Modeling the Urban Deterioration and Typology in Deteriorated Fabrics’ City of Qom

Document Type : Research Paper

Authors

tarbiat modares univesity

Abstract

Extended Abstract
Introduction
Any concern for understanding changes in rapid urbanization, particularly those in a deteriorated urban area, requires the exhaustive investigation of the underlying factors for their evolution and subsequent development. In the recent development process of urban places, their central areas have gradually lost their values because the medium and high-income groups leave those places for the suburbs. Therefore, the centers of the cities faced with physical deterioration, economic and environmental problems and were occupied by the poor immigrants and low-income groups. In consequence of this migration and displacement, quality of life in these areas downgraded to so lowest possible that destructed the fabrics. Urban planners require detailed information about the functional, morphological and socio-economic structure of the built environment that are the first step to classify them in similar categories. Many of planners have emphasized on the importance of typology and classification as the first action and most important process of the intervention of the old fabrics. According to this, the focus of this study is to provide a scientific and systematic method to classify and typology deteriorated fabrics. Type as a concept refers to a kind, class, or category of people or group of objects that have certain characteristics in common, which are distinct from the other groups of objects. Hence it is possible to identify objects, events, and settings with specific characteristics.Typology is a descriptive and analytic tool that helps develop and refine concepts, tease out underlying concepts and create categories for classifying, measuring and sorting case studies so urban researchers often have tried to categorize and organize cities with typology frameworks. What it is interesting in this research is 1074 hectares of the city of Qom is covered with decline which allocated about 6.8 percent of the city’s legal limit its own and is occupied by over 220 thousand people. The principal aim of this study was to explore the main factors of urban deterioration, typology and classify old texture of Qom city based on effective homogeneous factors. So the present paper seeks the modeling that categorized homogeneously urban declined area in terms of physical, socio-demographic, economic and environmental characteristics
Methodology
The present study is applied and is investigated by the library, and documentary studies. Statistical data include 1609 statistical deteriorated blocks in the city of Qom. The process of this study involves several steps. First, the effective indicators of deterioration were investigated; then, the measurement of the deteriorated blocks of the city was studied. These were done by using factor analysis model type R, in which research indicators were loaded into four factors: physical, socio-demographic, economic, and environmental factors. After specifying the main factors and measuring deterioration in each block in the city, the kernel density estimation method was used because of the typology of the old fabric of the city. The data analysis was made using inferential statistical methods using SPSS and ArcGIS10 software.

Result and discussion
Due to the complexity of the urban deterioration phenomenon, it is impossible to study urban deterioration in Qom city as a discrete and individual phenomenon so identification of main factors and typology of the deteriorated district of Qom need several steps. The first step is to identify the main factors and measure urban deterioration. Factor analysis as a powerful tool is responsible to develop solutions to reduce and analyze the factors. The results of this research showed that 20 indicators by using factor analysis were reduced to 6 factors which are the most effective indicators to identify old fabrics in the city of Qom. Accumulatively all the extracted factors explained 67.95 percent of urban decayed fabrics. Economic and social factors were known as the main factors in the deteriorated fabric of the city of Qom. The measurement of the deterioration of the city had the most relationship with economic indicators such as land price, occupational classification, income groups and housing facilities. Then, in association with the priorities of development and intervention in the old fabrics, the district is categorized into five different levels (or priorities) based on their surface deteriorated textures. the results obtained from a kernel density estimation of deteriorated locations showed that the highest concentration of urban deterioration are located mainly in the north and south of the deteriorated district of the city and had the most prone and highest probability of severity and extension of the deterioration, therefore, to intervene and renovate this district, these places have the highest priorities.

