CC BY
23
Ukrainian Journal of Ecology
Ukrainian Journal of Ecology, 2018,8(3), 203-211
ORIGINAL ARTICLE
Assessment the impact of women's security, vitality and green space on Majlesi city land valuation by hedonic price
method (Esfahan Province, Iran)
A. Mousavi, E.S. Madani, O. Iranpour
Islamic Azad University, Majlesi, Isfahan Province, Iran. E-mail: em iut@yahoo.com Received: 28.05.2018. Accepted: 26.06.2018
Social issues such as women's security and vitality and environmental issues, such as green space, are not traded in the markets and hence lack specific prices. At the same time, this is one of the major factors affecting the acceptance and pricing of land prices in newly built towns. The purpose of this research is to assessment the impact of urban security and vitality on women, as well as the urban green space index on land economic value in Majlesi and, finally, to propose ideas for increasing land prices, creating economic prosperity and sustainable income. In this research, the valuation of these resources was carried out by indirect methodology. In this way, the preference for land purchase will increase the demand in that area and affect its price. Affective variables in the security debate in urban space include activity and productivity, accessibility and communication, social relationships, comfort and relaxation, and was studied in the field of vitality, economic, social, environmental and cultural vitality. Also, based on the calculation of landscape metrics, the status of this parameter was determined in the landform. The results of quantitative and quantitative researches in the Hedonic Price Method showed a significant positive correlation between the cultural and social values of the place for women, the index of green space in the neighborhood and the price of land in the Majlesi city, Esfahan Province, Iran. Keywords: Security; vitality; women; green space; hedonic economic valuation
Introduction
Increasing the quality of urban life and urban viability in the planning and designing of cities by orienting towards the "sustainable city" is More than ever is attention of the experts (Khan, 2008).
Today, urban space is considered to be a social dimension apart from the definition of solitary space, and it includes content forces that sustain the life and dynamism of urban space. So, it is logical to pay attention to the role and position of women as half of the human population of communities in urban spaces.
The need for security is one of the main human needs. Individuals like Maslow and Herzberg prioritize the need for security in human societies after meeting their biological needs. The importance of the need for safety, security and security is such that it is considered obligatory to maintain equilibrium in society (Safiry, 2008).
Social issues such as the security and availability for women and environmental issues, such as green space indicators, are not traded in markets and therefore lacking in price. At the same time, this is one of the major factors affecting the acceptance and pricing of property prices in newly built townships.
Hence, the valuation of these resources by indirect methods is used. For example, it's true that citizens do not directly pay for security, vitality and green space, but typically they prefer living in a district of the city. This preference will ultimately increase housing demand in that area and affect housing prices. On this basis, it can be interpreted that people at a higher cost of housing, in fact, indirectly cost a higher quality environment (Emami et al., 2009).
The purpose of this research was to assessment the effect of urban security and vitality for women as well as the index of urban green space on the economic value of land in Majlesi, and finally to propose ideas for achieving this important and as a result of rising property prices in the new city of Majlesii and Creating a prosperous economic and sustainable income. Urban public space and women
Livabet (1968) says: "Gender issues can no longer be ignored in planning." Today, with the changes in the way of life and the system of human relations, the social life of women has undergone major changes, so that women as the core The family assemblage has other tasks other than housekeeping and child rearing, with little time to regulate and do all of them, hence the need for ease of purchase from shopping centers (near home or work), educational (Near the place of residence), health
Ukrainian Journal of Ecology_204
care (near the place of residence), etc. (Moady, 2013). Concept of Vitality Urban Space
Basically, vitality is designed with a specific concept including relevant keywords and terms: accessibility, justice and participation, comfort and relaxation, social interactions, availability, security and accountability are among the factors that define and make sense of the concept of vitality (Jahanshah, 2006). Types of vitality
• Economic vitality: Assessed by levels of employment, net income and living standards of people in a surveyed area, the annual number of tourists, retail operations, land value, and assets.
• Social vitality: measured by the levels of social activity and social interaction, as well as the nature of social communication. A vibrant and socially vibrant city can be described by its low levels of deprivation, strong social cohesion, good communication and dynamism among the social strata, collective spirit and civil pride, a wide range of lifestyles, lively relationships, and a city community. .
