Urban green parks as sociomental landscapes: Understandings from Iran’s case study
Vol 9, Issue 3, 2024, Article identifier:
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Abstract
This paper aims to investigate the impact of complexity and mystery on the perceived legibility of citizens in urban parks. The theoretical framework is based on Rachel and Stephen Kaplan’s theory (four cognitive states) and Lynch’s legibility theory. The method is descriptive correlational. Data collection was done through a survey questionnaire and mental maps. The paper uses Lynch’s mental maps and asks people to draw some aspects of the parks they remembered the most and compare the results with the surveys. The data analysis uses descriptive and inferential techniques as well as logical reasoning. The research claims a significant correlation with a higher-than-average coefficient between the legibility indicators (path, edge, node, district, landmark) and complexity and mystery in urban parks. The conclusion is that districts in urban parks have the most significant impact on the overlapping of citizens’ collective mental maps. Landmarks, paths, edges, and entrances are almost equally and moderately fuzzy-scale on the legibility of citizens’ mental maps in urban parks. Nodes play less of a role in citizens’ collective mental maps than other park elements. Parks with too many entrances, non-linear paths, indistinguishable districts, and undefined edges are not perceptible to citizens, and citizens’ perceptions of space differ significantly from the existing reality. The correlation between legibility dimensions, such as edges, nodes, landmarks, districts, paths, and entrances, is higher than the fuzzy scale average. Moreover, the legibility in each dimension will affect legibility dimensions a lot. Lynch’s theory of legibility in the spatial perception of parks and Kaplan’s theory of complexity and mystery criteria appear to be not fully responsive. It differs based on the features of each park, such as openness and closeness. For future research, it is better to comprehensively understand by using all dimensions of Kalpan’s theory: complexity, mystery, refuge, and prospect.
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1. Alvarez L, Borsi K, Rodrigues L. The role of social network analysis on participation and placemaking. Sustainable Cities and Society. 2017; 28: 118-126. doi: 10.1016/j.scs.2016.06.017
2. Angelidou M, Psaltoglou A. An empirical investigation of social innovation initiatives for sustainable urban development. Sustainable Cities and Society. 2017; 33: 113-125. doi: 10.1016/j.scs.2017.05.016
3. Motevalian N, Yeganeh M. Visually meaningful sustainability in national monuments as an international heritage. Sustainable Cities and Society 2020; 60. doi: 10.1016/j.scs.2020.102207
4. Yeganeh M, Baygi F, Sargazi A. Evaluation of environmental quality components on satisfaction, delight and behavior intentions of customers (Case study: Gorgan restaurants). American Journal of Research 2018; 84–99. doi: 0.26739/2573-5616-2018-3-2-10
5. Piga B, Morello E. Environmental design studies on perception and simulation: an urban design approach. Ambiances 2015. doi: 10.4000/ambiances.647
6. Rebernik N, Marušić BG, Bahillo A, Osaba E. A 4-dimensional model and combined methodological approach to inclusive Urban planning and design for ALL. Sustainable Cities and Society 2019; 44: 195–214. doi: 10.1016/j.scs.2018.10.001
7. Kaplan R, Kaplan S. The Experience of Nature: A Psychological Perspective. Cambridge University Press; 1989.
8. Dosen AS, Ostwald MJ. Evidence for prospect-refuge theory: A meta-analysis of the findings of environmental preference research. City Territ Archit. 2016; 3(1). doi: 10.1186/s40410-016-0033-1
9. Mansour Y. Educating Designing an Architectural Model Based on Natural Principles and Criteria. International Conference New Perspectives in Science Education; 2015.
10. Stamps AE. Mystery, Complexity, Legibility and Coherence: A Meta-analysis. J. Environ. Psychol. 2004; 24: 1-16. doi: 10.1016/S0272-4944(03)00023-9
11. Girnblett HR. Environmental cognition: The prediction of preference in rurai Indiana. Journal of Architectural and Planning Research. 1990; 7(3): 222-234.
12. Herzog TR, Kaplan S, Kaplan R. The prediction of preference for unfamiliar urban places. Population and Environment. 1982; 5: 43-59. doi: 10.1007/BF01359051
13. Memari S, Pazhouhanfar M. Role of Kaplan’s Preference Matrix in the Assessment of Building. Case of Gorgan, Iran; 2017.
