Assessing relations among landscape preference, informational variables, and visual attributes
Abstract
The theory of preference matrix proposes coherence and complexity as informational variables to explain landscape preferences. To understand the relationship between the perceived coherence/complexity and the visual attributes of landscape scenes, we constructed multivariate generalized linear models based on a questionnaire study. A total of 488 respondents’ ratings of the preference, the perceived coherence and complexity, and four visual attributes, namely, the openness of visual scale (openness), the richness of composing elements (richness), the orderliness of organization (orderliness), and the depth of view (depth), of a set of digitally manipulated landscape scenes were analyzed. The results showed that landscape preference needed to be explained with coherence and complexity together. Meanwhile, rather than showing the one-one connection with a single visual attribute, the degree of perceived coherence/complexity should be explained with multiple visual attributes. Ranked by explanatory power, the coherence was positively related to orderliness, negatively related to richness, and positively related to openness. The complexity was positively influenced by the level of richness, depth, and negatively influenced by orderliness and openness. Based on the results, feasible ways to build landscape environments with both preferable coherence and complexity were proposed.
Keyword : preference matrix, coherence, complexity, visual attributes, explanatory model, landscape management
How to Cite
Zhang, G., Yang, J., & Jin, J. (2021). Assessing relations among landscape preference, informational variables, and visual attributes. Journal of Environmental Engineering and Landscape Management, 29(3), 294-304. https://doi.org/10.3846/jeelm.2021.15584
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Dronova, I. (2017). Environmental heterogeneity as a bridge between ecosystem service and visual quality objectives in management, planning and design. Landscape and Urban Planning, 163, 90–106. https://doi.org/10.1016/j.landurbplan.2017.03.005
Foelske, L., & van Riper, C. J. (2020). Assessing spatial preference heterogeneity in a mixed-use landscape. Applied Geography, 125. https://doi.org/10.1016/j.apgeog.2020.102355
Foltête, J.-C., Ingensand, J., & Blanc, N. (2020). Coupling crowd-sourced imagery and visibility modelling to identify landscape preferences at the panorama level. Landscape and Urban Planning, 197, 103756. https://doi.org/10.1016/j.landurbplan.2020.103756
Hoyle, H., Hitchmough, J., & Jorgensen, A. (2017). All about the ‘wow factor’? The relationships between aesthetics, restorative effect and perceived biodiversity in designed urban planting. Landscape and Urban Planning, 164, 109–123. https://doi.org/10.1016/j.landurbplan.2017.03.011
Hunter, M. R., & Askarinejad, A. (2015). Designer’s approach for scene selection in tests of preference and restoration along a continuum of natural to manmade environments. Frontiers in Psychology, 6, 1228. https://doi.org/10.3389/fpsyg.2015.01228
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Kalivoda, O., Vojar, J., Skrivanova, Z., & Zahradnik, D. (2014). Consensus in landscape preference judgments: the effects of landscape visual aesthetic quality and respondents’ characteristics. Journal of Environmental Management, 137, 36–44. https://doi.org/10.1016/j.jenvman.2014.02.009
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Kaplan, R., Kaplan, S., & Ryan, R. (1998). With people in mind: Design and management of everyday nature. Island Press. https://books.google.lt/books/about/With_People_in_Mind.html?id=snqtOUwqlXsC&redir_esc=y
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Kuper, R. (2017). Evaluations of landscape preference, complexity, and coherence for designed digital landscape models. Landscape and Urban Planning, 157, 407–421. https://doi.org/10.1016/j.landurbplan.2016.09.002
Kuper, R. (2020). Preference and restorative potential for landscape models that depict diverse arrangements of defoliated, foliated, and evergreen plants. Urban Forestry & Urban Greening, 48, 126570. https://doi.org/10.1016/j.ufug.2019.126570