• Environmental vitality: Two aspects. First, ecological sustainability is associated with variables such as air and noise pollution, waste and waste disposal, traffic volumes, and green spaces. The second aspect is design that includes variables such as legibility, sense of location, architectural differentiation, connection and communication between different parts of the city. , Quality of light and how friendly the environment is, how safe and psychologically approached.
• Cultural vitality: Includes survival, respect and celebration of the city and its people, identity, memories, traditions, social celebrations, production, distribution and consumption of man-made products and signs indicating the distinct nature of the city (Maryam Khostou and Navid Saeedi Rezvani, 2010).
Social security
Social security means that everyone in their place of life and community is comfortable and calm, and is confident and free of any worries about their lives. This secure space requires conditions that, in order to achieve this, urban management should meet the needs of citizens based on the organization and organization. Part of these activities will be carried out by government agencies, and part of it will be achieved with the participation of people in creating secure space (Safiry, 2008). Features of secure social space in urban space
In general, a secure space in the city for citizens is realized if they have four features of the following pattern:
Activities and Productivity: If people in the social space do not feel the safety of their activities, they refuse to attend social
spaces.
Accessibility and communication: such as transportation facilities, shops, parks, places of services for citizens, including municipalities, educational centers, religious places, etc.
Existence of social relationships: People need to have a proper atmosphere in their everyday social interactions in order to be able to become more active in the social networking network.
Comfortable and relaxed: People want to have a pleasant mental image while viewing the comfort of these spaces. Green space
Parks and urban green space are important because of their dual role, the importance of recreation and environmental balance through air stroke, pollution reduction, and physical and mental fatigue. However, given that these effects are not just recreational aspects, other factors must be considered by the planners (Taghvai and Shahverdiyan, 2003). Also, green space should be quantitatively and qualitatively proportionate to the size of the city (buildings, streets and roads) and social needs (psychologically, leisure and health needs), and taking into account The ecological conditions of the cities and their growing trend are to be effective as active green spaces (Taghvai and Shahverdiyan, 2003). Quantifying the spatial Pattern of landscape
Landscape consists of three main features, including structure, function, and variation. According to the management principle, what can not be quantified is not manageable. According to this principle, many attempts have been made in recent years to develop methods for quantifying the spatial heterogeneity of Landscape (Pong et al., 2010)
Landscape metric metrics are a tool for quantization of land patterns (Costazza & Folk, 1997). Metrics are indicators that characterize the geometric, geometric, and the nature of the distribution and distribution of the structure of the Landscape structure, and can be compared and compared with each other (Eskandari and Hasani, 2011). Value
Value is in fact the price people are willing to pay in order to obtain goods or services. The value of a product is determined by the consumer's mental estimation. In other words, value is considered as the relationship between the benefit received by the consumer in relation to the costs observed from these benefits and is often expressed as the following equation: (Ghorbani and Zare, 2010) (1) Value=Benefits/Cost
Environmental attributes will only have value when they enter at least in the individual utility function or the production function of the unit (unit) (Hanley and Spas, 1993).
Here it is best to point out the difference between value and price. Price and value are two separate concepts. We may know the price of anything, but not worth it. It is human-centered, which means that man determines value, not natural law. Value is determined by the willingness to pay for individuals. Price is the cost of obtaining an object, in other words, the amount of money that is equal to those goods are bought and sold. (Ghorbani and Zare, 2010). Economic valuation
Assessing non-market functions and services on the environment on the one hand and cultural issues on the other hand to decision-makers and planners in providing the link between economic policies and natural and cultural revenues in support
205 Assessment the impact of women's security, vitality and green space on Majlesi city land valuation by hedonic price method_
of human well-being and development Sustainable helps (Khodaverdizade, 2008). Economic value and willingness to pay (WTP)
In economics, valuation concepts are related to social welfare. Therefore, economic value in environmental resources is only focused on that part of the ecosystem's service or performance that is a provider of social welfare. Economic values are measured through the concepts of willingness to pay (WTP) or willingness to accept (WTA). Among the two approaches, WTP is the most widely used (WTA) to compensate individuals for changes in environmental conditions (Firooz Zare). The WTP teller is the maximum amount of money a person wants to get a product (why wtp). In economics, WTP is the preferred value of a given value, because it is considered as an accurate indicator of value. Because the WTP is based on the valuation of value by the real persons that measures the values. (WTP) directly by asking people to express their willingness to pay or indirectly by viewing the economic costs necessary for using the environmental (and cultural) services or costs incurred to achieve It is deduced from their successor services (Taghvai and Zare, 2010). Contingent valuation method
