Document Type : Original Research Paper
Authors
Graduate in Faculty of Environment, University of Tehran, Iran
Abstract
Keywords
INTRODUCTION
Throughout the history, either people have shaped their own living environments or environments have formed their communities. In this cycle, social lives and their contextual spaces may have undertaken certain changes. After 1950s and particularly after Industrial Revolution, unplanned and fast urbanism as well as continuous population growth caused many changes and all of these factors influenced the environment where people lived (Yilmaz & Sagsöz, 2011).
Normally establishing buildings and urban space items are referred to streets and squares as well as other public places, owned by municipality. Living in marginal buildings has disturbed the harmony, formed by city-building factors. These various complexities of urban spaces and different degrees of their users have made cities sensitive to and negatively influenced by different kinds of pollutions. Visual pollution damages human eyesight. Under the influence of human lifestyle and economic status, spatial directions and psychological aspects have suffered a lot (Purice, 2013). One of the most significant visual pollution indices on cities is shadows. Shadows or uniformed black paintings are observable shadows of cities’ physical structures and historical masses. When we talk about environment, the first thing that strikes our mind is water, air, and noise pollution. But one of the pollutions which has recently attracted attention, but has been ignored compared to other kinds of pollution, is visual pollution (Yilmaz & Sagsöz, 2011). Since visual comfort is one of important and basic components of safe man-made environments (human beings consider cities as their own homes), home should have desirable qualities to satisfy security- and peace-related requirements of its residents. Furthermore, a city should be a warm and intimate place in order to provide good conditions of life. Also, visual comfort is one of the factors that should receive attention in order to create suitable urban landscape. Visual comfort components include color, brightness, and environmental quality. Undesirable application of colors and lack of proper lighting have led to some kinds of pollution in urban environments, related to color, brightness, and façade (Salehi, 2006).
Based on European Planning Chart in 2012, nowadays professional planning is scarcely coordinated with urban spaces (Voronych, 2013). Visual pollution may be considered as the overall messy units, observed usually in natural or man-made environments, indirectly having bad effects on human minds (Yilmaz & Sagsöz, 2011). Reasons behind visual pollution include wrong decisions, lack of legal requirements, lack of control, and incompatible applications with performance, not to mention lack of education and culture (Yilmaz & Sagsöz, 2011). Visual pollution may be reflected throughout the city including local spaces and buildings. Environments in which compact buildings without green spaces or buildings, not compatible with environment, create such scenes which would result in visual pollution. Additionally, mobile waste baskets, traffic signs, direction signs, large advertisement signs at cities' exit and entrance roads, electrical power cables and poles, building transformers, telephone cables, installed air-conditioners on the external building walls, and satellite antennas can also result in visual pollution.
People always interact with their environments. As a matter of fact, there is some kind of balance between human being and his environment; however, the intensity of such balance is sometimes at such high levels, causing distraction, reluctance and adaptability problems, behavior disorders, pessimism, and increased psychological illnesses in human beings (Bodur & Kucur, 1994). Therefore based on previous investigations, there is statistical correlation between frequency of deviations as well as behavioral disorders, on one hand, and different types of visual and environmental pollutions, on the other. The study hypothesizes that behavioral pollution tends to spatial and time-based adherence to environmental pollutions, including visual pollution. Currently due to scarce urban planners’ attention, lack of comprehensive programs for urban spaces, and unhealthy city growth as a result of increased population growth, the issue of visual beauty is receiving less attention than ever, which has caused visual disorders in cities. Given the political, cultural, social, and geographical features; social status of its residents; forgotten principles of reconstruction, unreasonable interventions in textures of the city; and indifference on the part of relevant authorities, Tehran has undergone decreased environment quality in recent decades.
With regards to visual comfort and urban landscape as well as determination of visual pollutions, there have been widespread researches, such as the work of Kalen (2005) in a book titled “Excerption of Urban Landscape”, also translated into Persian. It deals with urban landscape as well as the art of integrating visual and structural elements into constituting components of the city which shape urban environments. Furthermore, Salehi (2006) in an article titled “Components of Visual Comfort and its Role in Environment Improvement” investigated the visual component in evaluation of environment quality. Voronych (2013) in “Visual Pollution in Urban Space of El Vivo City" investigated the relation between increased motorways and visual pollutions. Chmielewski et al. (2016) in “Measuring Visual Pollution by Outdoor Advertisements in an Urban Street, Using Intervisibility Analysis and Public Surveys” focused on measuring visual pollution by OAs (banners and billboards).
