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Relationships between the visual preferences of urban recreation area users and various landscape design elements
Urban Forestry & Urban Greening 14 (2015) 573–582
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Urban Forestry & Urban Greening journal homepage: www.elsevier.com/locate/ufug
Relationships between the visual preferences of urban recreation area users and various landscape design elements Ahmet Tu˘grul Polat, Ahmet Akay ∗ Department of Landscape Architecture, Faculty of Agriculture, University of Selcuk, Selc¸uk Üniversitesi Ziraat Fakü. . ., 42075 Konya, Turkey
a r t i c l e
i n f o
Keywords: Konya Landscape design Landscape visual quality Photo-questionnaire Recreation
a b s t r a c t The locations and the relationships between locations that have emerged with urbanization and the growth of cities have placed considerable pressures on city dwellers. In recent times, city dwellers have been seeking comfort both inside and outside their homes. The search for comfort outside of homes, in particular, has increasingly focused on satisfying both the physical and psychological needs of city dwellers. To satisfy such demands, efforts should be made to create locations with aesthetic and functional qualities. In this study, our aim was to evaluate the relationships between the visual quality of urban recreational areas and the structural and vegetation landscape elements of these areas with regards to the preferences of visitors and users. One-on-one interviews using photo-questionnaires were conducted in the study areas with 409 individuals. Based on our findings, it was observed that the water surface area, the widths of pedestrian walkways, the function of recreational areas, plant composition, plant color composition, and plant species diversity can positively affect the visual quality of a landscape area. Furthermore, it was determined that a lack of bush-type plants within the plant composition can have a negative effect on visual quality. © 2015 Elsevier GmbH. All rights reserved.
Introduction A healthy environment and a high standard of living are the most basic demands of modern societies (Simonic, 2006). In this context, the protection and development of green areas that are closely associated with the environment and human health are very important for urban dwellers, especially in dry or arid city centers (Acar and Sakıcı, 2008). Green areas within cities make significant contributions to the urban landscape, especially with regards to its visual quality. Many studies have been performed to date on the aesthetic quality of townscapes (Abkar et al., 2011; Bernasconi et al., 2009; Chen et al., 2009; Galindo and Hidalgo, 2005; Wong and Domroes, 2005). Emphasis should be placed on the perceptions of users when planning and managing public resources such as urban green areas. The incompatibility between the expectations of urban landscape users and the current status of the city may lead to various negative outcomes (Daniel, 2001). The perceptions and sentiments of individuals towards the environment may be associated with certain features of that environment. A coherent setting is orderly; it is organized into clear
∗ Corresponding author. Tel.: +90 3322232725; fax: +90 3322410108. E-mail addresses: [email protected], [email protected] (A. Akay). http://dx.doi.org/10.1016/j.ufug.2015.05.009 1618-8667/© 2015 Elsevier GmbH. All rights reserved.
areas. People can readily discern the presence of a few distinct regions or areas, and those make it easier to make sense of, or understand, a place. The important issue in considering legibility is distinctiveness. To increase legibility, a scene has to have some memorable components that help with orientation. In a legible place, one can imagine finding one’s way, not only to a destination but back again as well (Kaplan et al., 1998). The landscape preferences of individuals for a particular region can be determined, and specific design criteria based on these findings can be accepted for the region in question. How people perceive their environment and what they choose to consider and remember most can be determined and measured through the landscape preferences of individuals (Abkar et al., 2011). While researching the perception and preferences of individuals for natural (untouched) and naturalistic (designed using the characteristics of natural landscapes) areas, importance should be accorded to the different spatial variables that affect landscape preferences (Acar and Sakıcı, 2008). Perception of environmental quality is an important area of study for psychologists, geographers and other researchers in environmental and behavioral sciences (Brown and Daniel, 1987). Landscape perception is considered as a subcategory of environmental perception, and can be accepted as a function of the interaction between individuals and the landscape (Zube et al., 1982). Landscape quality arises from the relationships between the
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characteristics of the landscape and the effects of these characteristics on individuals (Daniel, 2001). Studies of landscape perceptions and preferences are the subject of the field of environmental psychology. van den Berg et al. (1998) mentions that the earlier studies focused on environmental management, planning, and design and the definition of general beauty to shape policies. Parallel to this, in their study, Daniel and Vining (1983) proposed a relationship between visual character and recreational experience. Daniel (2001) mentions that the visual quality of a landscape can be defined as “the relative aesthetic perfection of any landscape”; it can be measured based on its appreciation by the observer (De La Fuente et al., 2006; Lothian, 1999). The concept of visual quality has an important place within the definitions of landscape planning and landscape design. Crowe (1969, page 37) defined landscape planning as “sustaining the process that enables the usage of the limited area of the earth in a best way by the people and also provides the protection of its beauty and productivity” (Zube, 1987). Landscape design could be defined as art which depends on aesthetic principles and science and necessitates knowledge of the physical components of nature. The attractiveness of recreational areas is related directly to their visual richness and their natural and cultural origin. Currently, examining and describing the visual characteristics of any area within the context of recreational planning studies is of considerable importance worldwide; especially within the context of tourism and recreation, the most important factor regarding the natural environment is its visual and/or landscape quality (Clay and Daniel, 2000; Bulut and Yılmaz, 2007). Turkey’s urban recreation areas are insufficient in terms of both quality and quantity. In Turkey, “picnics” are the most common urban recreation activity (Özgüner, 2011). Across the country, which has experienced a period of a rapid growth, efforts are being made to increase the amount of green area per capita in urban environments. As a result of these efforts, the amount of green area per capita in the city of Konya has reached approximately 45 m2 (for both active and passive green areas). Urban parks and recreation areas account for a considerable portion of the green areas within the city, and contribute considerably to the abovementioned ratio for the city. In this study, an attempt was made to answer the question, “how do various structural and plant design features affect the visual quality of landscaping in urban recreational spaces?” The relationships between plant or structural landscaping elements and urban recreational spaces were assessed using experts’ definitions of landscaping and by considering the preferences of users. Methods To assess the visual quality of the urban recreational areas in this study, a psychophysical method was used (Bernasconi et al., 2009; Brown and Daniel, 1986; Daniel, 1990; Taylor et al., 1987; Wherrett, 2000; Zube et al., 1982). This method provides a compromise between perception-based and expert-based methods. The study was carried out based on the photograph-based scenic beauty evaluation method used by Daniel and Boster (1976). The methods used in the studies of Clay and Daniel (2000), Clay and Smidt (2004), Arriaza et al. (2004), Arriaza et al. (2005), Bernasconi et al. (2009) and Abkar et al. (2011) were also employed. The method in question consists of taking photographs of the area in phases, using a photo-questionnaire design, and applying a statistical analysis.
study. The area sizes, usage, function, and distribution within the city were taken into consideration in the selection of these areas. Birlik Park is 6.4 ha, Karaaslan Park is 18 ha, and Koza˘gac¸ Picnic Area is 18 ha in area. The study areas are mostly used for picnicrelated activities. Birlik Park is located to the north of the city on the Ankara road, Karaaslan Park is located to the southeast of the city on the Karaman road, and the Koza˘gac¸ Picnic Area is located to the southwest of the city on the Antalya ring road (Fig. 1). Photography For photography, a semi-professional digital camera with a 12million-pixel resolution, 18x optical zoom lens and panoramic shooting mode was used. Photographs were taken in June 2011 during weekdays and between 07:00 and 08:00 in the morning so that human factors were not included in the photographs. Photographs were shot as 3-phase panoramas in a manner that reflected all of the characteristics of the areas. Approximately 150 photographs in total were taken in all of the areas. The panoramic photograph field method, used in Rogge et al.’s (2007) study and Sevenant and Antrop’s (2009) study, was also employed. Following this, 12 photographs were selected with the aid of subject experts from the local administration and university; selection was performed such that the main design elements of each area were accurately reflected (Figs. 3–5). Each selected photograph of the recreational fields is defined according to the characteristics in Table 1 by the 12 subject experts (landscape architects, academics, and local government staff). Because the study population was 1 million, 400 people were considered when determining the sample size (˛ = 0.05 for ±0.03, ±0.05 and ±0.10 sampling errors) (Yazıcıo˘glu and Erdo˘gan, 2004). Questionnaire data from a total of 409 users who were considered within the context of the photo-questionnaire were taken into evaluation. Data on demographic characteristics of the users are provided on Fig. 2 (Polat et al., 2011). The demographic characteristics of participants accurately represent the entire population of the city of Konya. According to this data, nearly half of the 409 participants were women. Efforts were made to determine the preferences of woman users. Additionally, younger individuals between the ages of 16 and 30 constituted 58% of individuals who answered the questionnaire. With regard to the level of income, the low-income group represents nearly 70% of the study participants. With regard to their residence location, an equal distribution was identified between those residing outside the city and those residing in the central districts of the city. Photo-questionnaire Four photographs for each recreation area were placed on A4size photograph paper. The photo-questionnaire also contained questions on gender, age, occupation, income level, education, and residence status of the users. Five sets of photo-questionnaire forms were designed accordingly. Inventory forms were also prepared to record data. Questionnaires were applied within the context of one-on-one interviews with users in the park areas. First, the demographic characteristics of the users were ascertained. Second, the users were asked to evaluate the visual quality of each photograph on a Likert scale (scored between 1 and 5) (Kaplan and Kaplan, 1989; Kaplan et al., 2006).
