PREDICTING VISUAL AESTHETIC PREFERENCES OF LANDSCAPES NEAR HISTORICAL SITES BY FLUENCY THEORY USING SOCIAL MEDIA DATA AND GIS

Yıl 2021, Sayı: 43, 265 - 277, 26.01.2021

Derya Gülçin

https://doi.org/10.32003/igge.811658

Cited By: 2

Öz

There is an interactive relationship between humans and landscapes. Humans inherently assess landscapes by creating spontaneous preferences based on surrounding stimuli. Vision plays a key role in these preferences. Visual preferences are relevant for understanding visual aesthetic liking (VAL), which needs to be evaluated objectively. This study was carried out in Herakleia ad Latmos, comprising Lake Bafa Natural Park and the Latmos-Beşparmak Mountains. The aim of this paper is to predict people’s VAL of historical sites (HS) by applying processing fluency theory to social media data. Among fluency theory metrics, four metrics – visual simplicity, visual symmetry, visual contrast, and visual self-similarity, were used to develop an ordinary least squares (OLS) regression model. Two primary questions are explored in this study: (1) How to quantify spontaneous visits of people near historical sites, and (2) how to estimate preferences of people based on distances to HS regardless of landscape types (either cultural or natural). Results show that people mostly visited three HS out of thirteen historical sites between 2004 and 2020: Kapıkırı Island (HS 1), and the ancient cities of Herakleia (HS 2) and Latmos (HS 3). According to the findings of the OLS regression model, year (t = 8.99, p <.0001), visual simplicity (t = -4.64, p ≤ 0.0001), and visual contrast (t = -2.01, p = 0.04) of the geotagged photos were all statistically significant predictors of VAL. HS 2 had the highest VAL value, followed by HS 1, and HS 3.

Anahtar Kelimeler

Visual Aesthetic Liking, GIS, Fluency Theory Metrics, Historical Site, Latmos

PREDICTING VISUAL AESTHETIC PREFERENCES OF LANDSCAPES NEAR HISTORICAL SITES BY FLUENCY THEORY USING SOCIAL MEDIA DATA AND GIS

Öz

There is an interactive relationship between humans and landscapes. Humans inherently assess landscapes by creating spontaneous preferences based on surrounding stimuli. Vision plays a key role in these preferences. Visual preferences are relevant for understanding visual aesthetic liking (VAL), which needs to be evaluated objectively. This study was carried out in Herakleia ad Latmos, comprising Lake Bafa Natural Park and the Latmos-Beşparmak Mountains. The aim of this paper is to predict people’s VAL of historical sites (HS) by applying processing fluency theory to social media data. Among fluency theory metrics, four metrics – visual simplicity, visual symmetry, visual contrast, and visual self-similarity, were used to develop an ordinary least squares (OLS) regression model. Two primary questions are explored in this study: (1) How to quantify spontaneous visits of people near historical sites, and (2) how to estimate preferences of people based on distances to HS regardless of landscape types (either cultural or natural). Results show that people mostly visited three HS out of thirteen historical sites between 2004 and 2020: Kapıkırı Island (HS 1), and the ancient cities of Herakleia (HS 2) and Latmos (HS 3). According to the findings of the OLS regression model, year (t = 8.99, p <.0001), visual simplicity (t = -4.64, p ≤ 0.0001), and visual contrast (t = -2.01, p = 0.04) of the geotagged photos were all statistically significant predictors of VAL. HS 2 had the highest VAL value, followed by HS 1, and HS 3. 

Anahtar Kelimeler

Visual Aesthetic Liking, GIS, Fluency Theory Metrics, Historical Site, Latmos

Teşekkür

Special thanks to Prof. Dr. Stefan Mayer and Prof. Dr. Jan Landwehr for their support to calculate fluency metrics. I thank you so much to Dr. Ian Bercovitz for checking the results of the OLS regression model used in this study. I would also like to express my gratitude to Dr. Stephen J. Jordan for revising the manuscript and his valuable comments. Thanks to Yalçın Gülçin for sharing his extensive knowledge about the historical sites.