Marselle, M. R., Irvine, K. N., Lorenzo-Arribas, A., & Warber, S. L. (2015). Moving beyond green: exploring the relationship of environment type and indicators of perceived environmental quality on emotional well-being following group walks. International Journal of Environmental Research and Public Health, 12(1), 106–130. https://doi.org/10.3390/ijerph120100106
Murphy, M. (2005). Landscape architecture theory. Island Press. https://doi.org/10.5822/978-1-61091-751-3
Nasar, J., & Li, M. (2004). Landscape mirror: the attractiveness of reflecting water. Landscape and Urban Planning, 66(4), 233–238. https://doi.org/10.1016/S0169-2046(03)00113-0
Nasar, J., & Lin, Y.-H. (2003). Evaluative responses to five kinds of water features. Landscape Research, 28(4), 441–450. https://doi.org/10.1080/0142639032000150167
Ode, Å., Hagerhall, C. M., & Sang, N. (2010). Analysing visual landscape complexity: theory and application. Landscape Research, 35(1), 111–131. https://doi.org/10.1080/01426390903414935
Ode, Å., Tveit, M. S., & Fry, G. (2008). Capturing landscape visual character using indicators: touching base with landscape aesthetic theory. Landscape Research, 33(1), 89–117. https://doi.org/10.1080/01426390701773854
Schirpke, U., Tappeiner, G., Tasser, E., & Tappeiner, U. (2019). Using conjoint analysis to gain deeper insights into aesthetic landscape preferences. Ecological Indicators, 96, 202–212. https://doi.org/10.1016/j.ecolind.2018.09.001
Schüpbach, B., Weiß, S. B., Jeanneret, P., Zalai, M., Szalai, M., & Frör, O. (2021). What determines preferences for seminatural habitats in agrarian landscapes? A choice-modelling approach across two countries using attributes characterising vegetation. Landscape and Urban Planning, 206, 103954. https://doi.org/10.1016/j.landurbplan.2020.103954
Sevenant, M., & Antrop, M. (2010). The use of latent classes to identify individual differences in the importance of landscape dimensions for aesthetic preference. Land Use Policy, 27(3), 827–842. https://doi.org/10.1016/j.landusepol.2009.11.002
Sowinska-Swierkosz, B., & Soszynski, D. (2019). The index of the Prognosis Rural Landscape Preferences (IPRLP) as a tool of generalizing peoples’ preferences on rural landscape. Journal of Environmental Management, 248, 109272. https://doi.org/10.1016/j.jenvman.2019.109272
Stamps, A. (2004). Mystery, complexity, legibility and coherence: A meta-analysis. Journal of Environmental Psychology, 24(1), 1–16. https://doi.org/10.1016/S0272-4944(03)00023-9
Suppakittpaisarn, P., Larsen, L., & Sullivan, W. C. (2019). Preferences for green infrastructure and green stormwater infrastructure in urban landscapes: Differences between designers and laypeople. Urban Forestry & Urban Greening, 43, 126378. https://doi.org/10.1016/j.ufug.2019.126378
Taylor, R., Spehar, B., Hagerhall, C., & Van Donkelaar, P. (2011). Perceptual and physiological responses to Jackson Pollock’s fractals. Frontiers in Human Neuroscience, 5, 60. https://doi.org/10.3389/fnhum.2011.00060
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
Tveit, M., Ode, Å., & Fry, G. (2006). Key concepts in a framework for analysing visual landscape character. Landscape Research, 31(3), 229–255. https://doi.org/10.1080/01426390600783269
Ulrich, R. S. (1983). Aesthetic and affective response to natural environment. In Human Behavior and Environment: Vol. 6. Behavior and the natural environment (pp. 85–125). Springer. https://doi.org/10.1007/978-1-4613-3539-9_4
Valtchanov, D., & Ellard, C. G. (2015). Cognitive and affective responses to natural scenes: effects of low level visual properties on preference, cognitive load and eye-movements. Journal of Environmental Psychology, 43, 184–195. https://doi.org/10.1016/j.jenvp.2015.07.001
van der Jagt, A. P. N., Craig, T., Anable, J., Brewer, M. J., & Pearson, D. G. (2014). Unearthing the picturesque: The validity of the preference matrix as a measure of landscape aesthetics. Landscape and Urban Planning, 124, 1–13. https://doi.org/10.1016/j.landurbplan.2013.12.006
Wolfe, J. M., Kluender, K. R., Levi, D. M., Bartoshuk, L. M., Herz, R. S., Klatzky, R. L., Lederman, S. J., & Merfeld, D. (2008). Sensation & perception (2nd ed.). Sinauer Associates.