Study area
Statistical analysis
Birlik Park, Karaaslan Park, and the Koza˘gac¸ Picnic Area in the immediate surroundings of Konya were selected as the areas of
As a final step, the collected data were arranged on an Excel spreadsheet and transferred into SPSS 15.0 software.
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Fig. 1. Locations of the Study Areas within Konya.
Fig. 2. Demographic characteristics of individuals who responded to the questionnaire.
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Fig. 3. Study Photographs used for Birlik Park.
The visual quality score averages of each photograph were then calculated. Spearman’s rho correlation analysis was used for structural elements and plant design elements between the average visual quality score of each photograph and the definitions/evaluations provided by the experts on the photographs. Results Visual quality scores of photographs of the recreational areas The average participant scores of the visual quality of each photograph in the photo-questionnaire were calculated. The calculated average scores are provided together with the values for the landscape design characteristics in Table 2. An examination of the table reveals that the visual quality scores of photographs from the Kozaa˘gac¸ Picnic Area and from the Karaaslan Park were higher than the visual quality scores of photographs from Birlik Park. The KA2 photograph from Karaaslan Park and the KO3 photograph from Kozaa˘gac¸ Picnic Area were the most liked and appreciated photographs, and both were given scores of 4.47. The B2 photograph from Birlik Park was the least appreciated photograph, with a score of 3.32.
Relationships between user demographics and the visual quality of urban recreational areas A Chi-square analysis was used to determine the relationship between user demographics and the visual quality scores (Polat et al., 2011). For the Chi-square analysis, relations were identified between users’ age, education, occupation and income level, and the visual quality of urban recreational areas (Table 3).
Relationship between the visual quality of recreational areas and landscape design elements Tables 4 and 5 show the results of the Spearman’s rho correlation analysis, which was performed to determine the relationship between the visual quality of recreational areas and landscape design elements. Based on these results, it was determined that the structural design elements, the water surface area (A4/VQ 0.731**), the width of the pedestrian walkway (A11/VQ 0.656*) and the function of recreational areas (A13/VQ 0.580*) were associated with the visual quality of recreational areas. Stagnant water surfaces and wide enough pedestrian paths increase the visual quality of parks. Among various plant design elements, plant color composition (harmony among colors of leaves, flowers, and stems of the
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Fig. 4. Study Photographs used for Karaaslan Park.
specific plants within the composition) (B6/VQ 0.734**); plant composition (harmony among trees, bushes, flowers, and ground cover plant species with their forms) (B8/VQ 0.629*); and plant species diversity (B10/VQ 0.658*) were all related to the visual quality of the landscape. The compositions of plants and their colors and plant species diversity are among the main elements of the visual quality of landscape areas. Furthermore, it was determined that the type of water element used is associated with water surface area (A3/A4 0.598*) and the amount of urban furniture (A3/A5 0.580*). The visually appreciated landscapes are formed with a convenient amount of urban furniture around the stagnant-surface artificial lakes. Among structural design elements, it was determined that the water surface area is associated with elements related to the amount of urban furniture (A4/A5 0.623*) and the width of the pedestrian path (A4/A11 0.690*). It was determined that the slope is associated with the function of recreational areas (A12/A13 0.585*). Certain correlations were also identified between the plant design elements. Relationships were found between leaf intensity and the amount of shadow (B3/B11 0.914**), between plant composition and plant color composition (B8/B6 0.804**), and between plant composition and plant design function (B8/B9 0.631*). Moreover, negative relationships were identified between the lack of bush-forming plants within the area and the plant color
composition (B5/B6 −0.629*), along with the plant composition (B5/B8 −0.630*) and the plan design function (B5/B9 −0.677*). Discussion Previous studies have suggested that landscape perception is associated with socio-demographic factors (Dramstad et al., 2006; Lothian, 1999; Rogge et al., 2007; Polat et al., 2011). Within the literature, there are numerous studies on the subject of landscape perception and preferences and the aesthetic preferences of individuals. Factors that affect aesthetic preferences are the features of the landscape and the characteristics of the observer (Sevenant and Antrop, 2010). Thus, it was ensured that the demographic characteristics of the participants displayed a distribution that was representative of the general population of the city. However, participation was greater among individuals within the 16to 30-year-old age groups compared with the other age groups. We believe that the greater participation of this age group was because of the relatively young overall population of the country and because schools were on holiday at the time of the study. We believe that the distribution of the participants’ income level was the consequence of the same factors. This study was realized in Konya, one of the strongholds of religious conservatism in Turkey. In this city, one could see women in public life, but the
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Table 1 Landscape design elements. A
Structural Design Characteristics
Categories
A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 B B1 B2 B3 B4 B5 B6 B7 B8 B9
Topographic structure of land Scale level Type of water element Water surface area Amount of urban furniture Type of urban furniture Surface pavement area ratio Type of surface pavement material Encirclement element Height of encirclement element Width of pedestrian walkway Slope status Recreational function Number of buildings Plant Design Characteristics Plant types Plants according to type of leaves Leaf intensity Tree usage according to their forms Bush usage according to their forms Plant color composition Number of plants Plant composition Plant design function
B10 B11
Plant species diversity Shadow amount
Flat Foreground No element No water None None None None None None None Straight Picnic None Categories Trees Coniferous Light Oval Vertical Monochrome Solitary Tree Complementary Symbolizing Few None
Lightly sloping Middle-ground Decorative pool Live 1 pcs Bower Low Concrete Wall Low Narrow Step Walking 1 pcs
Broad-leafed Medium Scenery Horizontal Complementary color Double Attractive Indicative Medium Less than 30%
segregation of women and men in public culture does not ease enough to include women in questionnaires. Therefore, concentrated efforts were focused on determining the preferences of female users. The photographs used to represent real landscapes and the methods used to obtain them are subjects that deserve further scrutiny. During the evaluation of landscape preferences, direct experience can be better represented by performing metaanalysis through photographs (Stamps, 1990). Photographs can be used as visual copies of real landscapes (Schuttleworth, 1980).
Middle sloping Background Artificial lake Still 2–3 Pergola Medium Parquet Fence Medium Normal Ramp Sport 2–3
Very Slopping Artificial Waterfall More than 3 Bank High Natural stone Wall/fence High Wide
Water Channel
Dustbin
Lighting
Sand
Soil
Rest More than 3
Scenery
Social interaction
Bushes
Groundcovers
Climbing plant
flowers
Intensive Pillar None
Conic
Pendulous
Composite color Group Bush Compatible Changing Many 30% and more
Tree-bush Highlighter
Tree-flower Distracter
Bush-flower
If photographs are taken by including the notable characteristics of the area while excluding its other characteristics, these photographs will not be sufficiently representative of the area (Scott and Canter, 1997). However, there is also the criticism that photographs cannot fully reflect and describe the real landscapes. Despite such criticism, photographs are used widely in studies ˜ et al., 2009). Sensibecause they save time and reduce costs (Canas tivity was demonstrated during the photo shoot phase of this study by allowing photographs to represent each park as a whole, without allowing subjective misrepresentation and physical errors.