There are various ways to assess the economic and environmental conditions. Many of the functions of the tradable ecosystems are not in the market, and they are neither affiliated with or associated with any market commodity. Therefore, people can not reveal what they are willing to pay for their market purchases. In these circumstances, the contingent valuation method is used to ask people to express directly on the hypothetical scenario the amount they are willing to pay for a service (Eskandary and Hassani, 2011). The application of this method is to estimate the value of regulatory, habitat, production, and information functions (King and Mostafa, 2000). In this method, in order to determine the economic value of the ecosystem's functions, it is necessary to refer individuals to extract their internal preferences (Khodroodizadeh, 1987) The term "hedonik" from the Greek root of Hadaynukus means pleasure. In the context of the welfare economy, the term means the utility or satisfaction of the consumer by the consumption of goods and services. Hedonic pricing calculates the value of a commodity in the market by examining the relationship between non-marketable goods and the demand for some of the complementary goods supplied to the market. Hedonic pricing is based on the principles of basic economics theory based on the demand curve. In accordance with the principles of valuing non-public goods, it is based on willingness to pay. This method reflects the level of people's demand for conditions that this demand reflects in choosing the place and type of residential home. The main assumption in the hedonic approach is that the price or rents of each land is a function of its physical, spatial and environmental characteristics (Gorbani and Zare, 2010)
The theoretical framework of this methodology is based on researchers such as Ridder, Henning and Rosen, based on the welfare economy. The history of using this method dates back to the 1920s. John Bates Clark and Kelvin John Lancaster have made great efforts to develop this approach. (Izadi & Barzegar, 2011)
Morancho 2003 studied a relationship between the price of residential houses and urban green areas using the Hedonic method. In addition to the contract variables used to describe the price of homes, three environmental variables were used, including: the presence of a park or public garden, the distance from residential areas to the nearest green space and the size of the open space. The results showed that there is an inverse relation between the transaction price of the property and its distance from the green space.
Also, Mohammad Zadeh et al. (2012) studied the impact of security on the price of residential property in a hedonic study. The results showed a positive and significant effect.
Materials and methods of research
Study area
The new capital city is located 65 km from Isfahan in the city of Mobarakeh. Its total area is 536,595 hectares and its built area is 377.67 hectares, with seven neighborhoods called Golestan, Farhang, Sepehr, Kushesh, Honar, Mahan and Mehran with 10,000 inhabitants. The basic data of the city of Majlesi in Table 1 and the location of the Majlesi and the neighborhoods studied in Isfahan province are presented in Figure 1.
Ukrainian Journal of Ecology 206
Figure 1. Location of the Majlesi and the neighborhoods studied in Isfahan province.
Table 1. Structural information of neighborhoods in the Majlesi city.
Golestan Farhang Koshesh Sepehr Honar Mehran Mahan
Area (Hectar) 64.2 54.87 67.73 55.99 58.75 51.86 23.66
Population 1700 1600 800 1200 700 1000 3000
Area (Hectar) Green space 23.11 2.5 11.24 4.8 3.8 8.8 3.9
Per capita park per person (M2/person) 135.95 15.77 14.54 34.6 54.55 88 13
Data and tools used in research
The polygon map of the parks was developed using the geographic location of the parks in two regions, in the Google Maps image. Also, according to the texts studied and expert opinions, a questionnaire was prepared. An example of a questionnaire is provided in the appendix. Sample size was calculated based on population density using Cochran formula. And questionnaires were collected in the mentioned areas.
The appropriate metrics on the level of the patch, the class, and the landscape were selected for carrying out the relevant analyzes by reviewing similar studies. In the ArcGIS 10 application, as well as Fragstats 3.3, parameters were calculated for the distribution of the parks in these two regions. To illustrate the structural characteristics of these parks, both composition and Configuration spatial metrics were used.
In the discussion on the security and vitality of the city's public space for women, according to the results of the questionnaire, utility maps were prepared and completed in GIS. Indicators of green space
Number of patch (NP): This metric brings the number of Patch at the level of the class or the landscape. Percentage of landscape (PLAND): Measures the proportion of the percentage of each type of spray (class). Pi=Relative of the Landscape occupied by the type of patch i, ay=Area (m-square) of the patch, A=The total area of the Landscape. i: Total area of the patchs.