The present paper has dealt with structural improvement of Vanak and Enghelab squares in terms of environmental qualities along with improvement of local religious identities through visual comfort components, using the techniques of QSPM and SWOT for its evaluation.
Visual pollution in urban area
City is the complete embodiment of communities on earth, which is realized through lots of readable signs for all kinds of residents. In various degrees, these signs have implications which realize the relations between human being and his realm. Based on an established framework of collective behavior of individuals in an environment, they have a symbolic role in history, information, guidance, rules, or a combination of two or more of these. Primary understanding of human beings from spaces has been naturally visual. People infer their environment and in fact their home as a collages of pictures. The quality of visual environment has been considered under subcategory of various types of consciousness. The pictures that we see are blocked with visual garbage more or less. Such a problem has been observed in majority of contemporary big cities (Voronych, 2013). Visual pollution is a compounded effect of clutter, disorder, and excess of various objects and graphics in the landscape, such as outdoor advertisements (OAs), street furniture, lighting features (Falchi et al., 2011; Chalkias et al., 2006), vegetation characteristics (Ulrich, 1986; Lamp & Purcell, 1990; Ribeiro & Barao, 2006), and other objects. In special cases of visual pollution, the overall design of the pollutant may be classified as the following:
Pollutions are result of unfair and excessive consumption, making it one of the important issues, regarding spatial planning (Voronych, 2013).
Fig. 1. Visual pollution in urban area
MATERIAL AND METHOD
This research is a descriptive-explanatory one, using methods for collecting data which included document and library-based studies, viewpoints, opinions, and definitions. Also, using field-based approaches (questionnaire, observation, interview, and field-based surveys), the required data were collected and processed in SPSS. Then, according to a statistical test of Khi^ 2, the data were analyzed and the assumptions, examined. The sample volume in this study was about 40 questionnaires, distributed randomly in two study places. Finally, using AHP technique and its related software (Expert Choice), the threats, opportunities, weaknesses, and strengths of Vanak and Enghelab squares were weighted and ultimately, based on SWOT and QSPM approaches, they were analyzed.
The squares under investigation
1. Enghelab square
Enghelab square is one of Tehran Squares, located at the intersection of Enghelab, Kargar, and Azadi streets, being one of the main squares of Tehran. Due to its central position, lots of people pass this square daily. Most of Tehran bookstores and publication centers are located in Enghelab square, along with Bahman Cinema in the northeastern, Shahr-e-Tamasha and Pars Cinema in the southwestern, and food market in the southern part of this square.
2. Vanak square
Vanak is a neighborhood located at the north west of Tehran, in District 3 of the city's municipal classifications. Deh Vanak is one of the oldest and most verdant neighborhoods of northern Tehran. Currently this region is south of Niayesh and north of Chamran Highway. It has retained its traditional mood, meaning that all of houses there are in form of detached houses (Fig. 2).
Fig. 2. Location of the study area
Analytic Hierarchy Process (AHP)
Analytic Hierarchy Process is considered a versatile and powerful decision-making technique for complex situations, which has contradictory and various measures (Saaty, 1994). It was invented by Iraqi scholar Tommy al Saaty in 1970s (Ghodsipour, 2008). In decision-making process, this pattern is based on pair comparisons. The value-based foundations of the analyzer is mixed with available information about the alternatives with a set of measurement priorities created for the evaluation process.
In the process of measuring capabilities, based on AHP technique, once the necessary criteria along with their importance coefficients are determined, the process of evaluation is performed, according to each criterion's competence. The process is performed on three stages of hierarchy formation, which is the most important part of AHP technique where the effective criteria in evaluation process are determined. The importance of criteria coefficients is implemented through experts' preference judgments, pair comparison method, and examination of the judgments' compatibility, based on the compatibility rate, which should be less than 0.1 in order that a judgment can be considered acceptable (Dey & Ramcharan, 2008).
In the present study, at first the criteria effective in visual pollution management were identified. In the next stage, the weight of each criterion was calculated. There are many approaches to determine importance coefficients of the criteria, the most common of which is pair comparison, provided by Saaty, and considered a suitable approach to weight criteria in AHP system, in which the criteria are measured and weighted via a software program, called Expert Choice.
The current study used experts' ideas in Planning and Environmental Management to analyze the criteria. Tables 1, 2, 3, and 4 show the weights of the criteria in visual pollution assessment.