Table 2 The visual quality scores and design characteristics of the photographs. Photo No
B1
B2
B3
B4
KA1
KA2
KA3
KA4
KO1
KO2
KO3
KO4
VQ Std. D A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11
3.39 0.653 1 2 4 2 4 4 2 2 3 3 1 1 1 2 1 2 2 2 3 1 3 1 1 2 2
3.32 0.675 1 2 1 1 4 6 2 3 1 1 2 1 2 3 1 2 1 3 1 2 1 3 7 2 2
3.48 0.669 1 1 1 2 4 4 3 3 1 1 3 1 1 1 1 2 3 2 3 2 3 1 4 1 3
3.85 0.762 1 2 4 2 4 4 2 3 3 3 2 1 4 1 1 2 2 2 1 2 3 3 4 2 2
4.30 0.811 1 3 3 3 4 2 3 3 3 3 4 1 5 2 1 2 1 1 1 3 3 3 7 1 2
4.47 0.924 1 2 3 3 4 2 3 3 3 3 4 2 6 1 2 1 1 3 2 3 3 5 7 3 1
4.37 0.944 1 2 3 3 4 6 4 3 3 3 4 2 6 2 1 1 1 1 1 3 3 5 6 3 1
3.84 0.824 1 2 2 2 3 6 2 3 1 1 3 1 6 1 1 2 1 2 3 1 1 1 1 2 2
4.06 1.112 1 2 1 1 1 1 1 1 1 1 3 1 4 1 1 1 3 2 3 2 3 1 1 3 3
4.44 0.886 1 3 3 3 4 2 3 4 1 1 3 1 5 1 1 2 3 2 3 2 3 3 2 3 3
4.47 0.917 1 3 3 3 4 2 2 3 1 1 3 1 6 1 1 2 3 2 1 3 3 3 2 3 3
4.24 0.948 2 3 1 1 1 1 4 3 3 3 2 3 6 1 5 2 3 2 2 3 3 4 2 3 3
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Fig. 5. Study Photographs used for Koza˘gac¸ Park.
The significant contributions of vegetation and water-related elements to the visual quality of landscapes have been mentioned in numerous previous studies. According to Wong and Domroes (2005), landscapes that maintain a proper balance
between the water element and vegetation have very high appreciation ratios. In parallel with our findings, it was previously stated that the vegetation structures of the landscapes with beautiful scenery include a large diversity of plants (Avıˇzıene˙ et al.,
Table 3 Relationships between user demographics and visual quality of photographs. Photo no.
Demographic characteristics of the participants Gender X2
B1 B2 B3 B4 KA1 KA2 KA3 KA4 KO1 KO2 KO3 KO4
4.502 2.665 15.877 4.121 3.750 6.844 1.542 5.036 5.124 1.562 1.051 1.258
P-value * 0.01 ** 0.05 *** 0. 10.
Age P 0.342 0.615 0.003* 0.390 0.441 0.144 0.819 0.284 0.275 0.816 0.789 0.869
X2 31.679 20.854 23.891 9.932 9.399 10.608 3.517 22.428 23.693 11.124 17.621 4.919
Education X2
P *
0.002 0.053*** 0.021** 0.622 0.669 0.563 0.991 0.033** 0.022** 0.518 0.040** 0.961
30.542 23.718 17.963 9.274 19.249 20.573 10.319 25.263 18.486 13.384 7.110 17.034
Occupation P *
0.002 0.022** 0.117 0.679 0.083*** 0.057*** 0.588 0.014** 0.102 0.342 0.626 0.148
Income (monthly)
Residence
X2
P
X2
P
X2
P
26.977 28.303 37.046 26.327 39.065 36.621 19.300 52.181 30.830 17.149 23.686 30.022
0.519 0.448 0.118 0.555 0.080*** 0.127 0.889 0.004* 0.325 0.946 0.309 0.362
15.872 20.065 19.509 12.299 8.606 11.075 17.827 9.495 15.732 17.711 11.926 20.020
0.197 0.066*** 0.077*** 0.422 0.736 0.522 0.121 0.660 0.204 0.125 0.218 0.067***
10.798 12.321 29.759 10.483 11.532 15.909 12.319 11.105 8.369 12.696 5.965 8.756
0.546 0.420 0.003* 0.574 0.484 0.195 0.420 0.520 0.756 0.392 0.743 0.724
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Table 4 Relationships between the visual quality of recreational areas and the structural landscape design elements. Spearman’s rho
Correlation coefficient sig. (2-tailed) VQ
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A1
0.044 0.893
A2
0.573 0.051
0.398 0.200
A3
0.267 0.401
−0.370 0.236
0.158 .623
A4
0.731** 0.007
−0.419 0.175
0.314 0.320
0.598* 0.040
A5
0.115 0.721
−0.575 0.051
−0.092 0.776
0.580* 0.048
0.623* 0.031
A6
−0.500 0.098
−0.452 0.140
−0.549 0.065
0.146 0.652
0.027 0.934
0.405 0.192
A7
0.395 0.204
0.462 0.130
0.234 0.464
−0.035 0.913
0.385 0.217
0.154 0.634
−0.069 0.831
A8
0.395 0.203
0.057 0.860
0.382 0.220
0.063 0.845
0.484 0.111
0.363 0.247
0.119 0.713
0.540 0.070
A9
0.169 0.599
0.302 0.341
0.110 0.733
0.537 0.072
0.206 0.521
0.159 0.622
−0.075 0.817
0.460 0.132
−0.127 0.695
A10
0.169 0.599
0.302 0.341
0.110 0.733
0.537 0.072
0.206 0.521
0.159 0.622
−0.075 0.817
0.460 0.132
−0.127 0.695
−0.322 0.308
0.076 0.815
0.000 1.000
0.690* 0.013
0.165 0.609
−0.084 0.796
0.398 0.200
0.261 0.413
0.051 0.875
0.051 0.875
A11
0.656* 0.020
A12
0.413 0.182
0.632* 0.027
0.121 0.709
−0.112 0.729
0.069 0.832
−0.224 0.484
−0.202 0.528
0.717** 0.009
0.109 0.737
0.572 0.052
0.572 .052
0.242 0.448
A13
0.580* 0.048
0.405 0.192
0.503 0.096
−0.038 0.906
0.320 0.310
−0.367 0.240
−0.102 0.751
0.492 0.105
0.397 0.202
0.199 0.536
.199 .536
0.455 0.138
−0.210 0.513
−0.055 0.865
0.125 0.700
−0.007 0.983
0.398 0.200
0.485 0.110
0.053 0.869
−0.171 0.595
0.261 0.412
.261 0.412
−0.062 0.848
** *
−0.370 0.236
A13
.
A11
A14
A12
0.585* 0.046 −0.064 0.844
−0.203 0.526
Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed).
2007; Uzun and Müderrisoglu, 2011). Strong relationships have been identified between the heterogeneity and diversity of the landscape and the landscape preferences of individuals (Hunziker, 1995; Zube, 1987). Bernasconi et al. (2009) stated in a study on automated transportation systems that turf, bush, and especially tree vegetation have a positive effect on preferences. The results of our study are entirely in agreement with these findings. In numerous previous studies, positive correlations were identified between the water element and the preference scores (Herzog and Barnes, 1999; Purcell et al., 1994). Acar et al. (2006) identified in their study a positive relation between water mobility and the visual quality of the landscape. This study suggested a positive relationship between water surface area and visual quality; this finding was also confirmed by the abovementioned results of our study. In Turkish culture, gardens are of considerable significance both as a water factor and a landscape type (Aksoy, 2011). The most important elements of Turkish gardens are water used for cooling, trees for providing shade, and music for resting and entertainment. Moreover, adding movement to water through the use of sprinklers is a common feature in Turkish gardens. The use of water is also essential in Egyptian, Persian, Japanese and baroque gardens.
Preferences regarding the use of water and vegetation diversity have remained largely unchanged from old garden landscapes to modern green areas. Human structures and artificial elements negatively affect the visual quality of landscapes (Acar et al., 2006; Arriaza et al., 2004). From this point of view, elements such as surface pavement materials, encirclement elements and the number of structures were expected to have a negative effect on the visual quality of the landscape. However, our study did not produce positive or negative results associated with these elements. The topographic structure of the land also affects the visual quality of the landscape. Aminzadeh and Ghorashi (2007) stated in their studies on forest parks that areas with flat topographies generally have higher visual qualities. However, such an effect could not be identified in our study. It is believed that Konya’s extremely flattened topography and the familiarity of the study participants with this type of topography contributed to such a result. The findings of our study are specific to the study region. Further studies conducted with different physical, cultural, and social environments are necessary to determine whether our study results are generally applicable.