PLAND = p = ^ a'] (100) (1)
Patch density index (PD): This metric shows the number of patchs per unit area and allows comparison between different areas=The number of patchs of type I, A=total area of the Landscape, the number of type I patchs divided by the total area of the Landscape multiplied by 10,000 for the conversion of hectares (multiplied by 100 to the density of patchs per 100 hectare PD=n/A(100) (10000) (2)
Edge density metric (ED): The equivalent of the length of all margins is divided by the area and is obtained from the following equation.
ym e
ED = i=1 ik (10000) (3)
A
eik=The total length of the class i in the landscape, A=the total area of the Landscape, multiplied by 10000 per hectare. Largest Patch Size (LPI): aij=Area (m2) Patch, A=Total Landscape Area (m2). The largest-sized profile of the patch with the area of the largest patch in the Landscape is divided by the total area of the landscape multiplied by 100 to the percentage. In other words, this profile shows the percentage of land imagery that has the largest patchs. 100 > LPI>0 When the area of the
207 Assessment the impact of women's security, vitality and green space on Majlesi city land valuation by hedonic price method_
largest patch is very small, this value is set to zero, and when the entire Landscape is covered only by a type of Landscape, then this profile is equal to 1. max a,,
LPI =-j (100) (4)
A
Mean patch size (mps): Means the average size of patchs at the level of the class or the Landscape. ai = patch area, m=number of patch.
yffl I" "I
MPS= (5)
m
Landscape signature profile (lsi): To measure the shape of the patch=perimeter class, i=minimum class perimeter.
e
LSI=-i— (6)
min ei
Mean nearest neighbor (MNN): The average of the nearest distances from a patch to another patch of the same type (aside). The distance between each patch and the nearest neighbor of its kind: hi' the total number of nearest neighbors to the patch: m.
Ym h
MNN = ±*=L-L (7)
m
The theoretical foundations of the Hedonic price function
In the pattern of Hedonic demand, a commodity has a multi dimensional dimension, and because the housing is also multidimensional, that is, a residential unit, such as a composite commodity, contains a basket of various features. As a result, the use of the hedonic price pattern in the housing market would be appropriate (Aboornuri et al., 2009). Hence, housing prices would be a function of the properties used in the housing unit demanded by the household, which is called the hedonic price function. The function of the price of the hedonic is indicated by p (z) (Awenuri et al., 2009). P(Z)=P (Z, Z.....Z) (8)
The price function shows the relationship between the market price of a land and its characteristics, that is, the effect of each feature of the residential unit in question, on its market price. If the conditions for maximizing profits by the suppliers of the land as well as the optimization of the demanded households are taken into account and the balance is taken into account through supply and demand, the price of the hedonic will be achieved. If a family uses physical, spatial and environmental features and other commodities, then this choice makes the household feel satisfied and provides a level of prosperity. And the utility function of this household is as follows: U=U (X, Z) (9)
Where z is the physical, spatial and environmental characteristics of a residential unit and X is another commodity. Now, if for simplicity of analysis, we will consider the price of other goods as a unit and show the household income with Y. The household budget can be written as follows (Aboornuri et al., 2009). Y=P(Z)+X (10)
Now, according to the Lagrange method, in order to maximize its utility function and with regard to the budget constraints
that exist, it will be as follows:
MAX U=U (X, Z, Z, ..., Z) and St: Y=P(Z)+X
L=U(X, Z, Z, ..., Z)+ A (Y-X-P(Z)) (11)
Where the initial condition for maximizing the utility function is as follows:
By solving the system of equations for P (Z), when all the properties except Zi are constant, the price function offered by the family comes in:
e=e (Z, z, ..., z, y, U)
In this equation, e is the proposed price for U's utility and Y is a typical household income (Avonurie et al., 2009).
In this research, for the purpose of estimating the price of a hedonic, the questions and questions and how they are arranged
in proportion to the subject of research, the function of the price of the hedonic is set.
SPSS, Excel, AutoCad10, Eviews, GIS were used to analyze the data and estimate the parameters of spatial econometrics. Given the features of the price function of the price of the price, and taking into account the effective variables, the variables
Ukrainian Journal of Ecology_208
used in this research will be as follows: As a dependent variable:
• Price variable (PRICE): This variable is obtained based on the land number in RMS.