SWOT and QSPM methods
SWOT is the abbreviation of four analytical factors, namely Strengths, Weaknesses, Opportunities, and Threats. As such the analysis of strengths and weaknesses is performed in internal environment, while that of opportunities and threats are performed in external one (Kajanus et al., 2012). Internal factors have been evaluated, using IFE matrix, whereas the evaluation of external factors employs EFE matrix. At this stage, the final score, obtained from each of these matrices, reveals the status of organization, relative to internal and external factors of visual pollution. In the next stage, using a list of strengths, weaknesses, opportunities, and threats of the major visual pollutions of the squares, SWOT system was created. Afterwards internal strengths were compared with external opportunities in order to create SO, and internal weaknesses were compared with available opportunities outside the organization in order to create ST Strategy. By comparing internal weaknesses with external threats, WT strategy was determined. Finally, using evaluating matrix of internal and external factors as well as the results of both SWOT and QSPM matrixes, the selected attractiveness and priority strategies were determined.
Formation of internal and external factors evaluation (IFE) matrix
Once the internal factors were investigated, the most important factors were listed. The number of these factors should be within the range of (10, 20). These factors should include the most important strengths and weaknesses of the organization. Formation of this matrix involves the following steps (Karbasi et al., 2008):
1. At first, the strengths and weaknesses are written.
2. To each of these factors a coefficient is assigned (ranging from 0 as non-important to 1 as very important)
3. Each factor is given a number from 1 to 4. Scores 1, 2, 3, and 4 represent basic weakness, little weakness, strength, and very powerful strength for the aforementioned factors, respectively.
4. To determine the final score of each of the factor, its coefficient is multiplied by its score.
5. The sum of final scores of all factor is calculated and the final score of the organization is determined.
6. In the matrix of internal factors evaluation, if the final score is above 2.5, the strengths will surpass the weaknesses and if the final score is below 2.5, the strengths will be fewer than the weaknesses.
RESULTS AND DISCUSSION
Tables 1 and 2 list the most important external and internal factors. Table 1 gives internal factors of Tehran's visual pollution management in Vanak Square, compared to those of Enghelab Square, presenting them in a matrix of internal factors' evaluation (Tables 1 and 3). The strengths and weaknesses are graded as follows: 4= strong strength, 3= weak strength; 2= low weakness, and 1= severe weakness. According to the table, the highest strength is 0.0215 and the lowest one, 0.057. As for the weaknesses, the highest weight is 0.154 and the lowest one, 0.025. Afterwards, by multiplying the weight in the amount of degree, the weight-based score is obtained. By summing up the weight scores, the total score, related to the internal factors, is obtained, thus the score average is 2.5 and its maximum amount, 4. Now, if this number is above 2.5, from the perspective of internal factors it means that visual pollution is in a desirable condition. According to the table, the sum of these scores is 2.459. QSPM uses the weights, attributed to these factors. Then using external factor evaluation in matrices 2 and 4, the most important opportunities and threats, related to Vanak and Enghelab Squares from the perspective of visual pollution have been presented. The opportunities and threats are graded as follows: great opportunity is equal to 1 and 2, while weak opportunity is 3. Also, severe threat is 1 and weak threat, 4. These factors have been presented quantitatively to avoid any misunderstanding and perceived judgments. Finally, the related total weight is obtained. If it is above 2.5, it means the organization has used the external opportunities properly and has avoided the potential threats. The highest weight which may be attributed to the overall set of factors is 4. As it can be seen, the highest opportunities and threats are 0.248 and the lowest ones, 0.017. The sum of this amount is 3.402. Afterwards, QSPM uses the matrix of internal and external factors evaluation, and, based on their importance in improving organization success, a weight is assigned to each factor. The same process has been performed for Enghelab Square.