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Table 5 Relationships between visual quality of recreational areas and the plant design elements. Spearman’s rho
Correlation Coefficient Sig. (2-tailed) VQ
B1
B2
B3
B4
B1
0.331 0.293
B2
−0.391 0.209
−0.214 0.504
B3
0.106 0.743
0.041 0.900
0.211 0.511
B4
−0.188 0.557
0.354 0.260
0.000 1.000
0.000 1.000
B5
−0.252 0.430
0.000 1.000
0.000 1.000
0.400 0.198
0.158 0.624
B5
B6
B7
B8
B6
0.734** 0.007
0.488 0.108
−0.331 0.293
−0.043 0.895
−0.226 0.480
−0.629* 0.029
B7
0.519 0.084
0.199 0.535
−0.258 0.418
0.490 0.106
−0.387 0.214
0.000 1.000
B8
0.629* 0.029
0.572 0.052
−0.354 0.259
−0.294 0.354
0.000 1.000
−0.630* 0.028
0.804** 0.002
0.240 0.452
B9
0.186 0.562
0.165 0.608
−0.143 0.658
−0.528 0.078
0.086 0.791
−0.677* 0.016
0.572 0.052
0.000 1.000
0.631* 0.028
B10
0.658* 0.020
0.423 0.171
−0.548 0.065
0.289 0.363
0.137 0.671
0.000 1.000
0.404 0.193
0.283 0.373
0.509 0.091
−0.055 0.865
0.392 0.208
0.914** 0.000
0.000 1.000
0.386 0.216
−0.098 0.762
0.210 0.512
−0.420 0.174
B11 ** *
−0.009 0.977
B9
B10
0.455 0.137
−0.207 .0518 −0.499 0.099
0.115 0.721
Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed).
Conclusion We can divide and categorize landscape design in urban recreation areas as structural or vegetation-related. These characteristics are specifically determined by landscape architecture. Landscape architecture provides designs in which living and non-living elements of the landscape are used in combination. Each design fulfills certain criteria regarding these two areas. Studies on the use of plant materials and the plant-related designs that are employed are relatively limited in the literature. Further study is necessary to improve the area’s visual quality value and to provide functional solutions in outdoor areas. Understanding and evaluating the visual quality of landscapes is a complicated process. It is understood that visual quality is based on both individual and environmental variables. In this respect, the visual quality of a landscape can be likened to an unresolved multiple-variable equation. In our study, we have focused on the visual quality of urban recreational landscape areas. Certain design elements of the landscape were considered, and evaluations were performed accordingly. The structural and plant design elements that affect the visual quality were identified. In parallel with findings from previous studies, our results have shown that the water elements and plant materials have a strong effect on visual quality. It was observed that the surface area of the water element, the width of the pedestrian walkway, the function of the recreational area, the plant composition, the plant color composition, and the plant species diversity all positively affected the visual quality of the landscape area. It was also demonstrated that the lack of bush-type plants within the plant composition had a negative effect on the visual quality.
Many studies have previously been conducted on the visual quality of landscaping, and various results have been obtained. The positive effect of water and vegetation on natural and designed landscaping is now well recognized. The results of our study are also in agreement with the findings of previous studies. However, the identification of tangible criteria for structural and plant landscaping, such as the water surface area, the pedestrian walkway width, the number of reinforcement elements, the plant composition, and the plant color composition, further underscores the significance of this study. In this study, the relationships between elements of structural and plant landscapes and the visual quality of areas are examined to find data highlighting urban landscape design. However, it is found that structural and plant landscape elements, such as surface pavements, encirclement elements, buildings, plants according to type of leaves and number of plants, have no specific effect on the visual quality of the landscape. It will be beneficial to evaluate these elements in forthcoming studies. The results of our study can potentially be used for the planning, design and management of urban recreational areas. These findings should especially be taken into consideration in landscape and rehabilitation projects that focus on increasing the visual quality of landscape areas. When designing urban recreation areas, the inclusion of water surfaces formed by artificial lakes should be considered. The characteristics and the general scenic beauty of the area should be considered before designs with different types of activity are proposed for the recreational area. Additionally, further emphasis and attention should be accorded to the plant designs, the plant color compositions, and the plant diversity. Further studies on landscape management, especially concerning planting and maintenance projects,
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should be conducted with consideration of the abovementioned data. Increasing the visual quality of urban recreational areas will significantly contribute to the physical structure and layout of the city, and provide further comfort and a better psychological environment for city dwellers. Landscape areas with high visual quality will improve the identity of the city, positively contribute to its appearance and vision, and provide various socioeconomic benefits. Such landscapes will similarly improve the quality of life within the city owing to their positive effects on the psychological health of city dwellers and their ability to alleviate the negative influence of structures on city life. References Abkar, M., Kamal, M.S., Maulan, S., Davoodi, S.R., 2011. Determining the visual preference of urban landscapes. Sci. Res. Essays 6 (9), 1991–1997. Acar, C., Sakıcı, C¸., 2008. Assessing landscape perception of urban rocky habitats. Build. Environ. 43, 1153–1170. Acar, C., Kurdoglu, B.C., Kurdoglu, O., Acar, H., 2006. Public preferences for visual quality and management in the Kackar Mountains National Park (Turkey). Int. J. Sustainable Dev. World Ecol. 13 (6), 499–512. Aksoy, Y., 2011. Gardening in Ottoman Turks. Int. J. Electron.; Mech. Mechatron. Eng. 2 (4), 345–351. Aminzadeh, B., Ghorashi, S., 2007. Scenic landscape quality and recreational activities in Natural Forest Parks, Iran. Int. J. Environ. Res. 1 (1), 5–13. ˜ ˜ Arriaza, M., Canas, J.F., Canas, J.A., Ruiz, P., Gonzáles, J., Barea, F., 2005. Landscape assessment via regression analysis. In: Paper Prepared for Presentation at the XIth Congress of the EAAE (European Association of Agricultural Economists), August 24–27, 2005, Copenhagen, Denmark. ˜ ˜ ˜ Arriaza, M., Canas-Ortega, J.F., Canas-Madue no, J.A., Ruiz-Aviles, P., 2004. Assessing the visual quality of rural landscapes. Landscape Urban Plann. 69, 115–125. ˙ D., Pakalnis, R., Sendˇzikaite, ˙ J., 2007. “Preservation, Assessment and ManAvıˇzıene, agement of Scenic Landscape in Lithuania” IGU/LUCC Central Europe Conference 2007 “Man in the landscape across frontiers: Landscape and land use change in Central European border regions” , 28 August–4 September 2007, Slovenia. Bernasconi, C., Strager, M.P., Maskey, V., Hasanmyer, M., 2009. Assessing public preferences for design and environmental attributes of an urban automated transportation system. Landscape Urban Plann. 90, 155–167. Brown, T.C., Daniel, T.C., 1986. Predicting scenic beauty of forest timber stands. For. Sci. 32, 471–487. Brown, T.C., Daniel, T.C., 1987. Context effects in perceived environmental quality* assessment: scene selection and landscape quality ratings. J. Environ. Psychol. 7, 233–250. Bulut, Z., Yılmaz, H., 2007. Determination of landscape beauties through visual quality assessment method: a case study for Kemaliye (Erzincan/Turkey). Environ. Monitor. Assess. 141 (1–3), 121–129. ˜ Canas, I., Ayuga, E., Ayuga, F., 2009. A contribution to the assessment of scenic quality of landscapes based on preferences expressed by the public. Land Use Policy 26, 1173–1181. Chen, B., Adimo, O.A., Bao, Z., 2009. Assessment of aesthetic quality and multiple functions of urban green space from the users’ perspective: the case of Hangzhou Flower Garden, China. Landscape Urban Plann. 93, 76–82. Clay, G.R., Daniel, T.C., 2000. Scenic landscape assessment: the effects of land management jurisdiction on public perception of scenic beauty. Landscape Urban Plann. 49, 1–13. Clay, G.R., Smidt, R.K., 2004. Assessing the validity and reliability of descriptor variables used in scenic highway analysis. Landscape Urban Plann. 66, 239–255. Crowe, S., 1969. Landscape Planning. International Union for the Conservation of Nature and Natural Resources, Morges, Switzerland. Daniel, T.C., Vining, J., 1983. Methodological issues in the assessment of landscape quality. In: Altman, I., Wohlwill, J. (Eds.), Human Behavior and Environment, vol. 6. Plenum Press, New York, NY, pp. 39–84. Daniel, T.C., 2001. Whither scenic beauty? Visual landscape quality assessment in the 21st century. Landscape Urban Plann. 54, 267–281.
