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Visual Complexity Analysis of Built Environments on the Axis of Tourism Potential: The Case of Odunpazarı, Eskişehir

Year 2023, Volume: 8 Issue: 2, 373 - 391, 30.04.2023
https://doi.org/10.26835/my.1206985

Abstract

The visual environment is an urban component that directs and influences the citizens and the users visiting the city. Terms of physical decisions must analyze urban design based on visuals, especially in areas with high tourism potential. It is possible to calculate the measurable values of the images presented with visual complexity analysis, which has come to the forefront thanks to the developments in computer-aided image processing technology. One of the most common methods used to evaluate visual complexity is fractal geometry-based analysis. The research aims to reveal the fractal dimension in the complexity assessments of the built environments by considering three different attraction regions (Islands, Boulevard, and Museums) from Odunpazarı district of Eskişehir, where the visitor potential is high with many historical and socio-cultural values. First, preprocessing was performed for 60 street images selected from the regions. Thus, perceptually meaningful edge structures in the images were effectively revealed. Then, the level of visual complexity was measured with the FDH-FDT method. In the method, FDH represents the heterogeneity dimension (Dv) of the images, and FDT represents the heterogeneity dimension of the tissues [Dv(s)]. The visual complexity values obtained were evaluated with the complex matrix of four quarters. While Dv values are between 1.51-1.70 in the Islands region, Dv(s) values vary between 1.62-1.76. While Dv values in the Boulevard area ranged between 1.50-1.69, Dv(s) values were measured between 1.54-1.78. In the Museums’ region, the Dv values of the images vary between 1.47-1.75, while the Dv(s) values are between 1.52-1.74. As a result of the research, it has been reached that the Islands region has a more complex design than other areas. This result shows that the Islands region is a more attractive and exciting urban area for visitors in terms of visual richness. The study reveals that the FDH-FDT method can be an effective systematic tool in quantitatively evaluating built environments in the context of visual-spatial perception.