Conclusion
Urban deterioration and decline are created and aggravated by many factors and variables and are considered as one of the most severe environmental and socio-economic problems of recent times. These areas faced with physical deterioration, economic and environmental problems and were occupied mostly by the poor immigrants and low-income groups. Renovation and intervention in deteriorated areas are a complex and multidimensional process, and a unique phenomenon for each city. Adopting the same approaches and strategies to develop cities despite their heterogeneities and their differences in terms of physical, socio-demographic, economic and environmental conditions of cities result in unbalanced planning and encountering cities with unsustainable cycles of socio-economic and environmental imbalances ,and causing unprecedented challenges such as urban poverty, and creation of suburban and informal districts which have contributed to cultural conflicts, decline in quality of life and so on. Urban management has been undergone huge costs by the hasty and unplanned intervention. Therefore, to renovate the city, we need to typology and classify this area to grasp the homogeneous context and main factors. The facilities and resources of the organizations related to urban renewal and rehabilitation require at first identify the worn tissues and prepare a map of the zoning of worn-out tissues. The typology of the urban fabric, taking advantage of a rigorous and versatile cartographic tool. This study has empirically demonstrated that this phenomenon related to many factors. Identifying effective factors helps adopt better urban policies, so these findings can scientific basis for urban policy and planning in order to reduce deterioration and well intervene in urban texture.

Keywords

Main Subjects

References

  1. بلیانی، یدالله و حکیم‏دوست، یاسر، 1393، اصول و مبانی پردازش داده‏های مکانی (فضایی) با استفاده از روش‏های تحلیل فضایی، تهران: آزادپیما.
  2. حاجی علی‏اکبری، کاوه و شفیعی، امیر، 1397، توسعة محله‏ای: چارچوبی برای محله‏های ناکارآمد شهر تهران، تهران: انتشارات شهرداری تهران، مرکز مطالعات و برنامه‏ریزی شهر تهران.
  3. زارع چاهوکی، محمدعلی، 1389، روش‏های تحلیل چندمتغیره در نرم‏افزار SPSS، تهران: انتشارات دانشکدة منابع طبیعی، دانشگاه تهران.
  4. زبردست، اسفندیار؛ خلیـلی، احمد و دهقانی، مصطفی، 1392، کاربرد روش تحلیل عاملی در شناسایی بافت‏های فرسودة شهری، نشریة هنرهای زیبا- معماری و شهرسازی، دورة ۱۸، ش 2، صص 27-42.
  5. زنگی‏آبادی، علی؛ خسروی، فرامرز و صحرائیان، زهرا، 1390، استخراج شاخص‏های شناسایی بافت فرسودة شهری با استفاده از سیستم اطلاعات جغرافیایی (مطالعۀ موردی: محدودة غربی بافت فرسودة شهر جهرم)، فصل‏نامة پژوهش‏هایجغرافیایانسانی، دورة 43، ش 78، صص 117-136.
  6. زینلی، سایه؛ حسینعلی، فرهاد؛ صادقی نیارکی، ابوالقاسم؛ کاظمی بیدختی، محمد و عفتی، میثم، 1394، تحلیل مکانی تصادفات در تقاطع‏های برون‏شهری با به‏کارگیری روش‏های خودهمبستگی مکانی و برآورد تراکم کرنل، مهندسی فناوری اطلاعات مکانی، دورة ۳، ش 2، صص 21-42.
  7. سیدیان، سیدعلی؛ علی‏نیا، سعید و حیدر نتاج، وحید، 1396، گونه‏شناسی بافت نمای شهری (با رویکرد شکلی) (نمونة موردی میدان امام خمینی (ره) تهران)، نشریة باغ نظر، دورة ۱۴، ش 53، صص 15-32.
  8. شاطریان، محسن و اکبری ارمکی، زکیه، 1394، رهیافت تجدید حیات شهری در راستای کاهش فرسودگی و فقر شهری (مطالعة موردی: بافت قدیم شهر کاشان)، فصل‏نامة جغرافیا، س ۱۳، ش 44، صص 119-142.
  9. صداقت رستمی، کبریا؛ اعتماد، گیتی؛ بیدرام، رسول و ملاذ، جعفر، 1390، تدوین شاخص‏های شناسایی بافت‏های ناکارآمد، برنامه‏ریزی فضایی (جغرافیا)، دورة ۱، ش 1، صص 103-120.
  10. کامروا، محمدعلی و دیگران، 1386، طرح پژوهشی «ارزیابی پنجاه سال مداخله در بافت‏های فرسودة شهری ایران»، تهران: سازمان نوسازی شهر تهران، انتشارات دانشگاه تهران.
  11. کلانتری، محسن؛ قزلباش، سمیه و جباری، کاظم، 1388، تحلیل فضایی بزهکاری شهری با استفاده از مدل تخمین تراکم کرنل مورد مطالعه: جرایم شرارت، نزاع، و درگیری در شهر زنجان، فصل‏نامة نظم و امنیت انتظامی، س ۲، ش 3، صص 73-100.
  12. لنگ، جان، 1383، آفرینش نظریة معماری: نقش علوم رفتاری در طراحی محیط، ترجمة علیرضا عینی‏فر، تهران: انتشارات دانشگاه تهران.
  13. لنگ، جان، 1393، طراحی شهری گونه‏شناسی رویه‏ها و طرح‏ها همراه با بیش از پنجاه مورد خاص، ترجمة سیدحسین بحرینی، تهران: انتشارات دانشگاه تهران.
  14. مرتضایی، گلناز؛ محمدی، محمود؛ نصراللهی، فرشاد و قلعه‏نویی، محمود، 1396، بررسی ریخت‏گونه‏شناسانة بافت‏های مسکونی جدید در راستای بهینه‏سازی مصرف انرژی اولیه (نمونة موردی: سپاهان شهر)، فصل‏نامة مطالعات شهری، دورة ۶، ش 24، صص 41-54.
  15. مهندسین مشاور شاران، 1396، شناسایی محله‏ها و محدوده‏های ناکارآمد هدف بازآفرینی شهری و راهکارهای اجرای آن، وزارت راه‏ و شهرسازی، شرکت بازآفرینی شهری ایران.
  16. مهندسین مشاور طرح و معماری، 1395، شناسایی و تهیة سند بهسازی و نوسازی محدوده‏ها و محلات هدف بازآفرینی شهر قم با دیدگاه شهرنگر، وزارت راه ‏و شهرسازی، شرکت بازآفرینی شهری ایران.
  17. میرسجادی، سیدامیر و فرکیش، هیرو، 1395، بازشناسی الگوها و شناخت فاکتورهای کالبدی تأثیرگذار در بافت مسکونی سنتی نیشابور، مجلة پژوهش‏های معماری اسلامی، دورة ۴، ش 4، صص 71-89.