Table 1. Internal factor evaluation matrix for Vanak square
Weighted score |
Score |
Weight |
Strengths |
|
0.86 |
4 |
0.215 |
Corridor to green space |
S1 |
0.228 |
4 |
0.076 |
Short Buildings |
S2 |
0.228 |
4 |
0.057 |
wall paintings on buildings |
S3 |
0.296 |
2 |
0.148 |
existence of green space |
S4 |
0.201 |
3 |
0.067 |
Low mass of cars and human beings |
S5 |
0.156 |
3 |
0.052 |
Low amount of human population |
S6 |
0.246 |
2 |
0.123 |
Decreased advertising Tableaus |
S7 |
Weakness |
||||
0.308 |
2 |
0.154 |
Lack of prominent elements |
W1 |
0.025 |
1 |
0.025 |
Weak access |
W2 |
0.027 |
1 |
0.027 |
Excessive use of decorative devices |
W3 |
0.112 |
2 |
0.056 |
Lack of pointwise green space |
W4 |
2.687 |
|
1 |
Total internal factors |
|
Table 2. External factor evaluation matrix for Vanak square
Weighted score |
Score |
weight |
Opportunities |
|
0.258 |
3 |
0.086 |
Increased Visual Comfort |
O1 |
0.912 |
4 |
0.228 |
Lower view blockage and installment of air-conditioner systems |
O2 |
0.288 |
3 |
0.096 |
Increased spatial feelings |
3O |
0.074 |
2 |
0.037 |
Higher landscape beauty |
O4 |
0.294 |
3 |
0.098 |
Decreased human and car encounters |
O5 |
1.096 |
4 |
0.247 |
Lower air temperature and pollution |
O6 |
0.294 |
3 |
0.098 |
Observation of space |
O7 |
Threats |
||||
0.076 |
2 |
0.038 |
Confusion |
T1 |
0.017 |
1 |
0.017 |
Deformation of Space |
T2 |
0.017 |
1 |
0.017 |
Disturbing traffic order |
T3 |
0.076 |
2 |
0.038 |
Less flexibility |
T4 |
3.402 |
|
1 |
Total external factors |
T5 |
Table 3. Internal factor evaluation matrix for Enghelab square
Weighted score |
Score |
Weight |
Strengths |
|
0.400 |
2 |
0.200 |
The existence of prominent elements |
S1 |
0.400 |
2 |
0.200 |
Presence of Subway station |
S2 |
0.228 |
2 |
0.114 |
Presence of retailers |
S3 |
0.336 |
3 |
0.112 |
Presence of causes for collective memory like Bahman Cinema |
S4 |
Weakness |
||||
0.063 |
1 |
0.063 |
No spatial feeling |
W1 |
0.098 |
2 |
0.049 |
Lack of green spaces |
W2 |
0.088 |
2 |
0.044 |
Lack of open spaces |
W3 |
0.078 |
2 |
0.039 |
Existence of billboards |
W4 |
0.076 |
2 |
0.038 |
Human and car traffic |
W5 |
0.033 |
1 |
0.033 |
Lack of viewing corridors to open spaces |
W6 |
0.029 |
1 |
0.029 |
Lack of appropriate urban furniture |
W7 |
0.025 |
1 |
0.025 |
Lack of brightness |
W8 |
0.019 |
1 |
0.019 |
View blockage |
W9 |
0.018 |
1 |
0.018 |
Presence of high-rise buildings |
W10 |
0.032 |
2 |
0.016 |
Existence of false Jobs |
W11 |
1.923 |
|
1 |
Total internal factors |
|
Table 4. External factor evaluation matrix for Enghelab square
Weighted score |
Score |
Weight |
Opportunities |
|
0.494 |
2 |
0.247 |
Creating ability in the presence of people |
O1 |
0.494 |
2 |
0.247 |
Use of public transportation |
O2 |
0.393 |
3 |
0.131 |
Increased control of observer over the space |
O3 |
0.144 |
2 |
0.072 |
Increased place feeling |
O4 |
Threats |
||||
0.066 |
1 |
0.066 |
Lack of observer control over the space |
T1 |
0.086 |
2 |
0.043 |
Car and human being encounters |
T2 |
0.068 |
2 |
0.034 |
Lack of appropriate air conditioning and the stability of polluted air |
T3 |
0.118 |
2 |
0.059 |
Lack of landscape beauty |
T4 |
0.090 |
2 |
0.045 |
Confusion |
T5 |
0.056 |
2 |
0.028 |
View blockage and disturbed visual comfort |
T6 |
0.031 |
1 |
0.031 |
Lack of financial security |
T7 |
2.040 |
|
1 |
|
|
Weighted score |
Score |
Weight |
Strengths |
|
0.86 |
4 |
0.215 |
Road to green space |
S1 |
0.228 |
4 |
0.076 |
Low-rise Buildings |
S2 |
0.228 |
4 |
0.057 |
Wall paintings on buildings |
S3 |
0.296 |
2 |
0.148 |
Presence of green spaces |
S4 |
0.201 |
3 |
0.067 |
Lower car and human density |
S5 |
0.156 |
3 |
0.052 |
Low amount of human population |
S6 |
0.246 |
2 |
0.123 |
Fewer advertising signs |
S7 |
Weakness |
||||
0.308 |
2 |
0.154 |
Lack of prominent elements |
W1 |
0.025 |
1 |
0.025 |
Weak access |
W2 |
0.027 |
1 |
0.027 |