Daniel, T.C., 1990. Measuring the quality of the natural environment: a psychophysical approach. Am. Psychol. 45 (5), 633–637. Daniel, T.C., Boster, R.S., 1976. Measuring landscape esthetics: the scenic beauty estimation method. In: USDA Forest Service Research Paper, RM-167. Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO. De La Fuente, G., Atauri, J.A., de Lucio, J.V., 2006. Relationship between landscape visual attributes and spatial pattern indices: a test study in Mediterraneanclimate landscapes. Landscape Urban Plann. 77, 393–407. Dramstad, W.E., Tveit, M.S., Fjellstad, W.J., Fry, G.L.A., 2006. Relationships between visual landscape preferences and map-based indicators of landscape structure. Landscape Urban Plann. 78, 465–474. Galindo, P., Hidalgo, C., 2005. Aesthetic preferences and the attribution of meaning: environmental categorization processes in the evaluation of urban scenes. Int. J. Psychol. 40 (1), 19–26. Herzog, T.R., Barnes, G.J., 1999. Tranquillity and preference revisited. J. Environ. Psychol. 19, 171–181. Hunziker, M., 1995. The spontaneous reafforestation in abandoned agricultural lands: perception and aesthetic assessment by locals and tourists. Landscape Urban Plann. 31, 399–410. Kaplan, S., Kaplan, R., 1989. The Experience of Nature: A Psychological Perspective. Cambridge University Press, Cambridge. Kaplan, A., Tas¸kın, T., Önenc¸, A., 2006. Assessing the visual quality of rural and urbanfringed landscapes surrounding livestock Farms. Biosyst. Eng. 95 (3), 437–448. Kaplan, S., Kaplan, R., Ryan, R., 1998. With People in Mind, Design and Management of Everyday Nature. Island Press, Washington, pp. 225p. Lothian, A., 1999. Landscape and the philosophy of aesthetics: is landscape quality inherent in the landscape or in the eye of the beholder? Landscape Urban Plann. 44, 177–198. Özgüner, H., 2011. Cultural differences in attitudes towards urban parks and green spaces. Landscape Res. 36 (5), 599–620. Polat, A.T., Güngör, S., Adıyaman, S., 2011. The relationships between demographic characteristics of users and the Visual Quality of Urban Recreation Areas in Konya and Its environs. In: I. International. Mediterranean Forest and Environment Symposium, 26–28 October 2011, Turkey, pp. 607–617. Purcell, A.T., Lamb, R.J., Peron, E.M., Falchero, S., 1994. Preference or preferences for landscape? J. Environ. Psychol. 14, 195–209. Rogge, E., Nevens, F., Gulinck, H., 2007. Perception of rural landscapes in Flanders: looking beyond aesthetics. Landscape Urban Plann. 82, 159–174. Schuttleworth, S., 1980. The use of photographs as an environmental presentation medium in landscape studies. J. Environ. Manage. 11, 61–76. Scott, M.J., Canter, D.V., 1997. Picture or place? Amultiple sorting study of landscape. J. Environ. Psychol. 17, 263–281. Sevenant, M., Antrop, M., 2009. Cognitive attributes and aesthetic preferences in assessment and differentiation of landscapes. J. Environ. Manage. 90, 2889–2899. 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, 827–842. Simonic, T., 2006. Urban landscape as a restorative environment: preferences and design considerations. Acta Agric. Sloven. 87 (2), 325–332. Stamps, A.E., 1990. Use of photographs to simulate environments: a meta-analysis. Percept. Mot. skills 71 (1), 907–913. Taylor, J.G., Zube, E.H., Sell, J.L., 1987. Landscape assessment and perception research methods. In: Marans, R.W., Michelson, W., Bechtel, R.B. (Eds.), Methods in Environmental and Behavioral Research. Van Nostrand, New York, NY, pp. 361–393. Uzun, O., Müderrisoglu, H., 2011. Visual landscape quality in landscape planning: examples of Kars and Ardahan cities in Turkey. Afr. J. Agric. Res. 6 (6), 1627–1638. van den Berg, A.E., Vlek, C.A.J., Coeterier, J.F., 1998. Group differences in the aesthetic evaluation of nature development plans: a multilevel approach. J. Environ. Psychol. 18, 141–157. Wherrett, J.R., 2000. Creating landscape preference models using internet survey techniques. Landscape Res. 25 (1), 79–96. Wong, K.K., Domroes, M., 2005. The visual quality of urban park scenes of Kowloon Park, Hong Kong: likeability, affective appraisal, and cross-cultural perspectives. Environ. Plann. B: Plann. Design 32, 617–632. Yazıcıo˘glu, Y., Erdo˘gan, S., 2004. SPSS Applied Scientific Research Methods. Detay Publishing, Ankara. Zube, E.H., 1987. Perceived land use patterns and landscape values. Landscape Ecol. 1 (1), 37–45. Zube, L.H., Sell, J.L., Taylor, J.G., 1982. Landscape perception: research, application and theory. Landscape Plann. 9, 1–33.
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Urban Forestry & Urban Greening journal homepage: www.elsevier.com/locate/ufug
Relationships between the visual preferences of urban recreation area users and various landscape design elements Ahmet Tu˘grul Polat, Ahmet Akay ∗ Department of Landscape Architecture, Faculty of Agriculture, University of Selcuk, Selc¸uk Üniversitesi Ziraat Fakü. . ., 42075 Konya, Turkey
a r t i c l e
i n f o
Keywords: Konya Landscape design Landscape visual quality Photo-questionnaire Recreation
a b s t r a c t The locations and the relationships between locations that have emerged with urbanization and the growth of cities have placed considerable pressures on city dwellers. In recent times, city dwellers have been seeking comfort both inside and outside their homes. The search for comfort outside of homes, in particular, has increasingly focused on satisfying both the physical and psychological needs of city dwellers. To satisfy such demands, efforts should be made to create locations with aesthetic and functional qualities. In this study, our aim was to evaluate the relationships between the visual quality of urban recreational areas and the structural and vegetation landscape elements of these areas with regards to the preferences of visitors and users. One-on-one interviews using photo-questionnaires were conducted in the study areas with 409 individuals. Based on our findings, it was observed that the water surface area, the widths of pedestrian walkways, the function of recreational areas, plant composition, plant color composition, and plant species diversity can positively affect the visual quality of a landscape area. Furthermore, it was determined that a lack of bush-type plants within the plant composition can have a negative effect on visual quality. © 2015 Elsevier GmbH. All rights reserved.
Introduction A healthy environment and a high standard of living are the most basic demands of modern societies (Simonic, 2006). In this context, the protection and development of green areas that are closely associated with the environment and human health are very important for urban dwellers, especially in dry or arid city centers (Acar and Sakıcı, 2008). Green areas within cities make significant contributions to the urban landscape, especially with regards to its visual quality. Many studies have been performed to date on the aesthetic quality of townscapes (Abkar et al., 2011; Bernasconi et al., 2009; Chen et al., 2009; Galindo and Hidalgo, 2005; Wong and Domroes, 2005). Emphasis should be placed on the perceptions of users when planning and managing public resources such as urban green areas. The incompatibility between the expectations of urban landscape users and the current status of the city may lead to various negative outcomes (Daniel, 2001). The perceptions and sentiments of individuals towards the environment may be associated with certain features of that environment. A coherent setting is orderly; it is organized into clear
∗ Corresponding author. Tel.: +90 3322232725; fax: +90 3322410108. E-mail addresses: [email protected], [email protected] (A. Akay). http://dx.doi.org/10.1016/j.ufug.2015.05.009 1618-8667/© 2015 Elsevier GmbH. All rights reserved.