18. Amorim, L.; NormandoBarros Filho, M. and Cruz, D., 2009, Urban texture and space configuration, In 7th International space syntax symposium.

19. Anas A., Arnott R., Small K.A., 1988, Urban spatial structure. Journal of Economic Literature 36: 1426-1463.

20. Anyumba, G., 2004, Urban types in rapidly urbanising cities: Analysis of formal and informal settlements in Dar-es-Salaam, Tanzania.

21. Beauregard, R. A., 2013, Voices of decline: the postwar fate of US cities, Second Edition, published 2012 by Routledge.

22. Belyani, Y. and Hakimdost, Y., 2014, The Principal of Spatial Data Analysis, Press: Azadpeyma Publication, Tehran. (In Persian)

23. Colaninno, N.; Cladera, J. R. and Pfeffer, K., 2011, An automatic classification of urban texture: form and compactness of morphological homogeneous structures in Barcelona, In 51st European.

24. Cramer Hill Redevelopment Study and Redevelopment Plan, 2004, South Jersey legal services.

25. Dayyani, L.; Pourtaheri, M.; Eftekhari, A. R. and Ahmadi, H., 2019, The identification and zoning of areas having rural deteriorated textures in the Tehran province by using KDE and GIS, Human and Ecological Risk Assessment: An International Journal, PP.1-30.

26. Donaldson, R. and Du Plessis, D., 2013, The urban renewal programme as an area-based approach to renew townships: The experience from Khayelitsha's Central Business District, Cape Town, Journal of Habitat International, Vol. 39, PP. 295-30.

27. Fol, S. and Cunningham-Sabot, E., 2010, Urban decline and shrinking cities: a critical assessment of approaches to urban shrinkage, In Annales de géographie, No. 4, PP. 359-383.

28. Friedrichs, J., 1993, A theory of urban decline: economy, demography and political elites, Journal of Urban Studies, Vol. 30, No. 6, PP. 907-917.