14. Zarghami E, Ghanbaran A, Vaghar PS, Zameni M. The role of physical readability in the security of urban parks (Case study: People’s Park and Eram Park in Hamadan). Journal of Studies On Iranian-Islamic City. 2018; 8: 17-31.
15. Daviran S, Kariminezhad M. Urban identity and sense of place in new public spaces (Nahjolbalagheh Park in Tehran city). Hoviatshahr. 2014; 8: 81-92.
16. Sarmadi S, Shahcheraghi A, Fard LK. The Comparative Study of the Factors of Sensory Richness in the garden’s transition to park in Tehran (Case Studies: Iranian Garden and Niavaran Park). Hoviatshahr. 2020; 14: 5-18. doi: 10.30495/hoviatshahr.2020.15022
17. Bemanian M, Zare Z, Dehghan N, Jamalian S. Analysis of the spatial attractiveness and spatial dynamics of the town square in its conversion to the Collective Space. Journal of Urban Management. 2019; 56.
18. Warren WH, Rothman DB, Schnapp BH, Ericson JD. Wormholes in virtual space: From cognitive maps to cognitive graphs. Cognition. 2017; 166: 152-163. doi: 10.1016/j.cognition.2017.05.020
19. Topcu KD, Topcu M. Visual Presentation of Mental Images in Urban Design Education: Cognitive Maps. Procedia-Social and Behavioral Sciences. 2013; 51: 573-582. doi: 10.1016/j.sbspro.2012.08.208
20. Osóch B, Czaplińska A. City image based on mental maps—The case study of Szczecin (Poland). Miscellanea Geographica. 2019; 23(2): 111-119. doi: 10.2478/mgrsd-2019-0016
21. Larsen LG, Eppinga MB, Passalacqua P, et al. Appropriate complexity landscape modeling. Earth-Science Reviews. 2016; 160: 111-130. doi: 10.1016/j.earscirev.2016.06.016
22. Olazabal M, Pascual U. Use of fuzzy cognitive maps to study urban resilience and transformation. Environmental Innovation and Societal Transitions. 2016; 18: 18-40. doi: 10.1016/j.eist.2015.06.006
23. Turk YA, Sen B, Ozyavuz A. Students Exploration on Campus Legibility. Procedia - Social and Behavioral Sciences. 2015; 197: 339-347. doi: 10.1016/j.sbspro.2015.07.147
24. Harris V, Kendal D, Hahs AK, et al. Green space context and vegetation complexity shape people’s preferences for urban public parks and residential gardens. Landscape Research. 2017; 43(1): 150-162. doi: 10.1080/01426397.2017.1302571
25. Ohly H, White MP, Wheeler BW, et al. Attention Restoration Theory: A systematic review of the attention restoration potential of exposure to natural environments. Journal of Toxicology and Environmental Health, Part B. 2016; 19(7): 305-343. doi: 10.1080/10937404.2016.1196155
26. Cullen G. Townscape. Reinhold Book Corporation. Routledge; 1961.
27. Elliovson S. The Japanese garden. In: Kaplan S, Kaplan R (editors). Hurnanscape: Environments for people. Ann Arbor:Ulrich’s Books; 1978.
28. Prak NL. The Visual Perception of the Built Environment. Delft University Press; 1977.
29. Rapoport A, Kantor RE. Complexity and Ambiguity in Environmental Design. Journal of the American Institute of Planners. 1967; 33(4): 210-221. doi: 10.1080/01944366708977922
30. Ariannia N, Naseri N, Yeganeh M. Cognitive-emotional feasibility of the effect of visual quality of building form on promoting the sense of place attachment (Case study: Cultural iconic buildings of Iran’s contemporary architecture). Frontiers of Architectural Research. 2023. doi: 10.1016/j.foar.2023.10.002
31. Ghanbari S, Yeganeh M, Reza bemanian M. Architecture Typology of Rural Plain Houses Based on Formal Features, Case Study: (Talesh, Iran). Frontiers in Built Environment. 2022; 8. doi: 10.3389/fbuil.2022.856567
