Wherrett, J. R., & Miller, D. R. (2000). Using image depth variables as predictors of visual quality. Environment and Planning B: Planning and Design, 27(6), 865–875. https://doi.org/10.1068/b26101
Blumentrath, C., & Tveit, M. S. (2014). Visual characteristics of roads: A literature review of people’s perception and Norwegian design practice. Transportation Research Part A: Policy and Practice, 59, 58–71. https://doi.org/10.1016/j.tra.2013.10.024
Bulut, Z., & Yilmaz, H. (2008). Determination of landscape beauties through visual quality assessment method: A case study for Kemaliye (Erzincan/Turkey). Environmental Monitoring and Assessment, 141(1–3), 121–129. https://doi.org/10.1007/s10661-007-9882-0
Cañas, I., Ayuga, E., & Ayuga, F. A. (2009). A contribution to the assessment of scenic quality of landscapes based on preferences expressed by the public. Land Use Policy, 26, 1173–1181. https://doi.org/10.1016/j.landusepol.2009.02.007
Charrad, M., Ghazzali, N., Boiteau, V., & Niknafs, A. (2014). NbClust: An R package for determining the relevant number of clusters in a data set. Journal of Statistical Software, 61, 1–36. https://doi.org/10.18637/jss.v061.i06
Chhetri, P. (2006). Modelling the attractiveness potential of scenic views: A case study of the Grampians National Park, Australia. Tourism Recreation Research, 31(3), 101–107. https://doi.org/10.1080/02508281.2006.11081512
Chhetri, P., & Arrowsmith, C. (2003). Mapping the potential of scenic views for the Grampians National Park. In Proceeding of the 21st International Cartographic Conference (pp. 1859–1871), Durban, South Africa.
Chhetri, P., & Arrowsmith, C. (2008). GIS-based modelling of recreational potential of nature-based tourist destinations. Tourism Geographies, 10(2), 233–257. https://doi.org/10.1080/14616680802000089
Churchward, C., Palmer, J. F., Nassauer, J. I., & Swanwick, C. A. (2013). Evaluation of methodologies for visual impact assessments. NCHRP. https://doi.org/10.17226/22644
Daniel, T. C. (2001). Whither scenic beauty? Visual landscape quality assessment in the 21st century. Landscape and Urban Planning, 54(1–4), 267–281. https://doi.org/10.1016/S0169-2046(01)00141-4
De Almeida Rodrigues, A., da Cunha Bustamante, M. M., & Sano, E. E. (2018). As far as the eye can see: Scenic view of Cerrado National Parks. Perspectives in Ecology and Conservation, 16(1), 31–37. https://doi.org/10.1016/j.pecon.2017.11.004
De Vries, S., Lankhorst, J. R. K., & Buijs, A. E. (2007). Mapping the attractiveness of the dutch countryside: A GIS-based landscape appreciation model. Forest Snow and Landscape Research, 81(1/2), 43–58.
Dupont, L., Ooms, K., Antrop, M., & Van Eetvelde, V. (2017). Testing the validity of a saliency-based method for visual assessment of constructions in the landscape. Landscape and Urban Planning, 167, 325–338. https://doi.org/10.1016/j.landurbplan.2017.07.005
Fambro, D. B., Fitzpatrick, K., & Koppa, R. J. (1997). Determination of stopping sight distances. Transportation Research Board.
Fatemi, M., & Narangifard, M. (2019). Monitoring LULC changes and its impact on the LST and NDVI in District 1 of Shiraz City. Arabian Journal of Geosciences, 12(4), 1–12. https://doi.org/10.1007/s12517-019-4259-6
García-Rubio, J., Carreras, D., Molina, S., Medina, A., & Godoy, S. (2020). Citius, altius, fortius; is it enough to achieve success in basketball. International Journal of Environmental Research and Public Health, 17(20), Article 7355. https://doi.org/10.3390/ijerph17207355
Garré, S., Meeus, S., & Gulinck, H. (2009). The dual role of roads in the visual landscape: A case-study in the area around Mechelen (Belgium). Landscape and Urban Planning, 92(2), 125–135. https://doi.org/10.1016/j.landurbplan.2009.04.001
Gobster, P. H., Ribe, R. G., & Palmer, J. F. (2019). Themes and trends in visual assessment research. Landscape and Urban Planning, 191, Article 103635. https://doi.org/10.1016/j.landurbplan.2019.103635
Gounaridis, D., & Zaimes, G. (2012). GIS-based multicriteria decision analysis applied for environmental issues; the Greek experience. International Journal of Applied Environmental Sciences, 7, 307–321.
Gungor, S., & Polat, A. T. (2018). Relationship between visual quality and landscape characteristics in urban parks. Journal of Environmental Protection and Ecology, 19(2), 939–948.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction. Springer. https://doi.org/10.1007/978-0-387-84858-7
Healthline. (2022). How far can we see and why? https://www.healthline.com/health/how-far-can-the-human-eye-see
Hobbs, F. D. (2016). Traffic planning and engineering: Pergamon international library of science, technology, engineering and social studies. Elsevier.