Excessive use of decorative devices |
W3 |
0.112 |
2 |
0.056 |
Lack of point-wise green spaces |
W4 |
2.687 |
|
1 |
Total internal factors |
|
Table 5. SWOT analysis matrix for Vanak square
Threats |
Opportunities |
Strategies |
TS strategies |
SO strategies |
|
1. Creating rhythm in space by using low-rise buildings () |
1. Providing the opportunity of people gathering with emphasis on significant elements (S1O1) |
Strengths |
2. Regulating traffic through low-density population ( |
2. Increasing the use of public transportation with emphasis on the subway station (S2O2) |
|
3. Increasing the readability of the environment by means of wall paintings () |
3. Increasing spatial feelings with emphasis on collective memory elements (S4O3) |
|
4. increasing the flexibility by means of making green spaces ( 5. Eliminating the confusion through use of low-density advertising signs () |
4. Increasing space liveliness with the emphasis on retailers (S3O4) |
|
WT Strategies |
WO strategies |
Weaknesses |
1. Increasing observational control over space by improving brightness and constructing low-rise buildings (T1W8) |
1. Improving landscape beauty in order to decrease low-density green space ( |
|
2. Granting more access and decreasing the accidents through improvement of human and car-based traffic (W5T2) |
2. Granting more access by lowering encounters with cars and human beings ( |
|
3. Establishing appropriate air conditioning through improvement of the green spaces (W2T3) |
3. Decreasing view blockage by taking decorative objects away ( |
|
4. Increasing landscape beauty by improving the routes to open space (W6T4) |
4. Increasing visual comfort and space view via increased significant elements ( ) |
Table 6. SWOT analysis matrix for Enghelab square
TS strategies |
SO strategies |
|
1. Creating rhythm in space by using short buildings () |
1. Providing opportunity of people gathering with emphasis on significant elements (S1O1) |
Strengths |
2. Regulating traffic using low-density population ( |
2. Increased the use of public transportation with emphasis on subway station (S2O2) |
|
3. Increased readability of environment using wall paintings () |
3. Increased place feeling with emphasis on collective memory elements (S4O3) |
|
4. increased flexibility through creating green space ( 5. Eliminating Confusion confusion through use of low-density advertising tableaus () |
4. Increased liveliness of space with the emphasis on retailers (S3O4) |
|
WT Strategies |
WO strategies |
Weaknesses |
1. Increasing observational control over space by improving brightness and creating short buildings (T1W8) |
1. Increased landscape beauty to decrease low-density green space ( |
|
2. Increased accesses and decreased accidents by improving human and car-based traffic (W5T2) |
2. Reinforcement of accesses through decreasing car and human beings encounters ( |
|
3. Creating an appropriate air conditioning by improving green space (W2T3) |
3. Decreased view blockage by decreasing decorative objects ( |
|
4. Increased landscape beauty through improving corridor to open space (W6T4) |
4. Increased visual comfort and space view through increased significant elements ( ) |
Forming SWOT matrix
SWOTMatrix has many applications among managers and strategic planners (Abya et al., 2015;Abbasi et al., 2013, using vital internal and external factors to create strategies that need paying attention to. Generally, this matrix links internal and external factors and is used as a basis for potential strategies (Tables 5 and 6). This analytic instrument develops strategies to be used later in QSPM system. Another application of SWOT is to compare key external opportunities and threats with internal strengths and weaknesses.
Results from the matrix of internal and external factors and these models lead to strategies, demonstrated in the following diagrams (Diagrams 1 and 2).