• Security variables in urban space include: activity and productivity, accessibility and communication, social relationships, comfort and relaxation
• Vital variables include: economic vitality, social vitality, environmental vitality, cultural vitality
• Green space variables include per capita green space per neighborhood and access to green space
• Data on land prices and its features are available from city offices, businesses, and services and other resources. Sample selection and sampling number
A total of 300 questionnaires were distributed and completed. SPSS software was used to construct regression model. After entering and defining each of the variables into the software, the multivariate regression model was estimated using stepwise method. The choice of step-by-step approach is an attempt to gradually insert variables until the regression equation becomes satisfactory. In this way, by performing a statistical test, the most effective independent variables (structural, neighborhood, access, and environmental) were identified in the formation of the dependent variable (land price). The criterion for deciding whether or not there is a relationship between variables and the ratio of correlation coefficient and significant level 1.
Cronbach's coefficient for the final questionnaire was 0.55 which indicates its reliability is acceptable. Questionnaires were also approved by experts and experts in this field.
Results and discussion
The results of this study are as follows:
The results of urban safety and livelihood questionnaire for women in GIS software were mapped in 8 maps. The results of each section are as follows:
Security: Golestan>Sepehr=Farhang>Mahan>Honar>Kushesh=Mehran Vitality: Sepehr>Golestan>Farhang>Mahan>Honar>Kushesh>Mehran
The overlay results of the two indicators are shown in Figure 2. In this green-to-red color figure, the importance of reducing the security and vitality criteria is in the order of magnitude.
Figure 2. Overlay map of the security and vitality values of urban space for ladies in the Majlesi city (the trend of devaluation from green to red).
Table 2. Green space metrics.
Aij(green space A(ar PLA NP(number of ED Mean patch Maximum LPI MPS PD
area) ea) ND patch) area patch
Golest 231120 6420 36/0 40 65/3 5778 130000 20/2 5778 62/3
an 00 0 4 5 1
Farha 25200 5487 2164 5 13/8 5040 20000 234 5040 434
ng 00 1 7 37 13
Koshe 112400 6773 16/6 2 432 56200 100000 433 56200 347
sh 00 0 56 26 31
Sepeh 40900 5599 1114 10 19/1 4090 12000 416 4090 17/8
r 00 0 7 71 6
Honar 38200 5875 1841 2 431 19100 21000 208 19100 146
00 5 66 80 71
209 Assessment the impact of women's security, vitality and green space on Majlesi city land valuation by hedonic price method_
Mehra 88000 5186 16/9 6 15/6 14666/66667 26000 431 14666/66 211
n 00 7 4 05 667 25
Maha 39000 2366 16/4 4 16/4 9750 59000 24/9 9750 16/9
n 00 8 6 4 1
In the present study, the green spaces of the seven neighborhoods were extracted from the QuickBird satellite image in Google Earth software. The map was analyzed to determine the distribution of green spaces in these areas in FRAGSTATS software. Then several metrics were selected and used in the Hindun pricing model.
Gelatin. Fsjlisji? t^p^hr H?nzr M?hraji MsJizji T- i i ^
G-clr:t ip. railiajiï Koshesh Sepahr Honir Mehr.m Mjlizn
Figure 3. Results of the metric survey of green space indicators in the new city Majlesi landscape.
As shown in Table 2 and Figure 3, the results of the PLAND metric indicate that Golestan with 36% and farhang with 5% have the highest and lowest percentage of green space in the region, respectively. Also, Golestan with 40 patchs has the highest degree of fragmentation (NP) and patchs density (PD). The MPS represents the average size of green space patchs in each area, with the increase in this ecological efficiency and ecological function as the only surviving natural environment in the city's space, the lowest spatial value of the metric has been allocated. The larger the metric ED or the Edge density in the urban environment indicates its higher accessibility to the public, which is one of the most important principles in designing and locating the park. Also LPI high number in the Mahan neighborhood, it means a low number of patchs. Obviously, the Golestan neighborhood and the effort have the highest and lowest Edge density, respectively. Land price: The price of land based on the results of a questionnaire of experts is as follows: Sepehr>Golestan>Farhang>Honar>Mahan>Mehran>Koushesh Results of spatial econometric estimation
Spatial and econometric econometrics have been used to derive the results of residential unit prices in the city. The results of this model are presented in Table 3 using Geoda software Lag.
