Measuring physical indicators of urban housing (Case Study: Gorgan)

Subject Areas :

Ebrahim Moameri ¹ , Mohammad Farrokhzad ² , Yasin Sayyad Salar ³

1 - Golestan University
2 - Assistant Professor, Architecture Department, Faculty of Engineering, Golestan University, Gorgan, Iran
3 - Ferdowsi University, Mashad, Iran

Received: 2018-11-24 Accepted : 2019-10-18 Published : 2020-01-21

Keywords: housing, Gorgan, WASPAS, Urban Housing, Housing Quality Indicators,

Abstract :

           The smallest housing and the smallest form of physical embodiment is the interconnectedness of man and the environment and the most private space of human life. Obviously identifying the quality levels of housing indices in different urban areas is an effective step in explaining the quality of life levels. Accordingly, the present study was conducted to evaluate the status of housing indices in urban areas of Gorgan. The type of research in this research is "Applied-development" and the "descriptive-analytic" method. In order to analyze the data from the Excel spreadsheet software and to prioritize the areas based on the indicators, WASPAS and WP multi-criteria decision-making techniques were used. The results show that in the spastic technique of the region 2 with the priority coefficient (355/0) in the first place, the third with a priority coefficient (336/0) in the second order, the seventh with a priority coefficient (315/0) in the third order The first one with a priority coefficient (0.228) in the fourth order, the fifth area with the priority coefficient (0.27) in fifth order, the fourth area with the coefficient of priority (0.263) at the sixth level, the sixth area with the priority coefficient (240 / 0) is in the seventh rank and area eight with a priority coefficient (235/0) at the eighth position. The results of the WP technique show that area 8 with a score of (501/0), area 2 with a score of (273/0), area 3 with a score of (251/0), area 7 with a score of (24/03), area 4 with Score (212/0), District 1 with score (197/0), Area 5 with score (196/0) and Area 6 with a score of (193/0), respectively, from the most stable to the most unstable areas in terms of physical indicators of housing In the city of Gorgan.
 
Keywords:Urban Housing, Housing Planning, Physical Housing Indicators, Gorgan City.
 



 


 
 



 
Extended Abstract
Introduction:
        Quantitative and qualitative housing analysis is done through a tool called variables called housing indices that represent different economic, social, cultural and physical dimensions of housing. Housing is a basic human need, and this confirms that governments are legally responsible for ensuring citizens have adequate access to adequate housing. The purpose of this study is to investigate the status of physical housing indices in eight districts in order to rate the status of districts in terms of quantitative and qualitative indices of housing to prioritize the preparation of a comprehensive housing plan in Gorgan. Thus, firstly, general understanding of the physical status of this area will be achieved for urban managers and planners, and secondly, areas of poorer quality physical planning will be identified and prioritized in terms of planning. In general, the most important goal of this study can be summarized as follows: The need for a proper and adequate understanding of the current situation in order to achieve proper and effective planning in the physical housing situation.
Methodology:
The purpose of this research is applied research and its descriptive-analytical nature with regard to method of work. The data were collected through library and documentary studies. The information was extracted from the official data of the 2011 statistics of Gorgan. The composite indices used in this study to evaluate housing status in eight districts of Gorgan have been extracted from urban planning and geography and urban planning researchs, including: x1 Residential Infrastructure (m), x2 Residential Area (m), x3 Gross Residency, x4 Single Floor Buildings, x5 One Storey Infrastructure (m), x6 Residential Area Only, x7 Population, x8 area (m), x9 net residential density, x10 three-story buildings, x11 three-story buildings, x12 two-story buildings, x13 two-story buildings, x14 percent occupancy, x15 per capita and x16 are building density (m). Since each of the 16 indices have different significance coefficients, Shannon entropy method is used to weight the indices. After determining the weight of the indices, multi-criteria decision-making methods have been used to classify the areas in terms of housing indices. Gorgan city with an area of 3669 hectares is located in the northern cities of Iran and the center of Golestan province, located in the southeast of the Caspian Sea. Its average elevation is 155 meters. The city extends to 54 degrees 26 minutes east longitude and 36 degrees 50 minutes north latitude on the north slope of the Alborz Mountains. Currently, Gorgan has a population of 354,000 with three regions and eight districts, covering a population of 115,000 in 1^st region, 124,000 in 2^nd region, and 114,000 in 3^rd region.
Results and discussion:
The obtained relative entropy coefficient was 0.931, which is very low at 1, indicating a balanced population distribution in Gorgan. The results of the waspas model show that the urban areas of Gorgan, in terms of urban housing indices, are at different levels, out of 8 urban areas, Area 2 in the south of Gorgan, and in the favorable part of urban climate with priority coefficient (0.355) ranks first in terms of urban housing indicators. Area 3 in the north of Gorgan with priority coefficient (0.336) in the second rank; Area 7 in the eastern entrance of the city with priority coefficient (0.315) in the third rank; Area 1 with priority coefficient (0.289) in the fourth rank; Area 5 with priority coefficient (0.270) in fifth order, Area 4 with priority coefficient (0.263) in sixth order, Area 6 with priority coefficient (0.240) in seventh order and Area 8 with priority coefficient (0.235) ranked eighth in terms of urban housing indicators. This indicates the poor condition of Gorgan city in terms of urban housing indicators. Of the Gorgan city areas, Area 2, which includes the southern part of Gorgan, and the newly constructed parts of the city, built on the principles of engineering and commensurate with the properties of the almonds, is the best in terms of housing indexes and Area 8, which contains centralized and downtown tissue, for some reason, including old tissue, has a high population and inadequate housing, and has the worst situation in terms of urban housing indicators. The WP model results show Area 8 with score (0.501), Area 2 with score (0.273), Area 3 with score (0.251), Area 7 with score (0.243), Area 4 with score (0.212), Area 1 with a score of (0.197), Area 5 with a score of (0.196) and Area 6 with a score of (0.193), respectively, from the most stable to the most unstable areas in terms of housing physical indicators in Gorgan city. Examination of the current status of physical indicators of housing in Gorgan shows that the housing situation in different parts of the city is not equal and has a significant difference with the principles of justice. However, a look at the status of different housing indicators in different areas reveals that a significant percentage of housing has been created without regard to existing principles and standards.
Conclusion:
The purpose of this study is to investigate the status of housing indexes in eight districts in order to rank the status of districts in terms of housing indicators to prioritize the preparation of a comprehensive housing program in Gorgan in order to gain a general understanding of the physical status of this area for urban managers and planners, identify areas of less favorable physical quality and priority in terms of urban housing planning. Finally, it can be said that Areas 3 and 2 are in stable condition in relation to housing properties. Areas 1, 5 and 7 are in semi-stable housing terms. Areas 8, 6 and 4 are unstable in terms of housing indicators.