Kaynakça

• Arriaza, M., Cañas-Ortega, J. F., Cañas-Madueño, J. A. & Ruiz-Aviles, P. (2004). Assessing the visual quality of rural landscapes. Landscape and Urban Planning, 69(1), 115-125.
• Arslan, E.S. & Örücü, Ö.K. (2020a). Kültürel ekosistem hizmetlerinin sosyal medya fotoğrafları kullanılarak modellenmesi: Eskişehir örneği. Türkiye Ormancılık Dergisi, 21(1), 94-105.
• Arslan, E.S. & Örücü, Ö.K. (2020b). MaxEnt modelling of the potential distribution areas of cultural ecosystem services using social media data and GIS. Environment, Development and Sustainability, 1-13.
• Atik, M., Işıklı, R. C., Ortaçeşme, V. & Yıldırım, E. (2017). Exploring a combination of objective and subjective assessment in landscape classification: Side case from Turkey. Applied Geography, 83, 130-140.
• Barromi-Perlman, E. (2020). Visions of landscape photography in Palestine and Israel. Landscape Research, 45(5), 564-582.
• Berlyne, D. E. (1974). Studies in the New Experimental Aesthetics: Steps Toward an Objective Psychology of Aesthetic Oppreciation. Washington, DC: Hemisphere Publishing Corporation. New York: John Wiley & Sons.
• Bruns, D., Kühne, O., Schönwald, A. & Theile, S. (2015). Landscape Culture-Culturing Landscapes: The Differentiated Construction of Landscapes. Wiesbaden, Germany: Springer.
• Daniel, T. C. (2001). Aesthetic preference and ecological sustainability. In S. Richard, J. Sheppard & H. W. Harshaw (Eds.), Advanced forests and landscape: linking ecology, sustainability and aesthetics (pp. 15-29). Wallingford: CABI Publishing.
• Day, H. Y. (1967). Evaluations of subjective complexity, pleasingness and interestingness for a series of random polygons varying in complexity. Perception and Psychophysics, 2(7), 281-286.
• Deniz, B., Kılıçaslan, Ç., Kara, B., Göktuğ, T. H. & Kutsal, E. (2011). Evaluation of the tourism potential of Besparmak Mountains in the respect of protection-use balance. Procedia-Social and Behavioral Sciences, 19, 250-257.
• DKMP, (2020). Korunan Alanlar-Bafa Gölü Tabiat Parkı. Doğa Koruma ve Milli Parklar Genel Müdürlüğü. Retrieved June 28, 2020, from http://bafagolu.tabiat.gov.tr/.
• Do, Y. & Kim, J. Y. (2020). An assessment of the aesthetic value of protected wetlands based on a photo content and its metadata. Ecological Engineering, 150.
• Esbah, H., Deniz, B., Kara, B. & Kesgin, B. (2010). Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics. Environmental Monitoring and Assessment, 165(1-4), 617-632.
• Filova, L., Vojar, J., Svobodova, K. & Sklenicka, P. (2015). The effect of landscape type and landscape elements on public visual preferences: ways to use knowledge in the context of landscape planning. Journal of Environmental Planning and Management, 58(11), 2037-2055.
• Fox, N., August, T., Mancini, F. Parks, K.E., Eigenbrod, F., Bullock, J.M., Sutter, L. & Graham, L.J. (2020). “photosearcher” package in R: An accessible and reproducible method for harvesting large datasets from Flickr. SoftwareX, 12, 100624.
• Freely, J., Biçen, A., Koca, G. & Birkan, T. (2003). Türkiye Uygarliklar Rehberi. İstanbul: Yapı Kredi Yayınları.
• Gosal, A. S. & Ziv, G. (2020). Landscape aesthetics: Spatial modelling and mapping using social media images and machine learning. Ecological Indicators, 117, 106638.
• Graf, L. K. & Landwehr, J. R. (2015). A dual-process perspective on fluency-based aesthetics: The pleasure-interest model of aesthetic liking. Personality and Social Psychology Review, 19(4), 395-410.