Jovanovska, D., Swetnam, R. D., Tweed, F. S., & Melovski, L. (2020). Assessing the landscape visual quality of Shar Planina, North Macedonia. Landscape Ecology, 35(12), 2805–2823. https://doi.org/10.1007/s10980-020-01122-5
Kapitaniak, B., Walczak, M., Kosobudzki, M., Jóźwiak, Z., & Bortkiewicz, A. (2015). Application of eye-tracking in drivers testing: A review of research. International Journal of Occupational Medicine and Environmental Health, 28(6), 941–954. https://doi.org/10.13075/ijomeh.1896.00317
Kassambara, A., & Mundt, F. (2017). Package ‘factoextra’: Extract and visualize the results of multivariate data analyses. http://cran.nexr.com/web/packages/factoextra/factoextra.pdf
Kaur, J. (1981). Methodological approach to scenic resource assessment. Tourism Recreation Research, 6(1), 19–22. https://doi.org/10.1080/02508281.1981.11015025
Lew, A. A. (1991). Scenic roads and rural development in the US. Tourism Recreation Research, 16(2), 23–30. https://doi.org/10.1080/02508281.1991.11014623
Li, C., Shen, S., & Ding, L. (2020). Evaluation of the winter landscape of the plant community of urban park green spaces based on the scenic beauty esitimation method in Yangzhou, China. PloS One, 15(10), Article e0239849. https://doi.org/10.1371/journal.pone.0239849
Lindemann-Matthies, P., & Bose, E. (2007). Species richness, structural diversity and species composition in meadows created by visitors of a botanical garden in Switzerland. Landscape and Urban Planning, 79(3–4), 298–307. https://doi.org/10.1016/j.landurbplan.2006.03.007
Lindemann-Matthies, P., Briegel, R., Schüpbach, B., & Junge, X. (2010). Aesthetic preference for a Swiss alpine landscape: The impact of different agricultural land-use with different biodiversity. Landscape and Urban Planning, 98(2), 99–109. https://doi.org/10.1016/j.landurbplan.2010.07.015
Maison, M., Darmaji, D., Kurniawan, D. A., Astalini, A., Kuswanto, K., & Ningsi, A. P. (2021). Correlation of science process skills on critical thinking skills in junior high school in Jambi City. Jurnal Penelitian Fisika dan Aplikasinya (JPFA), 11(1), 29–38. https://doi.org/10.26740/jpfa.v11n1.p29-38
Martín, B., Arce, R., Otero, I., & Loro, M. (2018). Visual landscape quality as viewed from motorways in Spain. Sustainability, 10(8), Article 2592. https://doi.org/10.3390/su10082592
Martín, B., Ortega, E., Otero, I., & Arce, R. M. (2016). Landscape character assessment with GIS using map-based indicators and photographs in the relationship between landscape and roads. Journal of Environmental Management, 180, 324–334. https://doi.org/10.1016/j.jenvman.2016.05.044
Möller, B. (2006). Changing wind-power landscapes: Regional assessment of visual impact on land use and population in Northern Jutland, Denmark. Applied Energy, 83(5), 477–494. https://doi.org/10.1016/j.apenergy.2005.04.004
Mooser, A., Anfuso, G., Stanchev, H., Stancheva, M., Williams, A. T., & Aucelli, P. P. (2022). Most attractive scenic sites of the Bulgarian Black Sea coast: Characterization and sensitivity to natural and human factors. Land, 11(1), Article 70. https://doi.org/10.3390/land11010070
Newman, M. (2002). Assortative mixing in networks. Physical Review Letters, 89(20), Article 208701. https://doi.org/10.1103/PhysRevLett.89.208701
Ode, Å., Tveit, M. S., & Fry, G. (2010). Advantages of using different data sources in assessment of landscape change and its effect on visual scale. Ecological Indicators, 10, 24–31. https://doi.org/10.1016/j.ecolind.2009.02.013
Omran, M. G., Engelbrecht, A. P., & Salman, A. (2007). An overview of clustering methods. Intelligent Data Analysis, 11(6), 583–605. https://doi.org/10.3233/IDA-2007-11602
Pettorelli, N., Vik, J. O., Mysterud, A., Gaillard, J. M., Tucker, C. J., & Stenseth, N. C. (2005). Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution, 20(9), 503–510. https://doi.org/10.1016/j.tree.2005.05.011
Pierskalla, C., Deng, J., & Siniscalchi, J. (2016). Examining the product and process of scenic beauty evaluations using moment-to-moment data and GIS: The case of Savannah, GA. Urban Forestry & Urban Greening, 19, 212–222. https://doi.org/10.1016/j.ufug.2016.07.011
Purcell, A. T. (1992). Abstract and specific physical attributes and the experience of landscape. Journal of Environmental Management, 34(3), 159–177. https://doi.org/10.1016/S0301-4797(05)80149-5
QGIS Development Team. (2013). QGIS Geographic Information System. http://qgis.osgeo.org
R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.r-project.org
Real, E., Arce, C., & Sabucedo, J. M. (2000). Classification of landscapes using quantitative and categorical data, and prediction of their scenic beauty in North-Western Spain. Journal of Environmental Psychology, 20(4), 355–373. https://doi.org/10.1006/jevp.2000.0184
Rodrigues, M., Montañés, C., & Fueyo, N. (2010). A method for the assessment of the visual impact caused by the large-scale deployment of renewable-energy facilities. Environmental Impact Assessment Review, 30(4), 240–246. https://doi.org/10.1016/j.eiar.2009.10.004
Schirpke, U., Hölzler, S., Leitinger, G., Bacher, M., Tappeiner, U., & Tasser, E. (2013a). Can we model the scenic beauty of an Alpine landscape? Sustainability, 5(3), 1080–1094. https://doi.org/10.3390/su5031080
Schirpke, U., Tasser, E., & Tappeiner, U. (2013b). Predicting scenic beauty of mountain regions. Landscape and Urban Planning, 111, 1–12. https://doi.org/10.1016/j.landurbplan.2012.11.010
Sezen, I., & Yilmaz, S. (2010). Public opinions about the use of highways as scenic roads: The sample of Erzurum-Çaykara-Of route. African Journal of Agricultural Research, 5(8), 700–706.