29. Haase, A.; Bernt, M.; Grossmann, K.; Mykhnenko, V. and Rink, D., 2013, Varieties of shrinkage in European cities, European Urban and Regional Studies, PP. 1-17.

30. Haase, A.; Rink, D.; Grossmann, K.; Bernt, M. and Mykhnenko, V., 2014, Conceptualizing urban shrinkage, Journal of Environment and Planning A, Vol. 46, No.7, PP. 1519-1534.

31. Haji-Ali-Akbari, K. and Shafiei, A., 2018, Neighborhood Development: A Framework for Inefficient Neighborhoods in Tehran, Tehran Municipality, Tehran Urban Planning and Research Center Publications, Teheran. (In Persian)

32. Hecht, R.; Herold, H.; Meinel, G. and Buchroithner, M., 2013, Automatic derivation of urban structure types from topographic maps by means of image analysis and machine learning, In Proceedings of the 26th International Cartographic Conference, Dresden, Germany.

33. Kalantari, M.; Ghezelbash, S. and Jabari, K., 2010, Spatial Analysis of Urban Crime Using the Kernel Density Estimation Case Study: Crimes in Evil, Strife and Conflict in Zanjan City, Journal of Discipline and Security Guard, Vol. 2, No. 3, PP. 119-142. (In Persian)

34. Kamrava, M. A. and et al., 2010, Research Project “Evaluation of Fifty Years of Intervention in Iran's Urban Decade Texture”, Tehran Renovation Organization, Tehran University Publications, Tehran. (In Persian)

35. La Rosa, D.; Riccardo, P.; Barbarossa, L. and La Greca, P., 2017, Assessing spatial benefits of urban regeneration programs in a highly vulnerable urban context: A case study in Catania, Italy, Journal of Landscape and Urban Planning, Vol. 157, PP. 180-192.

36. Lang, J., 2004, Urban Design, Translated by: Bahrainy, S. H., Tehran University Publications, Tehran. (In Persian)

37. Lang, J., 2005, Creating Architectural Theory: The Role of the Behavioral Sciences in Environmental Design, Translated by: Eynifar, A., Tehran University Publications, Tehran. (In Persian)

38. Lang, Th., 2005, Insights in the British debate about urban decline and urban regeneration, Erkner, Leibniz‐Institute for Regional Development and Structural Planning.

39. Larkham, Peter J., 2006, The study of urban form in Great Britain, Urban Morphology, Vol. 10, No. 2, PP. 117-141.

40. Lovra, E., 2016, Urban Tissue Typology and Urban Typology (1868-1918); Special Cases: Zagreb and Rijeka, Prostor: znanstveni časopis za arhitekturu i urbanizam, Vol. 24, No. 2, PP. 202-215.

41. Mirsajadi, S. A. and Farkisch H., 2017, Recognition of Typology and Effective Physical Factors in Traditional Residential Tissue of Neyshabur, Journal of Islamic Architectural Research, Vol. 4, No. 4, PP. 71-89. Vol. 4, No. 4, PP. 71-89. (In Persian)

42. Mortezaei, G.; Mohamadi, M.; Nasrollahi, F. and Ghale Noee, M., 2017, Typo-morphological evaluation of new residential urban texture in order to optimize primary energy consumption case study: Sepahanshahr, Journal of Urban Studies, Vol. 6, No. 24, PP. 41-54. (In Persian)

43. Philadelphia City Planning Commission, 2006, Amendment to the East Wick Redevelopment Area Plan, City of Philadelphia, Web Site.

44. Pinto, S. and Sablik, T., 2016, Understanding Urban Decline, Annual Report, PP. 4-20.

45. Rådberg, J., 1996, Towards a Theory of Sustainability and Urban Quality: A New Method for Typological Urban Classification, In Proceedings of the Conference of the International Association for People-Environment Studies—IAPS, Vol. 14, PP. 384-392.

46. Rapoport, A., 1990, Vernacular Architecture, in Turan M., (eds.); Current Challenges in the Environmental Social Sciences, England: Avebury, Aldershot.