Table 3. Estimated land prices using spatial econometrics._
Expectant The correlation coefficient Multiple correlation coefficient
Activities and Productivity Positive** 0/74 0/54
Accessibility and communication Positive** 0/85 0/72
social relations Positive** 0/67 0/52
Comfortable and relaxed Positive** 0/92 0/9
Economic vitality Positive** 0/74 0/62
Social vitality Positive* 0/84 0/00
Environmental vitality Positive** 0/86 0/78
Cultural vitality Positive** 0/84 0/82
Green space Positive** 0/33 0/57
Landscape Edgh Positive** 0/63 0/67
Number of observations 300
* And ** coefficients are significant at 95% and 99% levels.
In a supplementary study of the relationship between the higher price of land in the arena and the Mahan area, other reasons such as the villa of the real estate in the area of art have been affected. The aim of the study was not to assessment such cases.
Ukrainian Journal of Ecology_210
Studies show that for every 1% increase in security measures, the vitality of the amount and the margin of green space, respectively, increases the price per square meter of land 40, 23, 10 and 15 thousand USD. Increasing the margin of green space will mean increased access. The figures highlight the importance of security factors for women in their desire to buy land among people. Therefore, providing these conditions will be an effective step in increasing the price and willingness of people to buy land and sustainable development of the city's parliament.
Conclusions and recommendations
Improving the quality of urban space to interact and secure the presence of women in the city and the vitality of these spaces on the one hand and the indicator of urban green space on the other are a series of factors that indirectly affect the price of land in the city center. The quantification of this link will effectively assist urban managers and planners in raising land prices, creating sustainable income, and ultimately a sustainable city.
In this way, the proposed strategies in the area of urban planning and design women are as follows:
Zoning Criteria: It seems that the approach to disassociate major uses, such as work, housing, is one of the factors affecting the privacy of street and city centers at night. For this reason, the creation of diversity in mixed activities and uses, in addition to helping to enhance the vitality and attractiveness of urban spaces, can help protect the spaces and attract women and other vulnerable groups.
In designing settlements and residential complexes, creating active spaces between blocks and around parking lots and development of semi-private spaces, which attracts residents' interest in the presence and protection of them. Access should also be designed in such a way as to be legible, clear and visible, and to avoid creating blind patchs as much as possible. Appropriate lighting, open spaces, parking lots, commercial buildings, city centers, intersections, bus stations, pedestrians and more.
Public transportation: Public transportation faces two major risks. The first is the problem of waiting for passengers at remote stations and public transportation of public buses and taxis, which causes more insecurity and fear for passengers, and in particular for women. In this regard, the proposed solution is to make the public transport system safer, which is an option to increase the safety of intra-city travel. Some measures needed to achieve this aim include the presence of guides at the station and public transport, covering public transit lines into urban neighborhoods, and providing safe and secure access to residential units, installing cameras at stations, as well as means of transport And its activation, as well as ticket booths and supermarket kiosks, at least in the dark hours and at noon. If we look at the utility of the public transportation system (considering that the main vehicle for women), the type of quality of equipment used by users is very effective. For example, if the standard height for bus stops or ergonomic tramlining of bus stations is met, the quality of operation will be more appropriate for all citizens, and in particular for women. In addition to providing lighting and security at night, the proper placement and placement of pedestrian crossings is another important factor in the better utilization of women from urban transport systems.
Placing a fast and accessible wireless taxi in the city, lighting and monitoring the areas of crime and proper maintenance of urban furniture, signs, urban symbols, lighting and landscaping lights that can, in addition to optimizing urban costs, increase the capacity of areas in crime Also reduces. Care should be taken to plant plants and to avoid the creation of hidden and uncontrolled corners.
Considering the need to build and enhance the "women's garden" to an exclusive space for women. Or an experience such as the paradise of mothers where women can openly play sports, relax, and feel safe. Experience has shown that the tendency to use these spaces is increasing.
The construction of a child's home for holding children's watches near shopping malls and adult recreation centers. Studies have shown that packaging and product production with the female employer are smoother and more beautiful, and on the other hand, men have come to the forefront of production, and their morale has become more feminine, a fact that women do not know much about. The precision, elegance, and planning for production are much stronger in women. Therefore, in the production and planning of urban and urban furniture, the capabilities of this stratum should be used. Establishing an assembly called the "Women's Decision-Making Assembly" where women working in different parts of the government gather together and manage issues by looking at women as identity banners and addressing women's issues in the city.
