تحلیل کالبدی- فضایی شهر خرم‌آباد با استفاده از شاخص‌های رشد هوشمند شهری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری جغرافیا و برنامه‌ریزی شهری، استانداری کرمان، کرمان، ایران

2 دانشجوی دکتری جغرافیا و برنامه‌ریزی شهری، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران

چکیده

افزایش مشکلات ناشی از تراکم جمعیت در شهرها، صاحب­نظران را به چاره­اندیشی و حل معضلات شهری واداشت و برای کاهش معضلات ناشی از رشد بی­رویۀ فضاهای شهری، صاحب­نظران انگاره رشد هوشمند شهری را مطرح نمودند، رشد هوشمند شهری به عنوان ابزاری توانمند در سنجش میزان تمرکز یا پراکنده بودن رشد یک شهر در چارچوب الگوهای رایج و ایده­آل، امروزه نقش غیر قابل انکاری در توسعه، تغییر و شکل­دهی نقاط سکونتی انسان­ها به ویژه شهرها ایفا می­کند. از این رو هدف پژوهش حاضر تحلیل کالبدی- فضایی رشد هوشمند شهر خرم­آباد است. پژوهش حاضر به لحاظ هدف توسعه­ای ـ کاربردی و از لحاظ روش­شناسی کمی - تحلیلی مبتنی بر مطالعات کتابخانه­ای و داده­های فضایی است. در تجزیه‌وتحلیل اطلاعات این پژوهش از روش­های آماری- گرافیکی در قالب نرم­افزار ArcGIS و همچنین نرم­افزارهای Excel و GeoDa بهره گرفته شده است. نتایج حاصل از تحلیل شاخص­ها با استفاده از آزمون­های گرافیک مبنا نشان می­دهد که شهر خرم­آباد در زمینه شاخص­های منتخب فاصله­ی چشمگیری با اصول رشد هوشمند شهری دارد. این امر نشانگر تفاوت چشمگیر شاخص­های منتخب با اصول رشد هوشمند شهری است. نتایج آزمون­های گرافیک مبنا و آزمون­های نموداری با هم همسو بوده و در این زمینه توافق و سازگاری بین این آزمون­ها وجود دارد که درجه تجمع­پذیری کم، توزیع نامتعادل در سطح شهر خرم­آباد، پراکندگی، خوشه­ای بودن، توسعه جسته و گریختگی و توسعه منفصل و ناپیوسته بسیار زیاد و به طور کلی رشد پراکنش افقی بی­رویه است.

کلیدواژه‌ها


عنوان مقاله [English]

Physical-Spatial Analysis of Khorramabad City Using Urban Intelligence Growth Indices

نویسندگان [English]

  • Marzieh Afzali 1
  • Yaghob Abdali 2
  • Asghar Heydari 2
1 PhD in Geography and Urban Planning, Government of Kerman, Kerman, Iran.
2 Ph.D. Student of Geography and Urban Planning, Faculty of Geography, University of Tehran
چکیده [English]

Increasing the problems caused by population density in cities has led the owners to discriminate and solve urban problems. In order to mitigate the dilemmas caused by the unsustainable growth of urban spaces, think tanks have suggested the idea of smart urban growth, urban intelligent growth as A powerful tool in measuring the concentration or dispersion of a city's growth within the framework of the common and ideal patterns nowadays plays an indelible role in the development, transformation and shaping of human settlements, especially cities. Therefore, the purpose of the present research is to investigate the physical-spatial intelligence of urban intelligence using geographic data. The present research is based on the objective of developmental and quantitative analytical methodology based on library studies and spatial data. In analyzing the data of this research, the statistical-graphical methods have been used in the ArcGIS, Excel and GeoDa. The results of the analysis of the indices using the base-based graphic tests show that Khorramabad city has a long way to go with the principles of urban intelligence in terms of selected indicators. This indicates the significant difference between selected indicators and the principles of smart urban growth. The results of basic graphics and graphing tests are in line with each other. In this regard, there is agreement and compatibility between these tests that low degree of aggregation, unbalanced distribution in Khorramabad city, dispersion, cluster, development, and fatigue and the development of disjointed and discontinuous, and in general the growth of horizontal dispersion is superfluous.
Introduction: Urban superconductivity can be defined as continuous unobstructed growth on the margins of existing clusters or along roads. In the sprawling urban landscape, varying degrees of economic, social, and environmental impacts have accumulated. Despite its negative impacts, urban sprawl is still a growing trend. Therefore, the need to nurture compact cities has been acknowledged by policy and knowledge. A compact city is a spatial form that is well equipped with physical compaction, high density development and public transportation to respond to many urban problems such as land use in marginal areas, energy and resource waste, air pollution, access and social segregation.
Khorramabad is one of the cities that need to implement smart growth policy due to physical development constraints. The purpose of this study was to determine the spatial analysis of urban smart growth of Khorramabad city in order to achieve physical growth indices. Therefore, the purpose of this paper is not to create new indicators, but to extend existing ones based on the physical concepts of smart growth to the studied city and to measure the proximity of the studied city to the smart growth physical indicators.
 