32. Kaplan R, Kaplan S, Ryan R. With People in Mind: Design and Management of Everyday Nature. Island Press; 1998.
33. Ashtari B, Yeganeh M, Bemanian M, et al. A Conceptual Review of the Potential of Cool Roofs as an Effective Passive Solar Technique: Elaboration of Benefits and Drawbacks. Frontiers in Energy Research. 2021; 9. doi: 10.3389/fenrg.2021.738182
34. Bourassa SC. The aesthetics of landscape. Belhaven Press; 1991.
35. Carlson A. Aesthetic preferences for sustainable landscapes: seeing and knowing. Forests and landscapes: linking ecology, sustainability and aesthetics. 2000; 31-41. doi: 10.1079/9780851995007.0031
36. Fry G, Tveit MS, Ode Å, et al. The ecology of visual landscapes: Exploring the conceptual common ground of visual and ecological landscape indicators. Ecological Indicators. 2009; 9(5): 933-947. doi: 10.1016/j.ecolind.2008.11.008
37. Yu K. Research on the quality evaluation of natural scenery—BIB-LCJ aesthetic evaluation measurement method. Journal of Beijing Forestry University. 1988; 10: 1-11.
38. Zhou C, Zhang Q, Sun Y. Scenic Beauty Estimation of Residential Quarter Green Area. Chinese Landscape Architecture. 2006; 62-67.
39. Zheng Y. Characteristics of Vegetation Community and Landscape Evaluation in the Urban Parks in Harbin. Northeast Forestry University; 2007.
40. Scott SC. Complexity and Mystery as Predictors of Interior Preferences. Journal of Interior Design. 1993; 19(1): 25-33. doi: 10.1111/j.1939-1668.1993.tb00149.x
41. Tveit M, Ode Å, Fry G. Key concepts in a framework for analysing visual landscape character. Landscape Research. 2006; 31(3): 229-255. doi: 10.1080/01426390600783269
42. Sevenant M, Antrop M. Cognitive attributes and aesthetic preferences in assessment and differentiation of landscapes. Journal of Environmental Management. 2009; 90(9): 2889-2899. doi: 10.1016/j.jenvman.2007.10.016
43. Yeganeh M. International Conference New Perspectives in Science Education. 2015.
44. Gifford R. Environmental psychology: Principles and practice. Optimal Books; 2007.
45. Liu M, Schroth O. Assessment of Aesthetic Preferences in Relation to Vegetation-Created Enclosure in Chinese Urban Parks: A Case Study of Shenzhen Litchi Park. Sustainability. 2019; 11(6): 1809. doi: 10.3390/su11061809
46. Tang IC, Sullivan WC, Chang CY. Perceptual Evaluation of Natural Landscapes. Environment and Behavior. 2014; 47(6): 595-617. doi: 10.1177/0013916513520604
47. Lynch K. The image of the city. MIT press Cambridge; 1960.
48. Salingaros NA, Mehaffy MW. A Theory of Architecture. UMBAU-VERLAG Harald Püschel. 2006.
49. Hase B, Heerwagen J. Phylogenetic design: A new approach for workplace environments. Journal for Quality and Participation. 2000; 23: 27-31.
50. Guelton B. “Mental maps”: Between memorial transcription and symbolic projection. Frontiers in Psychology. 2023; 14. doi: 10.3389/fpsyg.2023.1142238
51. Peer M, Brunec IK, Newcombe NS, et al. Structuring Knowledge with Cognitive Maps and Cognitive Graphs. Trends in Cognitive Sciences. 2021; 25(1): 37-54. doi: 10.1016/j.tics.2020.10.004
52. Ericson JD, Warren WH. Probing the invariant structure of spatial knowledge: Support for the cognitive graph hypothesis. Cognition. 2020; 200: 104276. doi: 10.1016/j.cognition.2020.104276