References

  • Abboushi, B., Elzeyadi, I., Taylor, R., & Sereno, M. (2019). Fractals in architecture: The visual interest, preference, and mood response to projected fractal light patterns in interior spaces. Journal of Environmental Psychology, 61, 57-70. https://doi.org/10.1016/j.jenvp.2018.12.005
  • Akbarishahabi, L., Tekel, A. (2017). Fractal Analysis of Street Physical Characteristics: The Developmentof a Practical Tool For Improving Visual Quality in Street Scenes. Ecology Planning and Design,316-326.
  • Alexander, C., Ishikawa, S., & Silverstein, M. (1977). A Pattern Language, Towns, Buildings, Construction. (Second Edition). New York: Oxford University Press.
  • Cooper, J., Su, M. L., & Oskrochi, R. (2013). The influence of fractal dimension and vegetation on the perceptions of streetscape quality in Taipei: with comparative comments made in relation to two British case studies. Environment and Planning B: Planning and Design, 40(1), 43-62. https://doi.org/10.1068/b38010
  • Cooper, J., Watkinson, D., & Oskrochi, R. (2010). Fractal analysis and perception of visual quality in everyday street vistas. Environment and Planning B: Planning and Design, 37(5), 808-822. https://doi.org/10.1068/b34061
  • Dupont, L., Antrop, M., & Van Eetvelde, V. (2014). Eye-tracking analysis in landscape perception research: Influence of photograph properties and landscape characteristics. Landscape research, 39(4), 417-432. https://doi.org/10.1080/01426397.2013.773966
  • Encalada-Abarca, L., Ferreira, C. C., & Rocha, J. (2022). Measuring tourism intensification in urban destinations: An approach based on fractal analysis. Journal of Travel Research, 61(2), 394-413. https://doi.org/10.1177/0047287520987627
  • Ewing, R., & Handy, S. (2009). Measuring the unmeasurable: urban design qualities related to walkability. Journal of Urban Design, 14(1), 65-68. https://doi.org/10.1080/13574800802451155
  • Falk, J. H., & Balling, J. D. (2010). Evolutionary influence on human landscape preference. Environment and behavior, 42(4), 479-493. https://doi.org/10.1177/0013916509341244
  • Hagerhall, C. M., Laike, T., Kuller, M., Marcheschi, E., Boydston, C., & Taylor, R. P. (2015). Human physiological benefits of viewing nature: EEG responses to exact and statistical fractal patterns. Nonlinear dynamics, psychology, and life sciences, 19(1), 1-12.
  • Hagerhall, C. M., Purcell, T., & Taylor, R. (2004). Fractal dimension of landscape silhouette outlines as a predictor of landscape preference. Journal of environmental psychology, 24(2), 247-255. https://doi.org/10.1016/j.jenvp.2003.12.004
  • 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. https://doi.org/10.1080/01426397.2019.1593336
  • Isinkaralar, O., & Varol, C. (2023). A cellular automata-based approach for spatio-temporal modeling of the city center as a complex system: The case of Kastamonu, Türkiye. Cities, 132, 104073. https://doi.org/10.1016/j.cities.2022.104073
  • İlgar, E. (2008). Kent kimliği ve kentsel değişimin kent kimliği boyutu: Eskişehir örneği. Yüksek lisans tezi. Anadolu Üniversitesi Fen Bilimleri Enstitüsü, Mimarlık Ana Bilim Dalı, Eskişehir.
  • Jacobs, J. (1961). The Death And Life of Great American Cities. London: Vintage Books.
  • Juliani, A. W., Bies, A. J., Boydston, C. R., Taylor, R. P., & Sereno, M. E. (2016). Navigation performance in virtual environments varies with fractal dimension of landscape. Journal of environmental psychology, 47, 155-165. https://doi.org/10.1016/j.jenvp.2016.05.011
  • Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological perspective. Cambridge university press.
  • Lazard, A. J., & King, A. J. (2020). Objective design to subjective evaluations: Connecting visual complexity to aesthetic and usability assessments of eHealth. International Journal of Human–Computer Interaction, 36(1), 95-104. https://doi.org/10.1080/10447318.2019.1606976
  • Ma, L., He, S., & Lu, M. (2021). A Measurement of Visual Complexity for Heterogeneity in the Built Environment Based on Fractal Dimension and Its Application in Two Gardens. Fractal and Fractional, 5(4), 278. https://doi.org/10.3390/fractalfract5040278
  • Ma, L., Zhang, H., & Lu, M. (2020). Building's fractal dimension trend and its application in visual complexity map. Building and Environment, 178, 106925. https://doi.org/10.1016/j.buildenv.2020.106925
  • Madan, C. R., Bayer, J., Gamer, M., Lonsdorf, T. B., & Sommer, T. (2018). Visual complexity and affect: Ratings reflect more than meets the eye. Frontiers in psychology, 8, 2368. https://doi.org/10.3389/fpsyg.2017.02368
  • Mandelbrot, B. (1982). The fractal geometry of nature. San Francisco: W.H. Freeman and Company.
  • Patuano, A. (2018). Measuring naturalness and complexity using the fractal dimensions of landscape photographs. Journal of Digital Landscape Architecture, 3, 328-335. https://doi.org/10.14627/537642035
  • Patuano, A., & Tara, A. (2020). Fractal geometry for landscape architecture: review of methodologies and interpretations. Journal of Digital Landscape Architecture, 5, 72-80.
  • Salingaros, N. A. (1999). Urban Space and its Information Field. Journal of Urban Design, 4(1), 29-49. http://dx.doi.org/10.1080/13574809908724437
  • Sigaki, H. Y., Perc, M., & Ribeiro, H. V. (2018). History of art paintings through the lens of entropy and complexity. Proceedings of the National Academy of Sciences, 115(37), E8585-E8594. https://doi.org/10.1073/pnas.1800083115
  • Stamps, A. E. (2002). Fractals, Skylines, Nature and Beauty. Landscape and Urban Planning, 60(3), 163-184.
  • Tekel, A. (2021). Tarihsel Süreçte Sokak ve Caddelerin Görsel Estetik Kalitesinde Meydana Gelen Değişimi Değerlendirmede Bir Model Önerisi: Ankara’nın Ulus ve Kızılay Kent Merkezleri Örneği. Ankara Araştırmaları Dergisi, 9(2), 217-238. 10.5505/jas.2021.95867
  • Ulrich, R.S. (1983). Aesthetic and Affective Response to Natural Environment. In: Altman, I., Wohlwill, J.F. (eds) Behavior and the Natural Environment. Human Behavior and Environment, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3539-9_4
  • Vaughan, J., & Ostwald, M. J. (2021). Measuring the geometry of nature and architecture: comparing the visual properties of Frank Lloyd Wright's Fallingwater and its natural setting. Open House International. https://doi.org/10.1108/OHI-01-2021-0011
  • Yang, Z., & Purves, D. (2003). A statistical explanation of visual space. Nature neuroscience, 6(6), 632-640. https://doi.org/10.1038/nn1059
  • Yılmaz, D., Öztürk, S., & Işınkaralar, Ö. (2023). Bir Yaşam Sahnesi Olarak Sokak Algısının Kullanıcılar Gözünden Okunması: Ankara ve İstanbul Sokaklarından Tespitler. Artium, 11(1), 75-86. http://dx.doi.org/10.51664/artium.1169765
  • Yılmaz, D., Öztürk, S., Işınkaralar, Ö. (2022). Kent İmgesinin Yapıtaşı Olarak Sokaklarda Mekânsal Zenginliğin Fraktal Geometri İle Analizi, Kent Akademisi Dergisi, 15(3)1341-.1358. https://doi.org/10.35674/kent.996119