Methodology: The purpose of this study is to develop an applied and quantitative-analytical methodology based on library studies and spatial data. The statistical population of this study includes residential, commercial, educational, higher education, religious, cultural, tourist, catering, health, sports, administrative and law enforcement, green, military, industrial, urban and transportation facilities and equipment. Bayer is a city of Khorramabad. Statistical-graphical methods in the form of ArcGIS software as well as Excel and GeoDa software were used for data analysis.
 
Results and discussion: Based on calculations and analyzes using existing geographical data of Khorramabad, residential land with 27.83 m 2, Higher education 0.86 m 2 and green space 8.23 m 2 are in desirable condition. It is higher than the standard net per capita, but other uses are in a poor state and lower than the standard net per capita.
The nearest neighbor index test revealed that indices of higher education, cultural, religious, military and sport were randomly distributed throughout the city of Khorramabad; health, residential and residential indicators were scattered. Distributed throughout the city of Khorramabad, and features administrative, military, training, Bayer, facilities, commercial, medical, industrial and green spaces across the city of Khorramabad in specific clusters. This factor illustrates the inaccuracy of access to the above indicators.
The average center of all selected landmarks in Khorramabad city largely corresponds to the geographical center of Khorramabad city. It is located around the center of the commercial district of Khorramabad. The standard deviation ellipse of all the indices studied is highly elongated, indicating that the set of selected indices of the Khorramabad city area tends to extend north-south and along the valley, with most of the indices selected tending toward Outside the city they have a north and south direction.
To compare and compare selected indices in Khorramabad city with smart growth principles, dispersion chart and box tests were used. The box diagram illustrates the results of the dispersion diagram in relation to the selected indices in the city of Khorramabad, ie, the diagram confirms the dispersion diagram results in a different way.
 
Conclusion: The results of the analysis of indices using graphical basis tests showed that Khorramabad city in terms of residential, commercial, educational, higher education, religious, cultural, tourist-catering, health, sports, Administrative, law enforcement, green space, military, industries, utilities, transportation, and waste areas are also within easy reach of smart growth principles. This illustrates the significant difference between the selected indicators and the principles of smart urban growth. It was also concluded that the unbalanced distribution throughout the city of Khorramabad is dispersal, clustering, junction-evaporation, discontinuous-discontinuous development, and overall horizontal dispersion growth.
 

کلیدواژه‌ها [English]