Also, considering that the building is one of the new and developing cities, creating a permanent place to resale the day market and the place of sale of home-grown products with the presence of the private sector investor, the creation and construction of a game city in the city of Majlesii with a prestigious view Being in town in terms of facilities, organizing and restarting the easy-to-use Mawa site in order to accommodate the largest elderly service site can be a striking step towards boosting the city and increasing land purchase tendency.
References
Hanley, N., & Spash, C. (1996). Cost benefit analysis and the environment.
Costanza, R., & Folke, C. (1997). Valuing ecosystem services with efficiency, fairness and sustainability as goals. Nature's
services: Societal dependence on natural ecosystems, 49-70.
King, D. M., Mazzotta, M., & Markowitz, K. J. (2000). Ecosystem valuation.
Morancho, A. B. (2003). A hedonic valuation of urban green areas. Landscape and urban planning, 66(1), 35-41. Taghvai, M., Shahverdiyan, M. (2003). An Introduction to the Basis of Urban Green space Design. Sabz Mouj, 4(15), 32-36.
211 Assessment the impact of women's security, vitality and green space on Majlesi city land valuation by hedonic price method_
Taghvai, M., Shahverdiyan, M. (2003). Planning and Design of Urban Green space and its Interactions on Human and Environment. Sepehr Quarterly Journal, 12(47), 46-55.
Pakzad, J. (2006). Theoretical Basis and Urban Design Process. Urban and Architectural High School Publications.
Khodawarizadeh, M., Hayati, B., Kavousi, K. M. (2008). Estimation of the environmental value of the tourist village of
Kandovan, East Azarbaijan, using Contingent valuation method method. Environmental Sciences, 5(4), 43-52.
Safiri, K. (2008). The role of local NGOs in providing social security with reliance on Tehran. Journal of Social Studies of Iran,
2(2).
Khan, S. M. (2008). Assessment Patterns of Urban Green spaces Using Urban Green space Ecology Approach and its Relationship with Urban Sustainability (Case Study: Tehran Metropolis). Third National Conference on Green and Urban Green space, 27, pp. 147-156.
Abu, N. A., Ramezani, K. V. R. (2009). Estimation of Housing Demand Function Using the Hedonic Model (Case Study: Sari City). Journal of Humanities and Social Sciences, Mazandaran University, 4, 13-34.
Emami, M., Azami, A., Haghdoost, A. (2009). Assessment the Effective Environmental Factors on the Prices of Residential Houses in Tehran by Hedonic Method. Economic Research, 44(87), 27-52.
Peng, J., Wang, Y., Zhang, Y., Wu, J., Li, W., Li, Y. (2010). Evaluating the effectiveness of green space metrics in quantifying spatial patterns. Ecological Indicators, 10, 217-223.
Khosto, M. and Saeedi, R. N. (2010). Factors Affecting the Liveliness of Urban Spaces, Urban Identity, 6.
Taghvai, M., Firooz, Z. A. S. (2010). Introduction to Environmental Valuation. Ferdowsi University Press, p. 216.
Eskandari, D., Hassani, H., Lichaei, B. (2011). Measuring the Economic Impact of Green spaces on Urban Development. First
National Conference on Civil and Development, Beautiful Next.
Izadi, H. Barzegar, S. (2011). An Assessment of Economic Valuation Methods in the Analysis of Urban Environmental Issues. Urban Economics Conference of Iran, Ferdowsi University of Mashhad.
Mohammadzadeh, P., Masoud, M., Babak, K. L. (2012). The Estimation of the Hedonics Cost of Residential Buildings in Tabriz City: With the Space Econometric Approach. Economic Modeling Quarterly, 6(2), 21-38. Moady, M. (2013). Women's Conferences, Architecture and City.
Citation: Aminollah, M., Elham, S.M., Omid, I. (2018). Assessment the impact of women's security, vitality and green space on Majlesi city land valuation by hedonic price method (Esfahan Province, Iran). Ukrainian Journal of Ecology, 8(3), 203-211. I ("il^^^^MlThk work Is licensed under a Creative Commons Attribution 4.0. License