Yang, B.-E., & Brown, T. J. (1992). A cross-cultural comparison of preferences for landscape styles and landscape elements. Environment and Behavior, 24(4), 471–507. https://doi.org/10.1177/0013916592244003
Beute, F., & de Kort, Y. A. (2013). Let the sun shine! Measuring explicit and implicit preference for environments differing in naturalness, weather type and brightness. Journal of Environmental Psychology, 36, 162–178. https://doi.org/10.1016/j.jenvp.2013.07.016
Buss, D. (2015). Evolutionary psychology: The new science of the mind (5th ed.). Psychology Press. https://doi.org/10.4324/9781315663319
Chiang, Y.-C., Li, D., & Jane, H.-A. (2017). Wild or tended nature? The effects of landscape location and vegetation density on physiological and psychological responses. Landscape and Urban Planning, 167, 72–83. https://doi.org/10.1016/j.landurbplan.2017.06.001
Coeterier, J. (1996). Dominant attributes in the perception and evaluation of the Dutch landscape. Landscape and Urban Planning, 34(1), 27–44. https://doi.org/10.1016/0169-2046(95)00204-9
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
Daniel, T. C., & Meitner, M. M. (2001). Representational validity of landscape visualizations: the effects of graphical realism on perceived scenic beauty of forest vistas. Journal of Environmental Psychology, 21(1), 61–72. https://doi.org/10.1006/jevp.2000.0182
Deng, L., Luo, H., Ma, J., Huang, Z., Sun, L.-X., Jiang, M.-Y., Zhu, C.-Y., & Li, X. (2020). Effects of integration between visual stimuli and auditory stimuli on restorative potential and aesthetic preference in urban green spaces. Urban Forestry & Urban Greening, 53, 126702. https://doi.org/10.1016/j.ufug.2020.126702
Dronova, I. (2017). Environmental heterogeneity as a bridge between ecosystem service and visual quality objectives in management, planning and design. Landscape and Urban Planning, 163, 90–106. https://doi.org/10.1016/j.landurbplan.2017.03.005
Foelske, L., & van Riper, C. J. (2020). Assessing spatial preference heterogeneity in a mixed-use landscape. Applied Geography, 125. https://doi.org/10.1016/j.apgeog.2020.102355
Foltête, J.-C., Ingensand, J., & Blanc, N. (2020). Coupling crowd-sourced imagery and visibility modelling to identify landscape preferences at the panorama level. Landscape and Urban Planning, 197, 103756. https://doi.org/10.1016/j.landurbplan.2020.103756
Hoyle, H., Hitchmough, J., & Jorgensen, A. (2017). All about the ‘wow factor’? The relationships between aesthetics, restorative effect and perceived biodiversity in designed urban planting. Landscape and Urban Planning, 164, 109–123. https://doi.org/10.1016/j.landurbplan.2017.03.011
Hunter, M. R., & Askarinejad, A. (2015). Designer’s approach for scene selection in tests of preference and restoration along a continuum of natural to manmade environments. Frontiers in Psychology, 6, 1228. https://doi.org/10.3389/fpsyg.2015.01228
Hunziker, M., & Kienast, F. (1999). Potential impacts of changing agricultural activities on scenic beauty – a prototypical technique for automated rapid assessment. Landscape Ecology, 14(2), 161–176. https://doi.org/10.1023/A:1008079715913
Ibarra, F. F., Kardan, O., Hunter, M. R., Kotabe, H. P., Meyer, F. A., & Berman, M. G. (2017). Image feature types and their predictions of aesthetic preference and naturalness. Frontiers in Psychology, 8, 632. https://doi.org/10.3389/fpsyg.2017.00632
Kalivoda, O., Vojar, J., Skrivanova, Z., & Zahradnik, D. (2014). Consensus in landscape preference judgments: the effects of landscape visual aesthetic quality and respondents’ characteristics. Journal of Environmental Management, 137, 36–44. https://doi.org/10.1016/j.jenvman.2014.02.009
Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological perspective. Cambridge University Press. https://psycnet.apa.org/record/1989-98477-000
Kaplan, R., Kaplan, S., & Ryan, R. (1998). With people in mind: Design and management of everyday nature. Island Press. https://books.google.lt/books/about/With_People_in_Mind.html?id=snqtOUwqlXsC&redir_esc=y
Kotabe, H. P., Kardan, O., & Berman, M. G. (2017). The naturedisorder paradox: A perceptual study on how nature is disorderly yet aesthetically preferred. Journal of Experimental Psychology: General, 146(8), 1126–1142. https://doi.org/10.1037/xge0000321
Kubovy, M., & Cohen, D. J. (2001). What boundaries tell us about binding. Trends in Cognitive Sciences, 5(3), 93–95. https://doi.org/10.1016/S1364-6613(00)01604-1
Kuper, R. (2017). Evaluations of landscape preference, complexity, and coherence for designed digital landscape models. Landscape and Urban Planning, 157, 407–421. https://doi.org/10.1016/j.landurbplan.2016.09.002