53. Kosko B. Fuzzy thinking: the new science of fuzzy logic. Hyperion; 1993.
54. Nugroho DP, Widiyanto S, Wardani DT. Comparison of Deep Learning-Based Object Classification Methods for Detecting Tomato Ripeness. International Journal of Fuzzy Logic and Intelligent Systems. 2022; 22(3): 223-232. doi: 10.5391/ijfis.2022.22.3.223
55. Hu C, Liu X, Pan Z, et al. Automatic Detection of Single Ripe Tomato on Plant Combining Faster R-CNN and Intuitionistic Fuzzy Set. IEEE Access. 2019; 7: 154683-154696. doi: 10.1109/access.2019.2949343
56. Ware C. Information visualization, perception for design, 3rd ed. Elsevier, Amsterdam; 2012.
57. Kärrholm M. The Materiality of Territorial Production. Space and Culture. 2007; 10(4): 437-453. doi: 10.1177/1206331207304356
58. Lawson B. Language of Space. Routledge; 2007. doi: 10.4324/9780080509969
59. Madanipour A. Public and Private Spaces of the City. Routledge; 2003. doi: 10.4324/9780203402856
60. Baradaran Motie M, Yeganeh M, Bemanian M. Assessment of greenery in urban canyons to enhance thermal comfort & air quality in an integrated seasonal model. Applied Geography. 2023; 151: 102861. doi: 10.1016/j.apgeog.2022.102861
61. Relph E. Place and Placelessness. Pion Limited; 2022.
62. Sack RD. Human Territoriality: Its Theory and History. Cambridge University Press; 1986.
63. Zadeh LA. Fuzzy sets. Information and Control. 1965; 8(3): 338-353. doi: 10.1016/s0019-9958(65)90241-x
64. Zadeh LA. Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. IEEE Transactions on Systems, Man, and Cybernetics. 1973; SMC-3(1): 28-44. doi: 10.1109/tsmc.1973.5408575
65. Ragin CC. Redesigning Social Inquiry. University of Chicago Press; 2008. doi: 10.7208/chicago/9780226702797.00
66. Golledge RG, Stimson RJ. Spatial Behavior A Geographic Perspective. Guilford Press; 1997.
67. Sakhaei H, Yeganeh M, Afhami R. Quantifying Stimulus-Affected Cinematic Spaces Using Psychophysiological Assessments to Indicate Enhanced Cognition and Sustainable Design Criteria. Frontiers in Environmental Science. 2022; 10. doi: 10.3389/fenvs.2022.832537
68. Soini K. Exploring human dimensions of multifunctional landscapes through mapping and map-making. Landscape and Urban Planning. 2001; 57(3-4): 225-239. doi: 10.1016/s0169-2046(01)00206-7
69. Mark DM, Freksa C, Hirtle SC, et al. Cognitive models of geographical space. International Journal of Geographical Information Science. 1999; 13(8): 747-774. doi: 10.1080/136588199241003
70. Badke‐Schaub P, Goldschmidt G, Meijer M. How Does Cognitive Conflict in Design Teams Support the Development of Creative Ideas? Creativity and Innovation Management. 2010; 19(2): 119-133. doi: 10.1111/j.1467-8691.2010.00553.x
71. Ahmadi S, Yeganeh M, Motie MB, et al. The role of neighborhood morphology in enhancing thermal comfort and resident’s satisfaction. Energy Reports. 2022; 8: 9046-9056. doi: 10.1016/j.egyr.2022.07.042
72. Carter H. The study of urban geography. Edward Arnold; 1981.
73. Schönfelder S, Axhausen KW. Structure and innovation of human activity spaces. Institut für Verkehrsplanung und Transportsysteme (IVT). 2004.
74. Zare Z, Yeganeh M, Dehghan N. Environmental and social sustainability automated evaluation of plazas based on 3D visibility measurements. Energy Reports. 2022; 8: 6280-6300. doi: 10.1016/j.egyr.2022.04.064
75. Mansour Y. Educating Designing an Architectural Model Based on Natural Principles and Criteria. International Conference New Perspectives in Science Education; 2015.
76. Shahbazi M, Yeganeh M, Bamanian MR. Meta-analysis of environmental vitality factors in open spaces. Motaleate Shahri. 2020; 9(34): 61-76.
77. Kandelan SN, Yeganeh M, Peyman S, et al. Environmental study on greenery planning scenarios to improve the air quality in urban canyons. Sustainable Cities and Society. 2022; 83: 103993. doi: 10.1016/j.scs.2022.103993
DOI: https://doi.org/10.54517/esp.v9i3.2024
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