47. Roberts, P. and Sykes, H. (Eds.), 2000, Urban regeneration: a handbook, London: Sage.

48. Sedaghat-Rostami, K.; Etemad, G. K.; Bidram, R. and Molaz, J., 2010, Determining the Criteria for Recognition of Urban Distressed Area, Journal of Spatial Planning (Geology), Vol. 1, No. 1, PP. 103-120. (In Persian)

49. Sedghi, V. and Nematimehr, M., 2016, Identification and prioritization of decline factors in Karaj distressed areas by applying the fuzzy analytic hierarchy process (FAHP), Int. J. Architect. Eng. Urban Plan, Vol. 26, No. 2, PP. 173-182.

50. Seyedian, S.; Alinia, S. and Heidar-Nattaj, V., 2017, The Typology of Urban Facade Texture (in an approach to shape scrutiny) (Case study of Imam Khomeini Square in Tehran), Journal of Bagh- E Nazar, Vol. 14, No. 53, PP. 15-32. (In Persian)

51. Sharan Consulting Engineers, 2017, Identifying Inefficient Neighborhoods and Areas of Urban Regeneration and its Implementation Strategies, The Ministry of Roads and Urban Development, Urban Regeneration Compny of Iran. (In Persian)

52. Shaterian, M. and Akbar-Armaki, Z., 2016, Urban Rehabilitation Approach to Reduce Urban Decline and Urban Poverty (Case Study: Old Fabric of Kashan City), Journal of Geology, Vol. 13, No. 44, PP. 119-142. (In Persian)

53. Solecki, W.; Seto, K. C.; Balk, D.; Bigio, A.; Boone, C. G.; Creutzig, F. and Zwickel, T., 2015, A conceptual framework for an urban areas typology to integrate climate change mitigation and adaptation, Journal of Urban Climate, Vol. 14, PP. 116-137.

54. Steiniger, S.; Lange, T.; Burghardt, D. and Weibel, R., 2008, An approach for the classification of urban building structures based on discriminant analysis techniques, Journal of Transactions in GIS, Vol. 12, No 1, PP. 31-59.

55. Tarh and Memari Consulting Engineers, 2016, Identifying and Preparing Document of Renovation and Rehabilitation Areas and Neighborhoods of Urban Regeneration of Qom City With the Urbanistic Perspective, The Ministry of Roads and Urban Development, Urban Regeneration Compny of Iran. (In Persian)

56. Vigdor, J. L., 2010, Is urban decay bad? Is urban revitalization bad too?, Journal of Urban Economics, Vol. 63. No. 3, PP. 277-289.

57. Weaver, R. C. and Bagchi-Sen, S., 2013, Spatial analysis of urban decline: The geography of blight, Journal of Applied Geography, Vol. 40, PP. 61-70.

58. Zangiabadi, A.; Khosravi, F. and Sahraeian, Z., 2011, Extraction Indexes of Urban Distressed Structure (The Case Study: Western Area Decade Texture of Jahrom City), Journal of Human Geography Research, Vol. 43, No. 78, PP. 117-136. (In Persian)

59. Zare-Chahoki, M. A., 2011, Methods of Multivariate Analysis with SPSS, Publications of Faculty of Natural Resources, Tehran University, Tehran. (In Persian)

60. Zebardast, E.; Khalili, A. and Dehqani, M., 2013, Application of Factor Analysis Method in Identification of Decayed Urban Fabrics An, Journal of Fine Arts - Architecture and Urbanism, Vol. 18, No. 2, PP. 27-42. (In Persian)

61. Zeynali, S.; Hosseinali, F.; Sadeghi-Niaraki, A.; Kazemi-Beydokhti, M. and Effati, M., 2015, Spatial Analysis of Accidents at the Suburban Intersections Using Kernel Density Estimation and Spatial Autocorrelation Methods, Journal of Geospatial Information Technology (JGIT),Vol. 3, No. 2, PP. 21-42. (In Persian)

Human Geography Research
Volume 53, Issue 2
July 2021
Pages 365-387

Files

History

  • Receive Date: 03 October 2018
  • Revise Date: 24 August 2019
  • Accept Date: 24 August 2019

Share

How to cite

Statistics