Diagram 1. SWOT analysis diagram for Vanak square's visual pollution
4 Improvement of environment conditions by using capabilities Conservative position |
Use of capabilities to use opportunities Invasive position |
2.5 Less weaknesses and avoidance of using opportunities Defensive position |
Improvement of internal systems by means of external opportunities Competitive position |
1 2 |
2.5 3 4 |
Diagram 2. SWOT Analytic Diagram in Enghelab square's visual pollution
Improvement of environmental conditions by using capabilities Conservative position |
Utilization of capabilities for the use of opportunities
Invasive position |
2.5 Decreased weaknesses Defensive position |
Improvement of internal systems by means of external opportunities Competitive position |
1 2 |
3 |
QSPM
This system is an analytic technique, defining superior strategies (David, F.A, 2009 & 1985). Respectively, the columns on the left-hand side are the names of internal and external factors and their weights, which are exactly inferred from the matrix of internal and external factors of the organization. In the next columns, the mentioned strategies in SWOT matrix, namely SO1, SO2, WO1, WO2, ST1, ST2, WT1, and WT2, are placed in 8 columns. Each column includes AS (Attractiveness Score) and TAS (Total Attractiveness Score). The latter is obtained by multiplying the weight in Attractiveness Score, which can take the values of 1, 2, 3, and 4. Value 1 represents the lowest and value 4, the highest attractiveness. However, some strategic factors may not have any appeal for strategies, in which case, we should not consider any attractiveness score for that factor. It should be emphasized that ASs should not be based on guess, rather they should be precise, reasonable, and justifiable (Ghosiyan et al., 2015). Finally, TASs, related to each strategy, should be collected. Each strategy with the highest score has the highest priority for the organization (Tables 7, 8). This matter is important in the process of strategy selection.
Table 7. QSPM matrix for Vanak Square
WT2 |
WT1 |
ST2 |
ST1 |
WO2 |
WO1 |
SO2 |
SO1 |
Weights |
Strategic factors |
||||||||
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
||
Strengths |
|||||||||||||||||
|
|
|
|
|
|
|
|
|
|
|
0.645 |
3 |
0.86 |
4 |
0.215 |
|
Presence of observational corridor to open spaces |
|
|
|
|
|
0.304 |
4 |
|
|
|
|
0.304 |
4 |
0.076 |
1 |
0.07 |
|
Low-rise building
|
|
0.296 |
2 |
|
|
|
|
|
|
0.592 |
|
|
|
|
|
0.057 |
|
Existence of wall paintings on building |
|
|
0.296 |
2 |
|
|
0.296 |
2 |
|
|
|
4 |
0.444 |
3 |
0.296 |
2 |
0.148 |
Existence of green spaces |
0.201 |
3 |
0.067 |
1 |
0.268 |
4 |
|
|
0.268 |
4 |
0.067 |
1 |
0.134 |
2 |
|
|
0.067 |
Low density of cars and human |
0.156 |
3 |
0.052 |
1 |
0.208 |
4 |
0.104 |
2 |
0.208 |
4 |
0.052 |
1 |
0.104 |
2 |
0.156 |
3 |
0.052 |
Low population |
0.123 |
1 |
0.246 |
2 |
|
|
0.246 |
2 |
0.246 |
2 |
|
|
|
|
0.246 |
2 |
0.123 |
Fewer advertising signs |
Weaknesses |
|||||||||||||||||
|
|
|
4 |
|
|
0.462 |
3 |
0.154 |
1 |
|
|
|
|
0.154 |
1 |
0.154 |
Lack of significant elements |
0.1 |
4
|
|
|
0.075 |
3 |
0.025 |
1 |
0.075 |
3 |
|
|
|
|
|
|
0.025 |
Weak access |
|
|
0.027 |
1 |
|
|
|
|
0.027 |
1 |
0.081 |
3 |
|
|
0.054 |
2 |
0.027 |
Excessive use of decorative objects |
0.112 |
2 |
0.112 |
2 |
0.112 |
2 |
0.112 |
2 |
0.056 |
1 |
0.168 |
3 |
0.112 |
2 |
0.168 |
3 |
0.056 |
Lack of green spaces |
Opportunities |
|||||||||||||||||
0.258 |
3 |
0.258 |
3 |
0.258 |
3 |
0.258 |
3 |
0.344 |
4 |
0.258 |
3 |
0.258 |
3 |
0.344 |
4 |
0.086 |
Higher visual comfort |
Table 8. QSPM matrix for Enghelab Square
WT2 |
WT1 |
ST2 |
ST1 |
WO2 |
WO1 |
SO2 |
SO1 |
Weights |
Strategic factors |
||||||||
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
TAS |
AS |
||
|
|
|
|
0.228 |
1 |
0.456 |
2 |
0.456 |
2 |
0.228 |
1 |
0.912 |
4 |
0.648 |
3 |
0.228 |