Turizm Potansiyeli Ekseninde Yapılı Çevrelerdeki Görsel Karmaşıklığın Analizi: Odunpazarı, Eskişehir Örneği

Year 2023, Volume: 8 Issue: 2, 373 - 391, 30.04.2023
https://doi.org/10.26835/my.1206985

Abstract

Görsel çevre, kentliyi ve kenti ziyaret eden kullanıcıları yönlendiren ve etkileyen bir kentsel bileşendir. Özellikle turizm potansiyeli yüksek alanlarda görsellerden yola çıkarak kentsel tasarıma yönelik analizler yürütmek fiziksel kararlar açısından bir gerekliliktir. Bilgisayar destekli görüntü işleme teknolojisinde yaşanan gelişmeler sayesinde öne çıkan görsel karmaşıklık analizi ile sunulan görsellerin ölçülebilir değerlerinin hesaplanması mümkündür. Görsel karmaşıklığın değerlendirilmesinde kullanılan en yaygın yöntemlerden biri ise fraktal geometri tabanlı analizlerdir. Araştırmada tarihi ve sosyo-kültürel pek çok değeri ile ziyaretçi potansiyelinin yüksek olduğu Eskişehir Odunpazarı ilçesinden üç farklı cazibe bölgesi (Adalar, Bulvar ve Müzeler) ele alınarak, yapılı çevrelerinin karmaşıklık değerlendirmelerinde fraktal boyutu ortaya koymak amaçlanmaktadır. Bölgelerden seçilen 60 sokak görüntüsü için ilk olarak ön işleme yapılmıştır. Böylece, görüntülerdeki algısal olarak anlamlı kenar yapıları etkili bir şekilde ortaya çıkarılmıştır. Ardından, görüntülerin fraktal heterojenlik boyutu (FDH: fractal dimension of heterogeneity) ve dokunun fraktal boyutu (FDT: fractal dimension of texture) yöntemleri ile görsel karmaşıklık düzeyi ölçülmüştür. Yöntemde FDH görüntülerin heterojenlik boyutunu (Dv), FDT ise dokuların heterojenlik boyutunu [Dv(s)] temsil etmektedir. Elde edilen görsel karmaşıklık değerleri, dört farklı çeyrekten oluşan karmaşıklık matrisi ile değerlendirilmiştir. Adalar bölgesinde Dv değerleri 1,51-1,70 arasındayken, Dv(s) değerleri ise 1,62-1,76 arasında değişmektedir. Bulvar bölgesinde Dv değerleri 1,50-1,69 arasında değişim gösterirken, Dv(s) değerleri 1,54-1,78 arasında ölçülmüştür. Müzeler bölgesinde ise görüntülerin Dv değerleri 1,47-1,75 arasında değişim gösterirken, Dv(s) değerleri 1,52-1,74 arasındadır. Araştırma sonucunda, Adalar bölgesinin diğer alanlardan daha karmaşık bir tasarıma sahip olduğuna ulaşılmıştır. Bu sonuç ise Adalar bölgesinin görsel zenginlik açısından ziyaretçiler için daha çekici ve heyecan verici bir kentsel alan olduğunu göstermektedir. Çalışma, görsel mekânsal algı bağlamında yapılı çevrelerin nicel olarak değerlendirilmesinde FDH-FDT yönteminin etkili bir sistematik araç olabileceğini göstermektedir