Kuper, R. (2020). Preference and restorative potential for landscape models that depict diverse arrangements of defoliated, foliated, and evergreen plants. Urban Forestry & Urban Greening, 48, 126570. https://doi.org/10.1016/j.ufug.2019.126570
Marselle, M. R., Irvine, K. N., Lorenzo-Arribas, A., & Warber, S. L. (2015). Moving beyond green: exploring the relationship of environment type and indicators of perceived environmental quality on emotional well-being following group walks. International Journal of Environmental Research and Public Health, 12(1), 106–130. https://doi.org/10.3390/ijerph120100106
Murphy, M. (2005). Landscape architecture theory. Island Press. https://doi.org/10.5822/978-1-61091-751-3
Nasar, J., & Li, M. (2004). Landscape mirror: the attractiveness of reflecting water. Landscape and Urban Planning, 66(4), 233–238. https://doi.org/10.1016/S0169-2046(03)00113-0
Nasar, J., & Lin, Y.-H. (2003). Evaluative responses to five kinds of water features. Landscape Research, 28(4), 441–450. https://doi.org/10.1080/0142639032000150167
Ode, Å., Hagerhall, C. M., & Sang, N. (2010). Analysing visual landscape complexity: theory and application. Landscape Research, 35(1), 111–131. https://doi.org/10.1080/01426390903414935
Ode, Å., Tveit, M. S., & Fry, G. (2008). Capturing landscape visual character using indicators: touching base with landscape aesthetic theory. Landscape Research, 33(1), 89–117. https://doi.org/10.1080/01426390701773854
Schirpke, U., Tappeiner, G., Tasser, E., & Tappeiner, U. (2019). Using conjoint analysis to gain deeper insights into aesthetic landscape preferences. Ecological Indicators, 96, 202–212. https://doi.org/10.1016/j.ecolind.2018.09.001
Schüpbach, B., Weiß, S. B., Jeanneret, P., Zalai, M., Szalai, M., & Frör, O. (2021). What determines preferences for seminatural habitats in agrarian landscapes? A choice-modelling approach across two countries using attributes characterising vegetation. Landscape and Urban Planning, 206, 103954. https://doi.org/10.1016/j.landurbplan.2020.103954
Sevenant, M., & Antrop, M. (2010). The use of latent classes to identify individual differences in the importance of landscape dimensions for aesthetic preference. Land Use Policy, 27(3), 827–842. https://doi.org/10.1016/j.landusepol.2009.11.002
Sowinska-Swierkosz, B., & Soszynski, D. (2019). The index of the Prognosis Rural Landscape Preferences (IPRLP) as a tool of generalizing peoples’ preferences on rural landscape. Journal of Environmental Management, 248, 109272. https://doi.org/10.1016/j.jenvman.2019.109272
Stamps, A. (2004). Mystery, complexity, legibility and coherence: A meta-analysis. Journal of Environmental Psychology, 24(1), 1–16. https://doi.org/10.1016/S0272-4944(03)00023-9
Suppakittpaisarn, P., Larsen, L., & Sullivan, W. C. (2019). Preferences for green infrastructure and green stormwater infrastructure in urban landscapes: Differences between designers and laypeople. Urban Forestry & Urban Greening, 43, 126378. https://doi.org/10.1016/j.ufug.2019.126378
Taylor, R., Spehar, B., Hagerhall, C., & Van Donkelaar, P. (2011). Perceptual and physiological responses to Jackson Pollock’s fractals. Frontiers in Human Neuroscience, 5, 60. https://doi.org/10.3389/fnhum.2011.00060
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
Tveit, M., Ode, Å., & Fry, G. (2006). Key concepts in a framework for analysing visual landscape character. Landscape Research, 31(3), 229–255. https://doi.org/10.1080/01426390600783269
Ulrich, R. S. (1983). Aesthetic and affective response to natural environment. In Human Behavior and Environment: Vol. 6. Behavior and the natural environment (pp. 85–125). Springer. https://doi.org/10.1007/978-1-4613-3539-9_4
Valtchanov, D., & Ellard, C. G. (2015). Cognitive and affective responses to natural scenes: effects of low level visual properties on preference, cognitive load and eye-movements. Journal of Environmental Psychology, 43, 184–195. https://doi.org/10.1016/j.jenvp.2015.07.001
van der Jagt, A. P. N., Craig, T., Anable, J., Brewer, M. J., & Pearson, D. G. (2014). Unearthing the picturesque: The validity of the preference matrix as a measure of landscape aesthetics. Landscape and Urban Planning, 124, 1–13. https://doi.org/10.1016/j.landurbplan.2013.12.006
Wolfe, J. M., Kluender, K. R., Levi, D. M., Bartoshuk, L. M., Herz, R. S., Klatzky, R. L., Lederman, S. J., & Merfeld, D. (2008). Sensation & perception (2nd ed.). Sinauer Associates.
Yang, B.-E., & Brown, T. J. (1992). A cross-cultural comparison of preferences for landscape styles and landscape elements. Environment and Behavior, 24(4), 471–507. https://doi.org/10.1177/0013916592244003