References:

1. Ebrahimzadeh, Eisa, Ghasemi, Ezzatollah )2015), Evaluation of Physical Indicators of Urban Housing with Sustainable Development Approach Case Study: Saman City, Urban and Regional Studies and Research, 7^th year, No. 26, pp 83-104.


2. Ahmadi, Vahid (2011), The Pathology of the Iranian Housing Market, Chook Ashtian Press, Tehran.


3. Esmaeelzadeh, Hassan, Esmaeelzadeh, Yaghoub (2016), Evaluation of Housing Qualification and Quality (Case Study: Gilan Provinces with Emphasis on Urban Areas), Geographical Engineering of Land, 1^st year, No. 1, pp 13-23


4. Inanlou, Ali (2001), Analytical Housing Planning on Housing Supply and Demand in the North of Qazvin City, Master thesis, Geography Department, Humanities faculty, Tarbiat Modarres University, Tehran.


5. Toufiq, Firooz (2003), Housing Planning, a collection of educational planning housing articles, National Organization of Land and Housing, Tehran.


6. Dezhakam, Laleh (1994), Government and the Housing Issue, Proceedings of the Seminar on Iranian Housing Development, Ministry of Housing and Urban Development, Vol. 1, 1^st edition, Tehran.


7. Dalalpourmohammadi, Mohammad (2017), Housing Planning, Samt press, Tehran.


8. Roostaei, Shahrivar, Ahadnejad, Mohsen, Asghari zamani, Akbar, Zanganeh, Alireza (2012), Investigation of Physical-Social Indicators of Housing in Determining Poor Blocks Using Factor Analytical Model (Case Study: Kermanshah City), Human Geography Research, No. 81, pp 141-156.


9. Zangeneh, Mehdi (2015), Spatial Analysis of Housing Situation in Mashhad Metropolis with Emphasis on Sustainable Urban Development Indicators, Urban and Regional Studies and Research, 7^th year, No. 27, pp 137-154.


10. Ziari, Keramatollah, Ghasemi Ghasemvand, Ezzatollah (2016), Evaluation of Quantitative and Qualitative Indicators of Housing with Sustainable Development Approach (Case Study: Saman City), Geographical Researches of Urban Planning, Vol. 4, No. 2, pp 197-221.


11. Ziari, Keramatollah, Mehdinejad, Hafez, Parhiz, Faryad, Aghajani, Mohammad (2011), Survey of Housing Status of Income Groups and Estimation of Low-Income Housing (Case Study of Hormozgan Province), Geographical Research Quarterly, No. 98.


12. Sartipipour, Mohsen (2008), Evaluation and Analysis of Rural Housing Properties in Iran, Conference on Housing Development Policies in Iran, Ministry of Housing and Urban Development.