• Gül, M., Zorlu, K. & Gül, M. (2019). Assessment of mining impacts on environment in Muğla-Aydın (SW Turkey) using Landsat and Google Earth imagery. Environmental Monitoring and Assessment, 191(11), 655.
• Häfner, K., Zasada, I., van Zanten, B. T., Ungaro, F., Koetse, M. & Piorr, A. (2018). Assessing landscape preferences: a visual choice experiment in the agricultural region of Märkische Schweiz, Germany. Landscape Research, 43(6), 846-861.
• Herda, A., Brückner, H., Müllenhoff, M., & Knipping, M. (2019). From the Gulf of Latmos to Lake Bafa: on the history, geoarchaeology, and palynology of the lower Maeander Valley at the foot of the Latmos Mountains. Hesperia. The Journal of the American School of Classical Studies at Athens, 88(1), 1-86.
• Hetemoğlu, M. A. (2019). Interpretation and presentation of the Byzantine Heritage at 'Herakleia ad Latmos'. (Master's thesis, Middle East Technical University). Retrieved August 20, 2020 from http://etd.lib.metu.edu.tr/upload/12622991/index.pdf.
• Huang, A. S. H. & Lin, Y. J. (2020). The effect of landscape colour, complexity and preference on viewing behaviour. Landscape Research, 45(2), 214-227.
• Hülden, O. (2000). Pleistarchos und die Befestigungsanlagen von Herakleia am Latmos. Klio, 82(2), 382.
• Hülden, O. (2012). Herakleia by Latmos. In R. S. Bagnall, K. Brodersen, C. B. Champion (Eds.), Advanced the encyclopedia of ancient history (pp. 3139-3140). New Jersey: Blackwell Publising.
• Junker, B. & Buchecker, M. (2008). Aesthetic preferences versus ecological objectives in river restorations. Landscape and Urban Planning, 85(3-4), 141-154.
• Kane, P. S. (1981). Assessing landscape attractiveness: a comparative test of two new methods. Applied Geography, 1(2), 77-96.
• Kaplan, R., & Kaplan, S. (1989). The Experience of Nature: A Psychological Perspective. New York: Cambridge University Press.
• Kaymaz, I. C. (2012). Landscape perception. In M. Ozyavuz (Ed.), Advanced landscape planning (pp. 251-276). Rijeka: IntechOpen.
• Langemeyer, J., Calcagni, F. & Baró, F. (2018). Mapping the intangible: Using geolocated social media data to examine landscape aesthetics. Land Use Policy, 77, 542-552.
• Laroche, G., Domon, G., & Olivier, A. (2020). Exploring the social coherence of rural landscapes featuring agroforestry intercropping systems using locals’ visual assessments and perceptions. Sustainability Science, 15(5), 1337-1355.
• Lontai-Szilágyi, Z., Bertalan Balázs, B., Zsiros, B., Vasvári, M., Kumar, S. S., Nilanchal, P., Martonné Erdős, K. & Szabó, S. (2019). A novel approach of mapping landscape aesthetic value and its validation with rural tourism data. Hungarian Geographical Bulletin, 68(3), 283-301.
• Lothian, A. (1999). Landscape and the philosophy of aesthetics: is landscape quality inherent in the landscape or in the eye of the beholder?. Landscape and Urban Planning, 44(4), 177-198.
• Maitland, R. & Smith, A. (2009). Tourism and the aesthetics of the built environment. In J. Tribe (Eds.), Advanced philosophical issues in tourism (pp. 171-190). Bristol: Channel View Publications.
• Maulan, S., Shariff, M. K. & Miller, P. (2006). Landscape preference and human survival well-being. International Journal on Sustainable Tropical Design Research and Practice, 1(1), 24-31.
• Mayer, S. & Landwehr, J. R. (2018). Quantifying visual aesthetics based on processing fluency theory: Four algorithmic measures for antecedents of aesthetic preferences. Psychology of Aesthetics, Creativity, and the Arts, 12(4), 399-431.
• McNicoll, A. & Milner, N. P. (1997). Hellenistic Fortifications from the Aegean to the Euphrates. Oxford: Oxford University Press.