Decreased view blockage and establishment of air conditioning systems |
0.288 |
3 |
0.288 |
3 |
0.096 |
1 |
0.096 |
1 |
0.096 |
1 |
0.192 |
2 |
0.192 |
2 |
|
|
0.096 |
Increased spatial feeling |
0.037 |
1 |
0.037 |
1 |
0.111 |
3 |
0.074 |
2 |
0.111 |
3 |
0.148 |
4 |
0.074 |
2 |
0.111 |
3 |
0.037 |
Increased landscape beauty |
0.294 |
3 |
|
|
0.196 |
2 |
|
|
0.392 |
4 |
0.098 |
1 |
0.196 |
2 |
0.196 |
2 |
0.098 |
Decreased car and human encounters |
0.498 |
2
|
|
|
0.741 |
3 |
0.741 |
3 |
0.741 |
3 |
0.498 |
2 |
0.498 |
2 |
0.247 |
1 |
0.247 |
Deteriorated weather temperature and air pollution |
|
|
0.294 |
3 |
0.098 |
1 |
0.294 |
3 |
0.195 |
2 |
0.195 |
2 |
0.294 |
3 |
0.294 |
3 |
0.098 |
Space observation |
Threats |
|||||||||||||||||
|
|
|
4 |
0.076 |
2 |
0.076 |
2 |
0.076 |
2 |
|
2 |
0.076 |
2 |
|
|
0.038 |
Confusion and destruction of environment readability |
0.017 |
1 |
|
3 |
|
|
0.017 |
1 |
0.017 |
1 |
0.017 |
1 |
|
|
0.034 |
2 |
0.017 |
Destruction of space form |
0.051 |
3 |
|
|
0.051 |
3 |
|
|
0.034 |
2 |
0.017 |
1 |
|
|
0.034 |
2 |
0.017 |
traffic disorder |
0.038 |
1 |
0.114 |
3 |
0.076 |
2 |
0.038 |
1 |
0.038 |
1 |
0.038
|
1 |
0.038 |
1 |
0.076 |
2 |
0.038 |
Decreased flexibility |
2.17 |
|
2.08 |
|
2.59 |
|
3.59 |
|
3.53 |
|
2.64 |
|
4.281 |
|
4.03 |
|
|
Total |
CONCLUSION
The aim of this study was to investigate SWOT analysis in the process of managing visual pollutions, related to Vanak and Enghelab Squares in Tehran, Iran. Accordingly, the location of these squares was analyzed and SWOT factors and matrix were investigated. QSPM makes the decision-makers think more about the weights of SWOT factors and analyze the situation more precisely and deeply than what SWOT performs on its own. Since QSPM is suitable almost for every situation, applicable for SWOT, to some extent weaknesses of SWOT would be alleviated by QSPM. Based on performed analyses and the evaluation matrix of internal and external factors of Vanak square, the obtained score for internal factors was 2.535 and the score obtained for external factors, 3.402. Therefore, based on principles of strategic management, the strategic position of Vanak square was in invasive area. Based on examination of the scores of internal factors, it was found that the research score was above 2.5. Accordingly, we concluded that the strength points of this factor were more than its weaknesses and the organization had a good status in the field of research. Also by examining the scores of external factors, we found that the score of research factor was greater than 2.5. Then, we concluded that opportunities of this factor were more than its threats, dominating them. Regarding the evaluation matrix of internal and external factors in Enghelab square, the obtained score of internal factors was below 2.5; therefore, weaknesses dominated the strengths and since the obtained scores of external factors were above 2.5, opportunities dominated threats, making this square's position conservative.
Among the 8 important strategies of visual pollution management in Vanak Square, the strategy of establishing air conditioning systems, while maintaining low-rise buildings, with an attractiveness score of 4.281 and the strategy of increasing visual comfort with emphasis on presence of routes to open spaces with an attractiveness score of 4.03 were superior than the other strategies. Among eight important strategies to manage visual pollution in Enghelab Square, the one, entailing the establishment of significant elements and use of public transportation with an attractiveness score of 7.292 and the one about the presence of significant elements and use of green spaces with an attractiveness score of 5.743, were considered the most useful, compared to other strategies. As a result, with regards to the issue of visual pollution, based on the present study, Vanak Square has a better condition than Enghelab square.