areas. People can readily discern the presence of a few distinct regions or areas, and those make it easier to make sense of, or understand, a place. The important issue in considering legibility is distinctiveness. To increase legibility, a scene has to have some memorable components that help with orientation. In a legible place, one can imagine finding one’s way, not only to a destination but back again as well (Kaplan et al., 1998). The landscape preferences of individuals for a particular region can be determined, and specific design criteria based on these findings can be accepted for the region in question. How people perceive their environment and what they choose to consider and remember most can be determined and measured through the landscape preferences of individuals (Abkar et al., 2011). While researching the perception and preferences of individuals for natural (untouched) and naturalistic (designed using the characteristics of natural landscapes) areas, importance should be accorded to the different spatial variables that affect landscape preferences (Acar and Sakıcı, 2008). Perception of environmental quality is an important area of study for psychologists, geographers and other researchers in environmental and behavioral sciences (Brown and Daniel, 1987). Landscape perception is considered as a subcategory of environmental perception, and can be accepted as a function of the interaction between individuals and the landscape (Zube et al., 1982). Landscape quality arises from the relationships between the
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characteristics of the landscape and the effects of these characteristics on individuals (Daniel, 2001). Studies of landscape perceptions and preferences are the subject of the field of environmental psychology. van den Berg et al. (1998) mentions that the earlier studies focused on environmental management, planning, and design and the definition of general beauty to shape policies. Parallel to this, in their study, Daniel and Vining (1983) proposed a relationship between visual character and recreational experience. Daniel (2001) mentions that the visual quality of a landscape can be defined as “the relative aesthetic perfection of any landscape”; it can be measured based on its appreciation by the observer (De La Fuente et al., 2006; Lothian, 1999). The concept of visual quality has an important place within the definitions of landscape planning and landscape design. Crowe (1969, page 37) defined landscape planning as “sustaining the process that enables the usage of the limited area of the earth in a best way by the people and also provides the protection of its beauty and productivity” (Zube, 1987). Landscape design could be defined as art which depends on aesthetic principles and science and necessitates knowledge of the physical components of nature. The attractiveness of recreational areas is related directly to their visual richness and their natural and cultural origin. Currently, examining and describing the visual characteristics of any area within the context of recreational planning studies is of considerable importance worldwide; especially within the context of tourism and recreation, the most important factor regarding the natural environment is its visual and/or landscape quality (Clay and Daniel, 2000; Bulut and Yılmaz, 2007). Turkey’s urban recreation areas are insufficient in terms of both quality and quantity. In Turkey, “picnics” are the most common urban recreation activity (Özgüner, 2011). Across the country, which has experienced a period of a rapid growth, efforts are being made to increase the amount of green area per capita in urban environments. As a result of these efforts, the amount of green area per capita in the city of Konya has reached approximately 45 m2 (for both active and passive green areas). Urban parks and recreation areas account for a considerable portion of the green areas within the city, and contribute considerably to the abovementioned ratio for the city. In this study, an attempt was made to answer the question, “how do various structural and plant design features affect the visual quality of landscaping in urban recreational spaces?” The relationships between plant or structural landscaping elements and urban recreational spaces were assessed using experts’ definitions of landscaping and by considering the preferences of users. Methods To assess the visual quality of the urban recreational areas in this study, a psychophysical method was used (Bernasconi et al., 2009; Brown and Daniel, 1986; Daniel, 1990; Taylor et al., 1987; Wherrett, 2000; Zube et al., 1982). This method provides a compromise between perception-based and expert-based methods. The study was carried out based on the photograph-based scenic beauty evaluation method used by Daniel and Boster (1976). The methods used in the studies of Clay and Daniel (2000), Clay and Smidt (2004), Arriaza et al. (2004), Arriaza et al. (2005), Bernasconi et al. (2009) and Abkar et al. (2011) were also employed. The method in question consists of taking photographs of the area in phases, using a photo-questionnaire design, and applying a statistical analysis.
study. The area sizes, usage, function, and distribution within the city were taken into consideration in the selection of these areas. Birlik Park is 6.4 ha, Karaaslan Park is 18 ha, and Koza˘gac¸ Picnic Area is 18 ha in area. The study areas are mostly used for picnicrelated activities. Birlik Park is located to the north of the city on the Ankara road, Karaaslan Park is located to the southeast of the city on the Karaman road, and the Koza˘gac¸ Picnic Area is located to the southwest of the city on the Antalya ring road (Fig. 1). Photography For photography, a semi-professional digital camera with a 12million-pixel resolution, 18x optical zoom lens and panoramic shooting mode was used. Photographs were taken in June 2011 during weekdays and between 07:00 and 08:00 in the morning so that human factors were not included in the photographs. Photographs were shot as 3-phase panoramas in a manner that reflected all of the characteristics of the areas. Approximately 150 photographs in total were taken in all of the areas. The panoramic photograph field method, used in Rogge et al.’s (2007) study and Sevenant and Antrop’s (2009) study, was also employed. Following this, 12 photographs were selected with the aid of subject experts from the local administration and university; selection was performed such that the main design elements of each area were accurately reflected (Figs. 3–5). Each selected photograph of the recreational fields is defined according to the characteristics in Table 1 by the 12 subject experts (landscape architects, academics, and local government staff). Because the study population was 1 million, 400 people were considered when determining the sample size (˛ = 0.05 for ±0.03, ±0.05 and ±0.10 sampling errors) (Yazıcıo˘glu and Erdo˘gan, 2004). Questionnaire data from a total of 409 users who were considered within the context of the photo-questionnaire were taken into evaluation. Data on demographic characteristics of the users are provided on Fig. 2 (Polat et al., 2011). The demographic characteristics of participants accurately represent the entire population of the city of Konya. According to this data, nearly half of the 409 participants were women. Efforts were made to determine the preferences of woman users. Additionally, younger individuals between the ages of 16 and 30 constituted 58% of individuals who answered the questionnaire. With regard to the level of income, the low-income group represents nearly 70% of the study participants. With regard to their residence location, an equal distribution was identified between those residing outside the city and those residing in the central districts of the city. Photo-questionnaire Four photographs for each recreation area were placed on A4size photograph paper. The photo-questionnaire also contained questions on gender, age, occupation, income level, education, and residence status of the users. Five sets of photo-questionnaire forms were designed accordingly. Inventory forms were also prepared to record data. Questionnaires were applied within the context of one-on-one interviews with users in the park areas. First, the demographic characteristics of the users were ascertained. Second, the users were asked to evaluate the visual quality of each photograph on a Likert scale (scored between 1 and 5) (Kaplan and Kaplan, 1989; Kaplan et al., 2006).
Study area
Statistical analysis
Birlik Park, Karaaslan Park, and the Koza˘gac¸ Picnic Area in the immediate surroundings of Konya were selected as the areas of
As a final step, the collected data were arranged on an Excel spreadsheet and transferred into SPSS 15.0 software.
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Fig. 1. Locations of the Study Areas within Konya.
Fig. 2. Demographic characteristics of individuals who responded to the questionnaire.
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Fig. 3. Study Photographs used for Birlik Park.
The visual quality score averages of each photograph were then calculated. Spearman’s rho correlation analysis was used for structural elements and plant design elements between the average visual quality score of each photograph and the definitions/evaluations provided by the experts on the photographs. Results Visual quality scores of photographs of the recreational areas The average participant scores of the visual quality of each photograph in the photo-questionnaire were calculated. The calculated average scores are provided together with the values for the landscape design characteristics in Table 2. An examination of the table reveals that the visual quality scores of photographs from the Kozaa˘gac¸ Picnic Area and from the Karaaslan Park were higher than the visual quality scores of photographs from Birlik Park. The KA2 photograph from Karaaslan Park and the KO3 photograph from Kozaa˘gac¸ Picnic Area were the most liked and appreciated photographs, and both were given scores of 4.47. The B2 photograph from Birlik Park was the least appreciated photograph, with a score of 3.32.
Relationships between user demographics and the visual quality of urban recreational areas A Chi-square analysis was used to determine the relationship between user demographics and the visual quality scores (Polat et al., 2011). For the Chi-square analysis, relations were identified between users’ age, education, occupation and income level, and the visual quality of urban recreational areas (Table 3).
Relationship between the visual quality of recreational areas and landscape design elements Tables 4 and 5 show the results of the Spearman’s rho correlation analysis, which was performed to determine the relationship between the visual quality of recreational areas and landscape design elements. Based on these results, it was determined that the structural design elements, the water surface area (A4/VQ 0.731**), the width of the pedestrian walkway (A11/VQ 0.656*) and the function of recreational areas (A13/VQ 0.580*) were associated with the visual quality of recreational areas. Stagnant water surfaces and wide enough pedestrian paths increase the visual quality of parks. Among various plant design elements, plant color composition (harmony among colors of leaves, flowers, and stems of the
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Fig. 4. Study Photographs used for Karaaslan Park.