  • Physical-Spatial Analysis
  • Intelligent Ggrowth
  • Graphic Patterns
  • Khorramabad City
  1. Berdi Anamradinejad, Rahim-Nikpour, Amer and Hassani, Zohreh (2018). Physical-Spatial Analysis of Urban Areas Based on Urban Smart Growth Indicators (Case Study: Babol City). Urban Planning and Research Quarterly, Volume 9, Number 34: 30-19.
  2. Pourmohammadi, MR (2016). Urban Land Use Planning. Khome Publications, Tehran.
  3. Hatami, Davood and Rahmani, Ismail (2017). Analysis of Chabahar Spatial-Physical Growth Pattern with Intelligent Growth Approach. Journal of Urban Civilization Studies, Volume I, Number 2: 139- 118.
  4. Khodaei, Zahra and Teymuri, Somayeh (2017). An Analysis on the Spatial Distribution of Urban Poverty in Khorramabad City Areas. Journal of Socio-Cultural Development Studies, Volume 6, Number 3: 58-33.
  5. Ziyari, Karamatollah (2013). Urban Land Use Planning. Second edition, Tehran University Press, Tehran.
  6. Ziyari, Keramatollah; Mahdinejad, Hafez and Parhiz, Faryad (2009). Fundamentals and Urban Planning Techniques, Chabahar International University Press, Chabahar.
  7. Shokrgozar, Asghar-Jamshidi, Zahra & Jamshidi, Parvaneh (2015). Evaluation of Urban Smart Growth Principles and Strategies in Rasht Future Development Based on Helderen Population Density Model. Journal of Geography and Development, Volume 13, Number 45-64.
  8. Abdollahi, Ali Asghar & Khodaman, Zahra (2016). Physical Spatial Evaluation of Smart Growth Indicators Using the WASPAS Model (Case Study: Yazd City Areas). Journal of Urban Social Geography, Volume 3, Issue 3, Issue 8: 99-79.
  9. Asgari, Ali (2011). Spatial Statistics Analytics with. Tehran Municipality Information and Communication Technology Organization Publication, First Edition, Tehran.
  10. Ghorbani, Rasool and Noshad, Somayeh (2008). Smart Growth Strategy in Urban Development Principles and Solutions. Journal of Geography and Development, Volume 6, Issue 12: 163-180.
  11. Iran Statistics Center (2016). Results of the General Census of Population and Housing. https://www.amar.org.ir/.
  12. Amood Consulting Engineers (2007). Empowerment studies and organization of informal settlements of Khorramabad. Lorestan Housing and Urban Development Organization.
  13. Mirzapour, Solaman (2005). Causes of physical development of Khorramabad city. Undergraduate Thesis, Supervisor Dr. Barat Ali Khakpour, Faculty of Humanities, Ferdowsi University of Mashhad.
  14. Albino, V., Berardi, U., Dangelico, R.M., 2015. Smart cities: definitions, dimensions,
  15. Andersson, E., McPhearson, T., Kremer, P., Gomez-Baggethun, E., Haase, D., Tuvendal, M., & Wurster, D. (2015). Scale and context dependence of ecosystem service providing units. Ecosystem Services, 12, 157-164.‏
  16. Banzhaf, H. S., & Lavery, N. (2010). Can the land tax help curb urban sprawl? Evidence from growth patterns in Pennsylvania. Journal of Urban Economics, 67(2), 169-179.‏
  17. Batisani, N., & Yarnal, B. (2011). Elasticity of capital-land substitution in housing construction, Gaborone, Botswana: Implications for smart growth policy and affordable housing. Landscape and urban planning, 99(2), 77-82.‏
  18. Couch, C., Leontidou, L., Arnstberg, K.-O., (2007). Introduction: definitions, theories and methods of comparative analysis. In: Couch, C., Leontidou, L., Petschel-Held, G. (Eds.), Urban Sprawl in Europe. Landscapes, Land-Use Change & Policy. Blackwell Publishing Ltd, Blackwell, Oxford, pp. 3–38.
  19. EC (European Commission), (2010). Europe 2020. A European Strategy for Smart, Sustainable and Inclusive Growth. EC, Brussels.
  20. EC (European Commission), (2012a). Connecting smart and sustainable growth through smart specialisation. A Practical Guide for ERDF Managing Authorities. Publications Office of the European Union, Luxembourg.
  21. EEA, 2016. Urban Sprawl in Europe. Joint EEA-FOEN Report. Publication Office of the European Union, Luxembourg.
  22. ESRI, (2016). An overview of the spatial statistics toolbox. ArcGIS 10.5 Online Help System (ArcGIS 10.5 Desktop, Release 10.5, 2016). Environmental Systems Research Institute, Redlands, CA.
  23. Hankey, S., & Marshall, J. D. (2010). Impacts of urban form on future US passenger-vehicle greenhouse gas emissions. Energy Policy, 38(9), 4880-4887.‏
  24. Jiang, L., Deng, X., & Seto, K. C. (2013). The impact of urban expansion on agricultural land use intensity in China. Land Use Policy, 35, 33-39.‏
  25. La Greca, P., Barbarossa, L., Ignaccolo, M., Inturri, G., & Martinico, F. (2011). The density dilemma. A proposal for introducing smart growth principles in a sprawling settlement within Catania Metropolitan Area. Cities, 28(6), 527-535.‏
  26. Neuman, M., (2005). The compact city fallacy. J. Plan. Educ. Res. 25, 11–26.
  27. OECD, 2012. Compact City Policies. A Comparative Assessment. OECD Publishing, Paris.
  28. Papa, R., Gargiulo, C., Galderisi, A., (2013). Towards an urban plannerś perspective on smart city. TeMA 1, 5–17.
  29. Smart Growth Network, (2003). Getting to Smart Growth. 100 Policies for implementation. https://www.epa.gov/sites/production/files/201401/documents/gettos. (Accessed 17 March 2016).
  30. Susanti, R., Soetomo, S., Buchori, I., & Brotosunaryo, P.M. (2016). Smart growth, smart city and density: in search of the appropriate indicator for residential density in Indonesia. Procedia-Social and Behavioral Sciences, 227, 194-201.‏
  31. Turner, M. A. (2007). A simple theory of smart growth and sprawl. Journal of Urban Economics, 61(1), 21-44.‏
  32. United Nations, (2012). World Urbanization Prospects. The 2011 Revision. Department of Economic and Social Affairs, New York.
  33. Whitehead, M., (2012). The sustainable city: an obituary? On the future form and prospects of sustainable urbanism. In: Flint, R., Raco, M. (Eds.), the Future of Sustainable Cities: Critical Reflections. The Policy Press, Chicago, pp.