References

  • Abboushi, B., Elzeyadi, I., Taylor, R., & Sereno, M. (2019). Fractals in architecture: The visual interest, preference, and mood response to projected fractal light patterns in interior spaces. Journal of Environmental Psychology, 61, 57-70. https://doi.org/10.1016/j.jenvp.2018.12.005
  • Akbarishahabi, L., Tekel, A. (2017). Fractal Analysis of Street Physical Characteristics: The Developmentof a Practical Tool For Improving Visual Quality in Street Scenes. Ecology Planning and Design,316-326.
  • Alexander, C., Ishikawa, S., & Silverstein, M. (1977). A Pattern Language, Towns, Buildings, Construction. (Second Edition). New York: Oxford University Press.
  • Cooper, J., Su, M. L., & Oskrochi, R. (2013). The influence of fractal dimension and vegetation on the perceptions of streetscape quality in Taipei: with comparative comments made in relation to two British case studies. Environment and Planning B: Planning and Design, 40(1), 43-62. https://doi.org/10.1068/b38010
  • Cooper, J., Watkinson, D., & Oskrochi, R. (2010). Fractal analysis and perception of visual quality in everyday street vistas. Environment and Planning B: Planning and Design, 37(5), 808-822. https://doi.org/10.1068/b34061
  • Dupont, L., Antrop, M., & Van Eetvelde, V. (2014). Eye-tracking analysis in landscape perception research: Influence of photograph properties and landscape characteristics. Landscape research, 39(4), 417-432. https://doi.org/10.1080/01426397.2013.773966
  • Encalada-Abarca, L., Ferreira, C. C., & Rocha, J. (2022). Measuring tourism intensification in urban destinations: An approach based on fractal analysis. Journal of Travel Research, 61(2), 394-413. https://doi.org/10.1177/0047287520987627
  • Ewing, R., & Handy, S. (2009). Measuring the unmeasurable: urban design qualities related to walkability. Journal of Urban Design, 14(1), 65-68. https://doi.org/10.1080/13574800802451155
  • Falk, J. H., & Balling, J. D. (2010). Evolutionary influence on human landscape preference. Environment and behavior, 42(4), 479-493. https://doi.org/10.1177/0013916509341244
  • Hagerhall, C. M., Laike, T., Kuller, M., Marcheschi, E., Boydston, C., & Taylor, R. P. (2015). Human physiological benefits of viewing nature: EEG responses to exact and statistical fractal patterns. Nonlinear dynamics, psychology, and life sciences, 19(1), 1-12.
  • Hagerhall, C. M., Purcell, T., & Taylor, R. (2004). Fractal dimension of landscape silhouette outlines as a predictor of landscape preference. Journal of environmental psychology, 24(2), 247-255. https://doi.org/10.1016/j.jenvp.2003.12.004
  • 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. https://doi.org/10.1080/01426397.2019.1593336
  • Isinkaralar, O., & Varol, C. (2023). A cellular automata-based approach for spatio-temporal modeling of the city center as a complex system: The case of Kastamonu, Türkiye. Cities, 132, 104073. https://doi.org/10.1016/j.cities.2022.104073
  • İlgar, E. (2008). Kent kimliği ve kentsel değişimin kent kimliği boyutu: Eskişehir örneği. Yüksek lisans tezi. Anadolu Üniversitesi Fen Bilimleri Enstitüsü, Mimarlık Ana Bilim Dalı, Eskişehir.
  • Jacobs, J. (1961). The Death And Life of Great American Cities. London: Vintage Books.
  • Juliani, A. W., Bies, A. J., Boydston, C. R., Taylor, R. P., & Sereno, M. E. (2016). Navigation performance in virtual environments varies with fractal dimension of landscape. Journal of environmental psychology, 47, 155-165. https://doi.org/10.1016/j.jenvp.2016.05.011
  • Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological perspective. Cambridge university press.