• Motevalian, N. & Yeganeh, M. (2020). Analysis of the production of visual richness in national monuments complex and its effect on the visually meaningful sustainability as an international heritage. Sustainable Cities and Society, 60, 102207.
• Müllenhoff, M., Handl, M., Knipping, M. & Brückner, H. (2004). The evolution of Lake Bafa (Western Turkey)–Sedimentological, microfaunal and palynological results. Coastline Reports, 1(2004), 55- 66.
• Ode, Å., Hagerhall, C. M. & Sang, N. (2010). Analysing visual landscape complexity: theory and application. Landscape Research, 35(1), 111-131.
• Özdemir, A. & Fenkçi, M. S. (2016). The role of aural and visual landscape perception in patient psychology. Journal of Human Sciences, 13(2), 3022-3032.
• Özhancı, E. & Yılmaz, H. (2019). Visual assessment of rural landscape with different characters. Forestist, 69(1), 44-60.
• Palmer, S. E., Schloss, K. B. & Sammartino, J. (2013). Visual aesthetics and human preference. Annual Review of Psychology, 64, 77-107.
• Peschlow, A. & Posamentir, R. (2012). Herakleia am Latmos und Seine Umgebung 2010. AST, 29(2), 225-238.
• Peschlow, U. (2014). The Latmos Region in the Byzantine Period. In A. Peschlow Bindokat (Eds.), Advanced a carian mountain landscape: Herakleia on the Latmos-City and environment (pp. 169-209). İstanbul: Homer Publishing.
• Peschlow Bindokat, A. (2005). Latmos’ta Bir Karia Kenti, Herakleia, Şehir ve Çevresi. Istanbul: Homer Kitap Evi.
• Peschlow Bindokat, A., Gerber, C., Özdoğan, M., Başgelen, N. & Kuniholm, P. (2012). The Latmos-Beşparmak Mountains Sites with early rock paintings in Western Anatolia. In M. Özdoğan, N. Basgelen & P. Kuniholm (Eds.), Advanced Neolithic in Turkey: new excavations and new research (pp. 67-115). İstanbul: Arkeoloji ve Sanat Yayınları.
• Sevenant, M. & Antrop, M. (2009). Cognitive attributes and aesthetic preferences in assessment and differentiation of landscapes. Journal of Environmental Management, 90(9), 2889-2899.
• Sheppard, S. R. (2001). Beyond visual resource management: emerging theories of an ecological aesthetic and visible stewardship. In S. Richard, J. Sheppard & H. W. Harshaw (Eds.), Advanced forests and landscapes: linking ecology, sustainability and aesthetics (pp. 149-172). Wallingford: CABI Publishing.
• Steele, J. (1992). Hellenistic Architecture in Asia Minor. London: Academy Editions.
• Tenerelli, P., Püffel, C. & Luque, S. (2017). Spatial assessment of aesthetic services in a complex mountain region: combining visual landscape properties with crowdsourced geographic information. Landscape Ecology, 32(5), 1097-1115.
• Thonemann, P. (2011). The Maeander Valley. A Historical Geography from Antiquity to Byzantium. Cambridge: Cambridge University Press.
• Tieskens, K. F., Van Zanten, B. T., Schulp, C. J. & Verburg, P. H. (2018). Aesthetic appreciation of the cultural landscape through social media: An analysis of revealed preference in the Dutch river landscape. Landscape and Urban Planning, 177, 128-137.
• Tveit, M. S. (2009). Indicators of visual scale as predictors of landscape preference; a comparison between groups. Journal of Environmental Management, 90(9), 2882-2888.
• Tveit, M., Ode, Å. & Fry, G. (2006). Key concepts in a framework for analysing visual landscape character. Landscape Research, 31(3), 229-255.
• Wang, R., Zhao, J. & Liu, Z. (2016). Consensus in visual preferences: The effects of aesthetic quality and landscape types. Urban Forestry and Urban Greening, 20, 210-217.
• Wiegand, T. (1913). Milet: Ergebnisse der Ausgrabungen und Untersuchungen seit dem Jahre 1899. Berlin: Georg Reimer.