specific plants within the composition) (B6/VQ 0.734**); plant composition (harmony among trees, bushes, flowers, and ground cover plant species with their forms) (B8/VQ 0.629*); and plant species diversity (B10/VQ 0.658*) were all related to the visual quality of the landscape. The compositions of plants and their colors and plant species diversity are among the main elements of the visual quality of landscape areas. Furthermore, it was determined that the type of water element used is associated with water surface area (A3/A4 0.598*) and the amount of urban furniture (A3/A5 0.580*). The visually appreciated landscapes are formed with a convenient amount of urban furniture around the stagnant-surface artificial lakes. Among structural design elements, it was determined that the water surface area is associated with elements related to the amount of urban furniture (A4/A5 0.623*) and the width of the pedestrian path (A4/A11 0.690*). It was determined that the slope is associated with the function of recreational areas (A12/A13 0.585*). Certain correlations were also identified between the plant design elements. Relationships were found between leaf intensity and the amount of shadow (B3/B11 0.914**), between plant composition and plant color composition (B8/B6 0.804**), and between plant composition and plant design function (B8/B9 0.631*). Moreover, negative relationships were identified between the lack of bush-forming plants within the area and the plant color
composition (B5/B6 −0.629*), along with the plant composition (B5/B8 −0.630*) and the plan design function (B5/B9 −0.677*). Discussion Previous studies have suggested that landscape perception is associated with socio-demographic factors (Dramstad et al., 2006; Lothian, 1999; Rogge et al., 2007; Polat et al., 2011). Within the literature, there are numerous studies on the subject of landscape perception and preferences and the aesthetic preferences of individuals. Factors that affect aesthetic preferences are the features of the landscape and the characteristics of the observer (Sevenant and Antrop, 2010). Thus, it was ensured that the demographic characteristics of the participants displayed a distribution that was representative of the general population of the city. However, participation was greater among individuals within the 16to 30-year-old age groups compared with the other age groups. We believe that the greater participation of this age group was because of the relatively young overall population of the country and because schools were on holiday at the time of the study. We believe that the distribution of the participants’ income level was the consequence of the same factors. This study was realized in Konya, one of the strongholds of religious conservatism in Turkey. In this city, one could see women in public life, but the
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Table 1 Landscape design elements. A
Structural Design Characteristics
Categories
A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 B B1 B2 B3 B4 B5 B6 B7 B8 B9
Topographic structure of land Scale level Type of water element Water surface area Amount of urban furniture Type of urban furniture Surface pavement area ratio Type of surface pavement material Encirclement element Height of encirclement element Width of pedestrian walkway Slope status Recreational function Number of buildings Plant Design Characteristics Plant types Plants according to type of leaves Leaf intensity Tree usage according to their forms Bush usage according to their forms Plant color composition Number of plants Plant composition Plant design function
B10 B11
Plant species diversity Shadow amount
Flat Foreground No element No water None None None None None None None Straight Picnic None Categories Trees Coniferous Light Oval Vertical Monochrome Solitary Tree Complementary Symbolizing Few None
Lightly sloping Middle-ground Decorative pool Live 1 pcs Bower Low Concrete Wall Low Narrow Step Walking 1 pcs
Broad-leafed Medium Scenery Horizontal Complementary color Double Attractive Indicative Medium Less than 30%
segregation of women and men in public culture does not ease enough to include women in questionnaires. Therefore, concentrated efforts were focused on determining the preferences of female users. The photographs used to represent real landscapes and the methods used to obtain them are subjects that deserve further scrutiny. During the evaluation of landscape preferences, direct experience can be better represented by performing metaanalysis through photographs (Stamps, 1990). Photographs can be used as visual copies of real landscapes (Schuttleworth, 1980).
Middle sloping Background Artificial lake Still 2–3 Pergola Medium Parquet Fence Medium Normal Ramp Sport 2–3
Very Slopping Artificial Waterfall More than 3 Bank High Natural stone Wall/fence High Wide
Water Channel
Dustbin
Lighting
Sand
Soil
Rest More than 3
Scenery
Social interaction
Bushes
Groundcovers
Climbing plant
flowers
Intensive Pillar None
Conic
Pendulous
Composite color Group Bush Compatible Changing Many 30% and more
Tree-bush Highlighter
Tree-flower Distracter
Bush-flower
If photographs are taken by including the notable characteristics of the area while excluding its other characteristics, these photographs will not be sufficiently representative of the area (Scott and Canter, 1997). However, there is also the criticism that photographs cannot fully reflect and describe the real landscapes. Despite such criticism, photographs are used widely in studies ˜ et al., 2009). Sensibecause they save time and reduce costs (Canas tivity was demonstrated during the photo shoot phase of this study by allowing photographs to represent each park as a whole, without allowing subjective misrepresentation and physical errors.
Table 2 The visual quality scores and design characteristics of the photographs. Photo No
B1
B2
B3
B4
KA1
KA2
KA3
KA4
KO1
KO2
KO3
KO4
VQ Std. D A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11
3.39 0.653 1 2 4 2 4 4 2 2 3 3 1 1 1 2 1 2 2 2 3 1 3 1 1 2 2
3.32 0.675 1 2 1 1 4 6 2 3 1 1 2 1 2 3 1 2 1 3 1 2 1 3 7 2 2
3.48 0.669 1 1 1 2 4 4 3 3 1 1 3 1 1 1 1 2 3 2 3 2 3 1 4 1 3
3.85 0.762 1 2 4 2 4 4 2 3 3 3 2 1 4 1 1 2 2 2 1 2 3 3 4 2 2
4.30 0.811 1 3 3 3 4 2 3 3 3 3 4 1 5 2 1 2 1 1 1 3 3 3 7 1 2
4.47 0.924 1 2 3 3 4 2 3 3 3 3 4 2 6 1 2 1 1 3 2 3 3 5 7 3 1
4.37 0.944 1 2 3 3 4 6 4 3 3 3 4 2 6 2 1 1 1 1 1 3 3 5 6 3 1
3.84 0.824 1 2 2 2 3 6 2 3 1 1 3 1 6 1 1 2 1 2 3 1 1 1 1 2 2
4.06 1.112 1 2 1 1 1 1 1 1 1 1 3 1 4 1 1 1 3 2 3 2 3 1 1 3 3
4.44 0.886 1 3 3 3 4 2 3 4 1 1 3 1 5 1 1 2 3 2 3 2 3 3 2 3 3
4.47 0.917 1 3 3 3 4 2 2 3 1 1 3 1 6 1 1 2 3 2 1 3 3 3 2 3 3
4.24 0.948 2 3 1 1 1 1 4 3 3 3 2 3 6 1 5 2 3 2 2 3 3 4 2 3 3
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579
Fig. 5. Study Photographs used for Koza˘gac¸ Park.
The significant contributions of vegetation and water-related elements to the visual quality of landscapes have been mentioned in numerous previous studies. According to Wong and Domroes (2005), landscapes that maintain a proper balance
between the water element and vegetation have very high appreciation ratios. In parallel with our findings, it was previously stated that the vegetation structures of the landscapes with beautiful scenery include a large diversity of plants (Avıˇzıene˙ et al.,
Table 3 Relationships between user demographics and visual quality of photographs. Photo no.
Demographic characteristics of the participants Gender X2
B1 B2 B3 B4 KA1 KA2 KA3 KA4 KO1 KO2 KO3 KO4
4.502 2.665 15.877 4.121 3.750 6.844 1.542 5.036 5.124 1.562 1.051 1.258
P-value * 0.01 ** 0.05 *** 0. 10.