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Sinaga, K. P., & Yang, M. S. (2020). Unsupervised k-means clustering algorithm. IEEE Access, 8, 80716–80727. https://doi.org/10.1109/ACCESS.2020.2988796
Sirait, K., & Nababan, E. (2017). K-means algorithm performance analysis with determining the value of starting centroid with random and KD-Tree method. Journal of Physics Conference Series, 930, Article 012016. https://doi.org/10.1088/1742-6596/930/1/012016
Son, W. J., & Cho, I. S. (2022). Analysis of trends in mega-sized container ships using the k-means clustering algorithm. Applied Sciences, 12(4), Article 2115. https://doi.org/10.3390/app12042115
Svobodova, K., Sklenicka, P., Molnarova, K., & Salek, M. (2012). Visual preferences for physical attributes of mining and post-mining landscapes with respect to the sociodemographic characteristics of respondents. Ecological Engineering, 43, 34–44. https://doi.org/10.1016/j.ecoleng.2011.08.007
Tan, X., & Peng, Y. (2020). Scenic beauty evaluation of plant landscape in Yunlong Lake Wetland Park of Xuzhou City, China. Arabian Journal of Geosciences, 13(15), 1–9. https://doi.org/10.1007/s12517-020-05626-x
Tempesta, T. (2010). The perception of agrarian historical landscapes: A study of the Veneto Plain in Italy. Landscape and Urban Planning, 97(4), 258–272. https://doi.org/10.1016/j.landurbplan.2010.06.010
Tessema, G., Poesen, J., Verstraeten, G., Rompaey, A., & Borg, J. (2021). The scenic beauty of geosites and its relation to their scientific value and geoscience knowledge of tourists: A case study from southeastern Spain. Land, 10(5), Article 460. https://doi.org/10.3390/land10050460
The American Association of State Highway and Transportation Officials. (2001). A policy on geometric design of highways and streets (4th ed.). Washington DC.
The American Association of State Highway and Transportation Officials. (2011). A policy on geometric design of highways and streets (6th ed.). Washington DC.
The Jamovi Project. (2021). Jamovi (Version 1.6). https://www.jamovi.org
Todd, J., Bui, Y., Tavassoli, A., & Krauss, D. (2017). Quantitative method for estimating driver eye height. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 61(1), 1443–1446. https://doi.org/10.1177/1541931213601846
Tsoutsos, T., Tsouchlaraki, A., Tsiropoulos, M., & Serpetsidakis, M. (2009). Visual impact evaluation of a wind park in a Greek island. Applied Energy, 86(4), 546–553. https://doi.org/10.1016/j.apenergy.2008.08.013
Tveit, M. S., Ode Sang, Å., & Hagerhall, C. M. (2018). Scenic beauty: Visual landscape assessment and human landscape perception. Wiley. https://doi.org/10.1002/9781119241072.ch5
U. S. Geological Survey. (2023). LP DAAC – ASTGTM. https://lpdaac.usgs.gov/products/astgtmv003
Uzun, O., & Muderrisoglu, H. (2011). Visual landscape quality in landscape planning: Examples of Kars and Ardahan cities in Turkey. African Journal of Agricultural Research, 6(6), 1627–1638.
Vugule, K., & Turlaja, R. (2016). Scenic roads in Latvia. Research for Rural Development, 1, 182–188.
Vukomanovic, J., Singh, K. K., Petrasova, A., & Vogler, J. B. (2018). Not seeing the forest for the trees: Modeling exurban viewscapes with LiDAR. Landscape and Urban Planning, 170, 169–176. https://doi.org/10.1016/j.landurbplan.2017.10.010
Yuan, Y., & Cheng, Y. (2017). Road planning for a scenic environment based on the Dijkstra algorithm: Case study of Nanjing Niushou Mountain Scenic Spot in China. Journal of Digital Landscape Architecture, 2, 162–173.
Zha, Y., Gao, J., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24(3), 583–594. https://doi.org/10.1080/01431160304987