  • Lazard, A. J., & King, A. J. (2020). Objective design to subjective evaluations: Connecting visual complexity to aesthetic and usability assessments of eHealth. International Journal of Human–Computer Interaction, 36(1), 95-104. https://doi.org/10.1080/10447318.2019.1606976
  • Ma, L., He, S., & Lu, M. (2021). A Measurement of Visual Complexity for Heterogeneity in the Built Environment Based on Fractal Dimension and Its Application in Two Gardens. Fractal and Fractional, 5(4), 278. https://doi.org/10.3390/fractalfract5040278
  • Ma, L., Zhang, H., & Lu, M. (2020). Building's fractal dimension trend and its application in visual complexity map. Building and Environment, 178, 106925. https://doi.org/10.1016/j.buildenv.2020.106925
  • Madan, C. R., Bayer, J., Gamer, M., Lonsdorf, T. B., & Sommer, T. (2018). Visual complexity and affect: Ratings reflect more than meets the eye. Frontiers in psychology, 8, 2368. https://doi.org/10.3389/fpsyg.2017.02368
  • Mandelbrot, B. (1982). The fractal geometry of nature. San Francisco: W.H. Freeman and Company.
  • Patuano, A. (2018). Measuring naturalness and complexity using the fractal dimensions of landscape photographs. Journal of Digital Landscape Architecture, 3, 328-335. https://doi.org/10.14627/537642035
  • Patuano, A., & Tara, A. (2020). Fractal geometry for landscape architecture: review of methodologies and interpretations. Journal of Digital Landscape Architecture, 5, 72-80.
  • Salingaros, N. A. (1999). Urban Space and its Information Field. Journal of Urban Design, 4(1), 29-49. http://dx.doi.org/10.1080/13574809908724437
  • Sigaki, H. Y., Perc, M., & Ribeiro, H. V. (2018). History of art paintings through the lens of entropy and complexity. Proceedings of the National Academy of Sciences, 115(37), E8585-E8594. https://doi.org/10.1073/pnas.1800083115
  • Stamps, A. E. (2002). Fractals, Skylines, Nature and Beauty. Landscape and Urban Planning, 60(3), 163-184.
  • Tekel, A. (2021). Tarihsel Süreçte Sokak ve Caddelerin Görsel Estetik Kalitesinde Meydana Gelen Değişimi Değerlendirmede Bir Model Önerisi: Ankara’nın Ulus ve Kızılay Kent Merkezleri Örneği. Ankara Araştırmaları Dergisi, 9(2), 217-238. 10.5505/jas.2021.95867
  • Ulrich, R.S. (1983). Aesthetic and Affective Response to Natural Environment. In: Altman, I., Wohlwill, J.F. (eds) Behavior and the Natural Environment. Human Behavior and Environment, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3539-9_4
  • Vaughan, J., & Ostwald, M. J. (2021). Measuring the geometry of nature and architecture: comparing the visual properties of Frank Lloyd Wright's Fallingwater and its natural setting. Open House International. https://doi.org/10.1108/OHI-01-2021-0011
  • Yang, Z., & Purves, D. (2003). A statistical explanation of visual space. Nature neuroscience, 6(6), 632-640. https://doi.org/10.1038/nn1059
  • Yılmaz, D., Öztürk, S., & Işınkaralar, Ö. (2023). Bir Yaşam Sahnesi Olarak Sokak Algısının Kullanıcılar Gözünden Okunması: Ankara ve İstanbul Sokaklarından Tespitler. Artium, 11(1), 75-86. http://dx.doi.org/10.51664/artium.1169765
  • Yılmaz, D., Öztürk, S., Işınkaralar, Ö. (2022). Kent İmgesinin Yapıtaşı Olarak Sokaklarda Mekânsal Zenginliğin Fraktal Geometri İle Analizi, Kent Akademisi Dergisi, 15(3)1341-.1358. https://doi.org/10.35674/kent.996119
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Architecture
Journal Section Makaleler
Authors

Öznur Işınkaralar 0000-0001-9774-5137

Publication Date April 30, 2023
Published in Issue Year 2023 Volume: 8 Issue: 2

Cite

APA Işınkaralar, Ö. (2023). Turizm Potansiyeli Ekseninde Yapılı Çevrelerdeki Görsel Karmaşıklığın Analizi: Odunpazarı, Eskişehir Örneği. Mimarlık Ve Yaşam, 8(2), 373-391. https://doi.org/10.26835/my.1206985