Age P 0.342 0.615 0.003* 0.390 0.441 0.144 0.819 0.284 0.275 0.816 0.789 0.869
X2 31.679 20.854 23.891 9.932 9.399 10.608 3.517 22.428 23.693 11.124 17.621 4.919
Education X2
P *
0.002 0.053*** 0.021** 0.622 0.669 0.563 0.991 0.033** 0.022** 0.518 0.040** 0.961
30.542 23.718 17.963 9.274 19.249 20.573 10.319 25.263 18.486 13.384 7.110 17.034
Occupation P *
0.002 0.022** 0.117 0.679 0.083*** 0.057*** 0.588 0.014** 0.102 0.342 0.626 0.148
Income (monthly)
Residence
X2
P
X2
P
X2
P
26.977 28.303 37.046 26.327 39.065 36.621 19.300 52.181 30.830 17.149 23.686 30.022
0.519 0.448 0.118 0.555 0.080*** 0.127 0.889 0.004* 0.325 0.946 0.309 0.362
15.872 20.065 19.509 12.299 8.606 11.075 17.827 9.495 15.732 17.711 11.926 20.020
0.197 0.066*** 0.077*** 0.422 0.736 0.522 0.121 0.660 0.204 0.125 0.218 0.067***
10.798 12.321 29.759 10.483 11.532 15.909 12.319 11.105 8.369 12.696 5.965 8.756
0.546 0.420 0.003* 0.574 0.484 0.195 0.420 0.520 0.756 0.392 0.743 0.724
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Table 4 Relationships between the visual quality of recreational areas and the structural landscape design elements. Spearman’s rho
Correlation coefficient sig. (2-tailed) VQ
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A1
0.044 0.893
A2
0.573 0.051
0.398 0.200
A3
0.267 0.401
−0.370 0.236
0.158 .623
A4
0.731** 0.007
−0.419 0.175
0.314 0.320
0.598* 0.040
A5
0.115 0.721
−0.575 0.051
−0.092 0.776
0.580* 0.048
0.623* 0.031
A6
−0.500 0.098
−0.452 0.140
−0.549 0.065
0.146 0.652
0.027 0.934
0.405 0.192
A7
0.395 0.204
0.462 0.130
0.234 0.464
−0.035 0.913
0.385 0.217
0.154 0.634
−0.069 0.831
A8
0.395 0.203
0.057 0.860
0.382 0.220
0.063 0.845
0.484 0.111
0.363 0.247
0.119 0.713
0.540 0.070
A9
0.169 0.599
0.302 0.341
0.110 0.733
0.537 0.072
0.206 0.521
0.159 0.622
−0.075 0.817
0.460 0.132
−0.127 0.695
A10
0.169 0.599
0.302 0.341
0.110 0.733
0.537 0.072
0.206 0.521
0.159 0.622
−0.075 0.817
0.460 0.132
−0.127 0.695
−0.322 0.308
0.076 0.815
0.000 1.000
0.690* 0.013
0.165 0.609
−0.084 0.796
0.398 0.200
0.261 0.413
0.051 0.875
0.051 0.875
A11
0.656* 0.020
A12
0.413 0.182
0.632* 0.027
0.121 0.709
−0.112 0.729
0.069 0.832
−0.224 0.484
−0.202 0.528
0.717** 0.009
0.109 0.737
0.572 0.052
0.572 .052
0.242 0.448
A13
0.580* 0.048
0.405 0.192
0.503 0.096
−0.038 0.906
0.320 0.310
−0.367 0.240
−0.102 0.751
0.492 0.105
0.397 0.202
0.199 0.536
.199 .536
0.455 0.138
−0.210 0.513
−0.055 0.865
0.125 0.700
−0.007 0.983
0.398 0.200
0.485 0.110
0.053 0.869
−0.171 0.595
0.261 0.412
.261 0.412
−0.062 0.848
** *
−0.370 0.236
A13
.
A11
A14
A12
0.585* 0.046 −0.064 0.844
−0.203 0.526
Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed).
2007; Uzun and Müderrisoglu, 2011). Strong relationships have been identified between the heterogeneity and diversity of the landscape and the landscape preferences of individuals (Hunziker, 1995; Zube, 1987). Bernasconi et al. (2009) stated in a study on automated transportation systems that turf, bush, and especially tree vegetation have a positive effect on preferences. The results of our study are entirely in agreement with these findings. In numerous previous studies, positive correlations were identified between the water element and the preference scores (Herzog and Barnes, 1999; Purcell et al., 1994). Acar et al. (2006) identified in their study a positive relation between water mobility and the visual quality of the landscape. This study suggested a positive relationship between water surface area and visual quality; this finding was also confirmed by the abovementioned results of our study. In Turkish culture, gardens are of considerable significance both as a water factor and a landscape type (Aksoy, 2011). The most important elements of Turkish gardens are water used for cooling, trees for providing shade, and music for resting and entertainment. Moreover, adding movement to water through the use of sprinklers is a common feature in Turkish gardens. The use of water is also essential in Egyptian, Persian, Japanese and baroque gardens.
Preferences regarding the use of water and vegetation diversity have remained largely unchanged from old garden landscapes to modern green areas. Human structures and artificial elements negatively affect the visual quality of landscapes (Acar et al., 2006; Arriaza et al., 2004). From this point of view, elements such as surface pavement materials, encirclement elements and the number of structures were expected to have a negative effect on the visual quality of the landscape. However, our study did not produce positive or negative results associated with these elements. The topographic structure of the land also affects the visual quality of the landscape. Aminzadeh and Ghorashi (2007) stated in their studies on forest parks that areas with flat topographies generally have higher visual qualities. However, such an effect could not be identified in our study. It is believed that Konya’s extremely flattened topography and the familiarity of the study participants with this type of topography contributed to such a result. The findings of our study are specific to the study region. Further studies conducted with different physical, cultural, and social environments are necessary to determine whether our study results are generally applicable.
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Table 5 Relationships between visual quality of recreational areas and the plant design elements. Spearman’s rho
Correlation Coefficient Sig. (2-tailed) VQ
B1
B2
B3
B4
B1
0.331 0.293
B2
−0.391 0.209
−0.214 0.504
B3
0.106 0.743
0.041 0.900
0.211 0.511
B4
−0.188 0.557
0.354 0.260
0.000 1.000
0.000 1.000
B5
−0.252 0.430
0.000 1.000
0.000 1.000
0.400 0.198
0.158 0.624
B5
B6
B7
B8
B6
0.734** 0.007
0.488 0.108
−0.331 0.293
−0.043 0.895
−0.226 0.480
−0.629* 0.029
B7
0.519 0.084
0.199 0.535
−0.258 0.418
0.490 0.106
−0.387 0.214
0.000 1.000
B8
0.629* 0.029
0.572 0.052
−0.354 0.259
−0.294 0.354
0.000 1.000
−0.630* 0.028
0.804** 0.002
0.240 0.452
B9
0.186 0.562
0.165 0.608
−0.143 0.658
−0.528 0.078
0.086 0.791
−0.677* 0.016
0.572 0.052
0.000 1.000
0.631* 0.028
B10
0.658* 0.020
0.423 0.171
−0.548 0.065
0.289 0.363
0.137 0.671
0.000 1.000
0.404 0.193
0.283 0.373
0.509 0.091
−0.055 0.865
0.392 0.208
0.914** 0.000
0.000 1.000
0.386 0.216
−0.098 0.762
0.210 0.512
−0.420 0.174
B11 ** *
−0.009 0.977
B9
B10
0.455 0.137
−0.207 .0518 −0.499 0.099
0.115 0.721
Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed).
Conclusion We can divide and categorize landscape design in urban recreation areas as structural or vegetation-related. These characteristics are specifically determined by landscape architecture. Landscape architecture provides designs in which living and non-living elements of the landscape are used in combination. Each design fulfills certain criteria regarding these two areas. Studies on the use of plant materials and the plant-related designs that are employed are relatively limited in the literature. Further study is necessary to improve the area’s visual quality value and to provide functional solutions in outdoor areas. Understanding and evaluating the visual quality of landscapes is a complicated process. It is understood that visual quality is based on both individual and environmental variables. In this respect, the visual quality of a landscape can be likened to an unresolved multiple-variable equation. In our study, we have focused on the visual quality of urban recreational landscape areas. Certain design elements of the landscape were considered, and evaluations were performed accordingly. The structural and plant design elements that affect the visual quality were identified. In parallel with findings from previous studies, our results have shown that the water elements and plant materials have a strong effect on visual quality. It was observed that the surface area of the water element, the width of the pedestrian walkway, the function of the recreational area, the plant composition, the plant color composition, and the plant species diversity all positively affected the visual quality of the landscape area. It was also demonstrated that the lack of bush-type plants within the plant composition had a negative effect on the visual quality.
Many studies have previously been conducted on the visual quality of landscaping, and various results have been obtained. The positive effect of water and vegetation on natural and designed landscaping is now well recognized. The results of our study are also in agreement with the findings of previous studies. However, the identification of tangible criteria for structural and plant landscaping, such as the water surface area, the pedestrian walkway width, the number of reinforcement elements, the plant composition, and the plant color composition, further underscores the significance of this study. In this study, the relationships between elements of structural and plant landscapes and the visual quality of areas are examined to find data highlighting urban landscape design. However, it is found that structural and plant landscape elements, such as surface pavements, encirclement elements, buildings, plants according to type of leaves and number of plants, have no specific effect on the visual quality of the landscape. It will be beneficial to evaluate these elements in forthcoming studies. The results of our study can potentially be used for the planning, design and management of urban recreational areas. These findings should especially be taken into consideration in landscape and rehabilitation projects that focus on increasing the visual quality of landscape areas. When designing urban recreation areas, the inclusion of water surfaces formed by artificial lakes should be considered. The characteristics and the general scenic beauty of the area should be considered before designs with different types of activity are proposed for the recreational area. Additionally, further emphasis and attention should be accorded to the plant designs, the plant color compositions, and the plant diversity. Further studies on landscape management, especially concerning planting and maintenance projects,
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