13. Shokrgozar, Asghar (2016), Urban housing development in Iran, Haghshenas press, Rasht.


14. Shams, Majid, Gomar, Mona (2015), Evaluation of Quantitative and Qualitative Indicators of Housing in Hamadan Province (with Emphasis on Low-Income Classes), Regional Planning Quarterly, No. 20, pp 55-68.


15. Azizi, Mohammad Mehdi (2005), An Analysis on the Status and Change of Urban Housing Indicators in Iran, Journal of Fine Arts, No. 23, Fine Arts faculty, University of Tehran.


16. Ghaed rahmati, Safar, Meshkini, Abolfazl, Garoosi, Alireza (2017), Evaluation of Housing Qualitative Indicators in Housing Planning (Case Study: Nazar Abad Urban Areas, Alborz Province), Journal of Geography and Urban Space Development, 4^th year, No. 2, pp 243-262.


17. Ghorbani, Rasool, Mahmoodzadeh, Hassan, Hosseinpour, Maziar (2018), Evaluation of Sustainable Housing Indicators with Sustainable Development Approach (Case Study: Tabriz Districts 2 and 4), Geography (Iranian Journal of Geography), New edition, 16^th year, No. 56, pp 90-107.


18. Ghanbari, Abolfazl, Zaheri, Mohammad (2010), Evaluation of macro-housing policies in pre- and post-revolution programs, Journal of Housing and Rural Environment, No. 132, pp 77-90.


19. Moammeri, Ebrahim, Mirkatooli, Jafar, Bazi, Khodarahm (2016), Evaluation and Monitoring of Housing Policies for Urban Low-Income Groups from the Perspective of Housing Sustainability Indicators Case Study: Mehr Gorgan Housing, Journal of Geography and Urban Planning, in press.


20. Moammeri, Ebrahim, Mirkatooli, Jafar, Bazi, Khodarahm (2016), Analysis and Evaluation of Housing Policies for Low-Income Urban Groups with Emphasis on Mehr Housing, Gorgan City Case Study, Master of Geography and Urban Planning, Golestan University.


21. Mirkatooli, Jafar, Moammeri, Ebrahim (2017), Spatial Distribution of Urban Services Development Indicators Using Composite Relative Detection Techniques in Anatomy of Urban Settlements of Golestan Province. Journal of Physical Development Planning, 2^nd year, No. 2 (New edition), pp 11-26.


22. Meshkini, Abolfazl, Khaliji, Mohammad Ali (2016), Evaluating Housing Status in Neighborhoods of Bonab Using Cluster Analysis, Journal of Human Geography Research, Vol. 48, No. 4, pp 617-629.


23. Moein, Mohammad (2011), Moein Encyclopedia, Zarrin press, Tehran.


24. Buckley, R., K. Jerry. (2005). Housing Policy in Developing Countries: Conjectures and Refutations, World Bank Res Obs: 233-257.


25. Jaiyeoba Babatunde Emmanuel (2013). Housing Quality” To the Low Income Housing Producers in Ogbere, Ibadan, Nigeria, Procedia - Social and Behavioral Sciences, Volume 35,2,Pages 483-494.


26. Jiboye, Adesoji(2011) . Evaluating Public Housing Performance: Providing a Basis  for Residential Quality Improvement in Nigeria ,Middle-East Journal of Scientific Research 9 (2): 225-232, .


27. Karatas, Aslihan, El-Rayes, Khaled(2016). Optimizing dradeoffs among housing sustainability objectives, Automation in construction,53:83-94.


28. Mills, Gregory, Daniel Gubits, Larry Orr, David Long, Judie Feins, Bulbul Kaul, Michelle Wood, and Amy Jones,( 2006) , Effects of Housing Vouchers on Welfare Families. Washington, DC: U.S. Department of Housing and Urban Development.


29. Oladapo,A(2006) study of tenants’ maintenance awareness, responsibility and satisfaction in institutional housing in Nigeria Full Terms & Conditions of access and use can be found at International Journal of Strategic Property Management, 217-213.


30. Tran,P.N, Boukhatea,N.(2009). Comparison of MADM Decision Algorithms for Interface Selection in Heterogeneous Wireless Networks, Computer Science & Network Department, TELECOM ParisTech, 46 rue Barrault, 75013 Paris, France

1. Triantaphyllou,E.& Baing,K. (2004), The Impact of Aggregating Benefit and Cost Criteria in Four MCDA Method , Dept of Inustrial and Manufacturing System Engineering  Louisiana State University, IEEE Transction on Engineering Management.

32. Wong, T.Ch. A. Yap. (2003). from universal public housing to meeting the increasing aspiration for private housing in Singapore, Habitat International: 361–380.